From 9ad87ace0a5111b9ee0f9c366bb2ab61205abb46 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 12 Mar 2024 02:11:29 -0700
Subject: [PATCH 001/122] chore: Upgrade to TRT 10.0

---
 .../converters/impl/constant_pad.cpp          |  2 +-
 .../converters/impl/conv_deconv.cpp           |  6 +--
 .../converters/impl/interpolate.cpp           | 50 +++++++++----------
 core/conversion/converters/impl/linear.cpp    | 30 ++++++-----
 core/runtime/TRTEngine.cpp                    | 47 ++++++++++++-----
 5 files changed, 81 insertions(+), 54 deletions(-)

diff --git a/core/conversion/converters/impl/constant_pad.cpp b/core/conversion/converters/impl/constant_pad.cpp
index 4191cb1bab..20a091e730 100644
--- a/core/conversion/converters/impl/constant_pad.cpp
+++ b/core/conversion/converters/impl/constant_pad.cpp
@@ -55,7 +55,7 @@ auto constant_pad_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns
            util::toDims(c10::IntArrayRef(stride)));
        TORCHTRT_CHECK(slice_layer, "Unable to create slice layer from node: " << *n);
        slice_layer->setName((util::node_info(n) + "_slice").c_str());
-       slice_layer->setMode(nvinfer1::SliceMode::kFILL);
+       slice_layer->setMode(nvinfer1::SampleMode::kFILL);
        slice_layer->setInput(4, *value_itensor);
 
        if (ctx->input_is_dynamic) {
diff --git a/core/conversion/converters/impl/conv_deconv.cpp b/core/conversion/converters/impl/conv_deconv.cpp
index 66620197a9..bf0df00c64 100644
--- a/core/conversion/converters/impl/conv_deconv.cpp
+++ b/core/conversion/converters/impl/conv_deconv.cpp
@@ -61,7 +61,7 @@ nvinfer1::ILayer* add_bias_layer(
   auto* sliceLayer = ctx->net->addSlice(*input_tensor, dummy, dummy, stride);
   sliceLayer->setInput(1, *start);
   sliceLayer->setInput(2, *size);
-  sliceLayer->setMode(nvinfer1::SliceMode::kFILL);
+  sliceLayer->setMode(nvinfer1::SampleMode::kFILL);
   nvinfer1::ITensor* slice_output = sliceLayer->getOutput(0);
 
   nvinfer1::Dims constantDims;
@@ -194,7 +194,7 @@ bool add_conv_deconv(ConversionCtx* ctx, const torch::jit::Node* n, args& args)
       nvinfer1::IConvolutionLayer* convLayer =
           ctx->net->addConvolutionNd(*in, num_output_maps, filter_dim, kernel_weights, bias.data);
       convLayer->setStrideNd(stride);
-      convLayer->setPaddingMode(nvinfer1::PaddingMode::kCAFFE_ROUND_DOWN);
+      convLayer->setPaddingMode(nvinfer1::PaddingMode::kEXPLICIT_ROUND_DOWN);
       convLayer->setPaddingNd(padding);
       convLayer->setPostPadding(out_padding);
       convLayer->setDilationNd(dilation);
@@ -293,7 +293,7 @@ bool add_conv_deconv(ConversionCtx* ctx, const torch::jit::Node* n, args& args)
     TORCHTRT_CHECK(conv, "Unable to create convolution layer from node: " << *n);
 
     conv->setStrideNd(stride);
-    conv->setPaddingMode(nvinfer1::PaddingMode::kCAFFE_ROUND_DOWN);
+    conv->setPaddingMode(nvinfer1::PaddingMode::kEXPLICIT_ROUND_DOWN);
     conv->setPaddingNd(padding);
     conv->setPostPadding(out_padding);
     conv->setDilationNd(dilation);
diff --git a/core/conversion/converters/impl/interpolate.cpp b/core/conversion/converters/impl/interpolate.cpp
index fad2ca5121..61721e3d2c 100644
--- a/core/conversion/converters/impl/interpolate.cpp
+++ b/core/conversion/converters/impl/interpolate.cpp
@@ -72,7 +72,7 @@ void resize_layer_size(
     nvinfer1::ITensor* in,
     std::vector<int64_t> out_shape,
     std::vector<float> scales,
-    nvinfer1::ResizeMode mode,
+    nvinfer1::InterpolationMode mode,
     bool align_corners = false) {
   TORCHTRT_CHECK((out_shape.size() > 0) ^ (scales.size() > 0), "only one of out_shape or scales should be defined");
   auto resize_layer = ctx->net->addResize(*in);
@@ -141,7 +141,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  float scale = args[2].IValue()->toDouble();
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 1] = scale;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -150,7 +150,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -172,7 +172,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  float scale = scale_factors[0];
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 1] = scale;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -181,7 +181,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -203,7 +203,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -212,7 +212,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -236,7 +236,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -245,7 +245,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -270,7 +270,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  padded_scales[padded_scales.size() - 3] = scale_d;
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -279,7 +279,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -306,7 +306,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  padded_scales[padded_scales.size() - 3] = scale_d;
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -315,7 +315,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -336,7 +336,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  float scale = args[3].IValue()->toDouble();
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 1] = scale;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -345,7 +345,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
@@ -368,7 +368,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  float scale = scale_factors[0];
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 1] = scale;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -377,7 +377,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
@@ -400,7 +400,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -410,7 +410,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
@@ -435,7 +435,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -445,7 +445,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
@@ -470,7 +470,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  padded_scales[padded_scales.size() - 3] = scale_d;
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -480,7 +480,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
@@ -507,7 +507,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  padded_scales[padded_scales.size() - 3] = scale_d;
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -517,7 +517,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
diff --git a/core/conversion/converters/impl/linear.cpp b/core/conversion/converters/impl/linear.cpp
index 6289334736..ad0931452a 100644
--- a/core/conversion/converters/impl/linear.cpp
+++ b/core/conversion/converters/impl/linear.cpp
@@ -40,22 +40,26 @@ auto linear_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns().pat
          in = in_shuffle->getOutput(0);
        }
 
-       auto w_tensor = args[1].IValue()->toTensor();
-       Weights w = Weights(ctx, w_tensor);
+       // Convert w_tensor to ITensor
+       auto weight_tensor = args[1].IValue()->toTensor();
+       weight_tensor = tensor_to_const(ctx, weight_tensor, util::node_info(n) + "_weight")
 
-       nvinfer1::ILayer* new_layer;
-       if (!args[2].IValue()->isNone()) {
-         Weights b(ctx, args[2].IValue()->toTensor());
-         new_layer = ctx->net->addFullyConnected(*in, w.num_output_maps, w.data, b.data);
-       } else {
-         LOG_DEBUG("There is no bias for the linear layer");
-         new_layer = ctx->net->addFullyConnected(*in, w.num_output_maps, w.data, Weights().data);
-       }
+           auto mm_layer = ctx->net->addMatrixMultiply(
+               *in, nvinfer1::MatrixOperation::kNONE, *weight_tensor, nvinfer1::MatrixOperation::kNONE);
+
+       TORCHTRT_CHECK(mm_layer, "Unable to create linear layer from node: " << *n);
+       mm_layer->setName(util::node_info(n).c_str());
 
-       TORCHTRT_CHECK(new_layer, "Unable to create linear layer from node: " << *n);
+       auto mm_output = mm_layer->getOutput(0);
 
-       new_layer->setName(util::node_info(n).c_str());
-       auto out_tensor = ctx->AssociateValueAndTensor(n->outputs()[0], new_layer->getOutput(0));
+       if (!args[2].IValue()->isNone()) {
+         // Convert bias to ITensor
+         auto bias_tensor = args[2].IValue()->toTensor();
+         bias_tensor = tensor_to_const(ctx, bias_tensor, util::node_info(n) + "_bias");
+         mm_output = add_elementwise(
+             ctx, nvinfer1::ElementWiseOperation::kSUM, mm_output, bias_tensor, util::node_info(n) + "_bias_add");
+       }
+       auto out_tensor = ctx->AssociateValueAndTensor(n->outputs()[0], mm_output);
 
        LOG_DEBUG("Output tensor shape: " << out_tensor->getDimensions());
 
diff --git a/core/runtime/TRTEngine.cpp b/core/runtime/TRTEngine.cpp
index 92e5d7a8ff..aa1ef7fc31 100644
--- a/core/runtime/TRTEngine.cpp
+++ b/core/runtime/TRTEngine.cpp
@@ -120,16 +120,25 @@ TRTEngine::TRTEngine(
   } else {
     uint64_t inputs_size = _in_binding_names.size();
     in_binding_names.resize(inputs_size);
-    for (size_t pyt_idx = 0; pyt_idx < inputs_size; pyt_idx++) {
+    for (uint64_t pyt_idx = 0; pyt_idx < inputs_size; pyt_idx++) {
       auto binding_name = _in_binding_names[pyt_idx];
-      auto trt_idx = cuda_engine->getBindingIndex(binding_name.c_str());
-      std::string engine_binded_name = cuda_engine->getIOTensorName(trt_idx);
-      TORCHTRT_CHECK(
-          (binding_name == engine_binded_name),
-          "Could not find a TensorRT engine binding for input named " << binding_name);
+      // Check if the binding name provided is in the list of engine's bindings
+      // by iterating through nbIOTensors and verify it is an input binding
+      bool is_binding = false, is_input = false;
+      int32_t trt_idx;
+      for (int32_t idx = 0; idx < cuda_engine->getNbIOTensors(); idx++) {
+        std::string curr_bind_name = cuda_engine->getIOTensorName(idx);
+        if (curr_bind_name == binding_name) {
+          is_binding = true;
+          trt_idx = idx;
+          if (cuda_engine->getTensorIOMode(binding_name.c_str()) == nvinfer1::TensorIOMode::kINPUT) {
+            is_input = true;
+          }
+        }
+      }
+      TORCHTRT_CHECK(is_binding, "Could not find a TensorRT engine binding for input named " << binding_name);
       TORCHTRT_CHECK(
-          (cuda_engine->getTensorIOMode(binding_name.c_str()) == nvinfer1::TensorIOMode::kINPUT),
-          "Binding " << binding_name << " specified as input but found as output in TensorRT engine");
+          is_input, "Binding " << binding_name << " specified as input but found as output in TensorRT engine");
       LOG_DEBUG(
           "Input binding name: " << binding_name << " has TensorRT binding index: " << trt_idx
                                  << ", Torch binding index: " << pyt_idx);
@@ -141,11 +150,25 @@ TRTEngine::TRTEngine(
     out_binding_names.resize(outputs);
     for (size_t pyt_idx = 0; pyt_idx < outputs; pyt_idx++) {
       auto binding_name = _out_binding_names[pyt_idx];
-      auto trt_idx = cuda_engine->getBindingIndex(binding_name.c_str());
-      TORCHTRT_CHECK((trt_idx != -1), "Could not find a TensorRT engine binding for output named " << binding_name);
+      // Check if the binding name provided is in the list of engine's bindings
+      // by iterating through nbIOTensors and verify it is an output binding
+      bool is_binding = false, is_output = false;
+      int32_t trt_idx;
+      for (int32_t idx = 0; idx < cuda_engine->getNbIOTensors(); idx++) {
+        std::string curr_bind_name = cuda_engine->getIOTensorName(idx);
+        if (curr_bind_name == binding_name) {
+          is_binding = true;
+          trt_idx = idx;
+          if (cuda_engine->getTensorIOMode(binding_name.c_str()) == nvinfer1::TensorIOMode::kOUTPUT) {
+            is_output = true;
+          }
+        }
+      }
+
+      TORCHTRT_CHECK(is_binding, "Could not find a TensorRT engine binding for output named " << binding_name);
       TORCHTRT_CHECK(
-          !(cuda_engine->getTensorIOMode(binding_name.c_str()) == nvinfer1::TensorIOMode::kINPUT),
-          "Binding " << binding_name << " specified as output but found as input in TensorRT engine");
+          is_output, "Binding " << binding_name << " specified as output but found as input in TensorRT engine");
+
       LOG_DEBUG(
           "Output binding name: " << binding_name << " has TensorRT binding index: " << trt_idx
                                   << ", Torch binding index: " << inputs_size + pyt_idx);

From a655c9a29113079b2da04d54ca574d7c97db6b36 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 12 Mar 2024 16:27:16 -0700
Subject: [PATCH 002/122] chore: updates to trt api

---
 core/conversion/converters/impl/linear.cpp       | 16 ++++++++--------
 cpp/include/torch_tensorrt/ptq.h                 |  8 ++++----
 py/torch_tensorrt/csrc/torch_tensorrt_py.cpp     |  5 +++++
 .../dynamo/conversion/_TRTInterpreter.py         |  4 ++--
 .../dynamo/conversion/_conversion.py             |  3 ++-
 py/torch_tensorrt/dynamo/conversion/impl/conv.py |  2 +-
 .../dynamo/conversion/impl/deconv.py             |  2 +-
 7 files changed, 23 insertions(+), 17 deletions(-)

diff --git a/core/conversion/converters/impl/linear.cpp b/core/conversion/converters/impl/linear.cpp
index ad0931452a..39f9cb055d 100644
--- a/core/conversion/converters/impl/linear.cpp
+++ b/core/conversion/converters/impl/linear.cpp
@@ -41,11 +41,10 @@ auto linear_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns().pat
        }
 
        // Convert w_tensor to ITensor
-       auto weight_tensor = args[1].IValue()->toTensor();
-       weight_tensor = tensor_to_const(ctx, weight_tensor, util::node_info(n) + "_weight")
-
-           auto mm_layer = ctx->net->addMatrixMultiply(
-               *in, nvinfer1::MatrixOperation::kNONE, *weight_tensor, nvinfer1::MatrixOperation::kNONE);
+       auto weight = args[1].IValue()->toTensor();
+       auto weight_tensor = tensor_to_const(ctx, weight, util::node_info(n) + "_weight");
+       auto mm_layer = ctx->net->addMatrixMultiply(
+           *in, nvinfer1::MatrixOperation::kNONE, *weight_tensor, nvinfer1::MatrixOperation::kNONE);
 
        TORCHTRT_CHECK(mm_layer, "Unable to create linear layer from node: " << *n);
        mm_layer->setName(util::node_info(n).c_str());
@@ -54,10 +53,11 @@ auto linear_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns().pat
 
        if (!args[2].IValue()->isNone()) {
          // Convert bias to ITensor
-         auto bias_tensor = args[2].IValue()->toTensor();
-         bias_tensor = tensor_to_const(ctx, bias_tensor, util::node_info(n) + "_bias");
-         mm_output = add_elementwise(
+         auto bias = args[2].IValue()->toTensor();
+         auto bias_tensor = tensor_to_const(ctx, bias, util::node_info(n) + "_bias");
+         auto bias_add_layer = add_elementwise(
              ctx, nvinfer1::ElementWiseOperation::kSUM, mm_output, bias_tensor, util::node_info(n) + "_bias_add");
+         mm_output = bias_add_layer->getOutput(0);
        }
        auto out_tensor = ctx->AssociateValueAndTensor(n->outputs()[0], mm_output);
 
diff --git a/cpp/include/torch_tensorrt/ptq.h b/cpp/include/torch_tensorrt/ptq.h
index d8570f0e6e..e88da06b0c 100644
--- a/cpp/include/torch_tensorrt/ptq.h
+++ b/cpp/include/torch_tensorrt/ptq.h
@@ -21,10 +21,10 @@
 #include "torch_tensorrt/macros.h"
 
 #ifndef DOXYGEN_SHOULD_SKIP_THIS
-namespace nvinfer1 {
-class IInt8Calibrator;
-class IInt8EntropyCalibrator2;
-} // namespace nvinfer1
+// namespace nvinfer1 {
+// class IInt8Calibrator;
+// class IInt8EntropyCalibrator2;
+// } // namespace nvinfer1
 
 namespace torch_tensorrt {
 namespace ptq {
diff --git a/py/torch_tensorrt/csrc/torch_tensorrt_py.cpp b/py/torch_tensorrt/csrc/torch_tensorrt_py.cpp
index 33c7e27398..c0655d9907 100644
--- a/py/torch_tensorrt/csrc/torch_tensorrt_py.cpp
+++ b/py/torch_tensorrt/csrc/torch_tensorrt_py.cpp
@@ -2,6 +2,7 @@
 #include "pybind11/stl.h"
 
 #include "ATen/core/jit_type.h"
+#include "NvInferRuntimeBase.h"
 #include "Python.h"
 #include "core/compiler.h"
 #include "core/conversion/conversion.h"
@@ -77,6 +78,10 @@ class pyIInt8Calibrator : public pyCalibratorTrampoline<nvinfer1::IInt8Calibrato
   using Derived = pyCalibratorTrampoline<nvinfer1::IInt8Calibrator>;
   using Derived::Derived;
 
+  nvinfer1::InterfaceInfo getInterfaceInfo() const noexcept override {
+    return nvinfer1::InterfaceInfo{"PYTHON CALIBRATOR", 1, 0};
+  }
+
   nvinfer1::CalibrationAlgoType getAlgorithm() noexcept override {
     try {
       PYBIND11_OVERLOAD_PURE_NAME(
diff --git a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
index 06ae596ed0..8b9d730a72 100644
--- a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
+++ b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
@@ -252,7 +252,7 @@ def run(
         if tactic_sources is not None:
             builder_config.set_tactic_sources(tactic_sources=tactic_sources)
 
-        engine = self.builder.build_engine(self.ctx.net, builder_config)
+        engine = self.builder.build_serialized_network(self.ctx.net, builder_config)
         assert engine
 
         serialized_cache = (
@@ -263,7 +263,7 @@ def run(
         _LOGGER.info(
             f"Build TRT engine elapsed time: {datetime.now() - build_engine_start_time}"
         )
-        _LOGGER.info(f"TRT Engine uses: {engine.device_memory_size} bytes of Memory")
+        _LOGGER.info(f"TRT Engine uses: {engine.nbytes} bytes of Memory")
 
         return TRTInterpreterResult(
             engine, self._input_names, self._output_names, serialized_cache
diff --git a/py/torch_tensorrt/dynamo/conversion/_conversion.py b/py/torch_tensorrt/dynamo/conversion/_conversion.py
index 844cb6789a..f1f4af9236 100644
--- a/py/torch_tensorrt/dynamo/conversion/_conversion.py
+++ b/py/torch_tensorrt/dynamo/conversion/_conversion.py
@@ -87,8 +87,9 @@ def convert_module(
         from torch_tensorrt.dynamo.runtime import TorchTensorRTModule
 
         with io.BytesIO() as engine_bytes:
-            engine_bytes.write(interpreter_result.engine.serialize())
+            engine_bytes.write(interpreter_result.engine)
             engine_str = engine_bytes.getvalue()
+
         return TorchTensorRTModule(
             serialized_engine=engine_str,
             name=name,
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/conv.py b/py/torch_tensorrt/dynamo/conversion/impl/conv.py
index 26e0d59b8f..6c15b4b5fe 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/conv.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/conv.py
@@ -63,7 +63,7 @@ def convNd(
         )
 
     # Process weight terms
-    if ctx.net.has_explicit_precision or isinstance(weight, TRTTensor):
+    if isinstance(weight, TRTTensor):
         weight = get_trt_tensor(ctx, weight, f"{name}_weight")
         # Append new dimension (unsqueeze) if the convolution is 1d
         if is_conv1d:
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/deconv.py b/py/torch_tensorrt/dynamo/conversion/impl/deconv.py
index f66bff7c82..03a209e2a5 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/deconv.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/deconv.py
@@ -63,7 +63,7 @@ def deconvNd(
         )
 
     # Process weight terms
-    if ctx.net.has_explicit_precision or isinstance(weight, TRTTensor):
+    if isinstance(weight, TRTTensor):
         weight = get_trt_tensor(ctx, weight, f"{name}_weight")
         # Append new dimension (unsqueeze) if the deconvolution is 1d
         if is_deconv1d:

From cd866609a18fb0dffe1e798a1831bcf698095de5 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 14 Mar 2024 02:01:07 -0700
Subject: [PATCH 003/122] feat: Add save API for torch-trt compiled models

---
 .github/scripts/install-torch-tensorrt.sh   |  3 +-
 py/torch_tensorrt/_compile.py               | 67 +++++++++++++++++++++
 py/torch_tensorrt/dynamo/_compiler.py       |  9 +--
 py/torch_tensorrt/dynamo/_defaults.py       |  1 -
 py/torch_tensorrt/dynamo/_exporter.py       | 17 +-----
 py/torch_tensorrt/dynamo/_settings.py       |  3 -
 tests/py/dynamo/models/test_export_serde.py | 58 +++++++++---------
 7 files changed, 104 insertions(+), 54 deletions(-)

diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index 2930421d5b..9757fadeb4 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -2,7 +2,8 @@
 set -eou pipefail
 # Source conda so it's available to the script environment
 source ${BUILD_ENV_FILE}
-${CONDA_RUN} ${PIP_INSTALL_TORCH} torchvision pyyaml
+${CONDA_RUN} ${PIP_INSTALL_TORCH} torchvision --extra-index-url https://pypi.python.org/simple
+${CONDA_RUN} python -m pip install pyyaml mpmath==1.3.0
 export TRT_VERSION=$(${CONDA_RUN} python -c "import versions; versions.tensorrt_version()")
 ${CONDA_RUN} python -m pip install /opt/torch-tensorrt-builds/torch_tensorrt*+${CU_VERSION}*.whl tensorrt~=${TRT_VERSION} tensorrt-bindings~=${TRT_VERSION} --extra-index-url=https://pypi.ngc.nvidia.com
 
diff --git a/py/torch_tensorrt/_compile.py b/py/torch_tensorrt/_compile.py
index 9dd816e633..aa1bc53a0a 100644
--- a/py/torch_tensorrt/_compile.py
+++ b/py/torch_tensorrt/_compile.py
@@ -6,6 +6,7 @@
 
 import torch
 import torch.fx
+import torch_tensorrt.dynamo
 import torch_tensorrt.ts
 from torch_tensorrt._enums import dtype
 from torch_tensorrt._Input import Input
@@ -29,6 +30,7 @@
 __all__ = [
     "compile",
     "convert_method_to_trt_engine",
+    "save",
 ]
 
 
@@ -332,3 +334,68 @@ def convert_method_to_trt_engine(
         )
     else:
         raise RuntimeError("Module is an unknown format or the ir requested is unknown")
+
+
+def save(
+    module: Any,
+    file_path: str = "",
+    *,
+    output_format: str = "exported_program",
+    inputs: Optional[Sequence[torch.Tensor]] = None,
+    retrace: bool = False,
+) -> None:
+    """
+    Save the model to disk in the specified output format.
+    Arguments:
+        module : Compiled Torch-TensorRT module (Options include torch.jit.ScriptModule | torch.export.ExportedProgram | torch.fx.GraphModule)
+        inputs (torch.Tensor): Torch input tensors
+    """
+    module_type = _parse_module_type(module)
+    accepted_formats = {"exported_program", "torchscript"}
+    if inputs and not all(isinstance(input, torch.Tensor) for input in inputs):
+        raise ValueError(
+            "Not all inputs provided are torch.tensors. Please provide torch.tensors as inputs"
+        )
+    if output_format not in accepted_formats:
+        raise ValueError(
+            f"Provided output_format {output_format} is not supported. Supported options are exported_program | torchscript"
+        )
+    if not file_path:
+        raise ValueError("File path cannot be empty. Please provide a valid file path")
+
+    if module_type == _ModuleType.nn:
+        raise ValueError(
+            "Input model is of type nn.Module. Saving nn.Module directly is not supported. Supported model types torch.jit.ScriptModule | torch.fx.GraphModule | torch.export.ExportedProgram."
+        )
+    elif module_type == _ModuleType.ts:
+        if output_format == "exported_program":
+            raise ValueError(
+                "Provided model is a torch.jit.ScriptModule but the output_format specified is exported_program. Please verify the output_format"
+            )
+        else:
+            torch.jit.save(module, file_path)
+    elif module_type == _ModuleType.ep:
+        if output_format == "torchscript":
+            raise ValueError(
+                "Provided model is a torch.export.ExportedProgram but the output_format specified is torchscript. Please verify the output_format"
+            )
+        else:
+            torch.export.save(module, file_path)
+    elif module_type == _ModuleType.fx:
+        if not inputs:
+            raise ValueError(
+                "Provided model is a torch.fx.GraphModule however the inputs are empty. Please provide valid torch.tensors as inputs to trace and save the model"
+            )
+        # The module type is torch.fx.GraphModule
+        if output_format == "torchscript":
+            module_ts = torch.jit.trace(module, inputs)
+            torch.jit.save(module_ts, file_path)
+        else:
+            if not retrace:
+                from torch_tensorrt.dynamo._exporter import export
+
+                exp_program = export(module, inputs)
+                torch.export.save(exp_program, file_path)
+            else:
+                exp_program = torch.export.export(module, tuple(inputs), strict=False)
+                torch.export.save(exp_program, file_path)
diff --git a/py/torch_tensorrt/dynamo/_compiler.py b/py/torch_tensorrt/dynamo/_compiler.py
index 6312532f1c..b321eabcb2 100644
--- a/py/torch_tensorrt/dynamo/_compiler.py
+++ b/py/torch_tensorrt/dynamo/_compiler.py
@@ -30,7 +30,6 @@
     MIN_BLOCK_SIZE,
     NUM_AVG_TIMING_ITERS,
     OPTIMIZATION_LEVEL,
-    OUTPUT_FORMAT,
     PASS_THROUGH_BUILD_FAILURES,
     PRECISION,
     REFIT,
@@ -48,7 +47,6 @@
     dryrun_stats_display,
     parse_non_trt_nodes,
 )
-from torch_tensorrt.dynamo._exporter import export
 from torch_tensorrt.dynamo.conversion import (
     CompilationSettings,
     UnsupportedOperatorException,
@@ -102,9 +100,8 @@ def compile(
     enable_experimental_decompositions: bool = ENABLE_EXPERIMENTAL_DECOMPOSITIONS,
     dryrun: bool = DRYRUN,
     hardware_compatible: bool = HARDWARE_COMPATIBLE,
-    output_format: str = OUTPUT_FORMAT,
     **kwargs: Any,
-) -> Union[ExportedProgram, torch.jit.ScriptModule, torch.fx.GraphModule]:
+) -> torch.fx.GraphModule:
     """Compile a TorchScript module for NVIDIA GPUs using TensorRT
 
     Takes a existing TorchScript module and a set of settings to configure the compiler
@@ -246,14 +243,12 @@ def compile(
         "dla_global_dram_size": dla_global_dram_size,
         "dryrun": dryrun,
         "hardware_compatible": hardware_compatible,
-        "output_format": output_format,
     }
 
     settings = CompilationSettings(**compilation_options)
     logger.info("Compilation Settings: %s\n", settings)
     trt_gm = compile_module(gm, inputs, settings)
-    trt_result = export(trt_gm, torch_inputs, output_format)
-    return trt_result
+    return trt_gm
 
 
 def compile_module(
diff --git a/py/torch_tensorrt/dynamo/_defaults.py b/py/torch_tensorrt/dynamo/_defaults.py
index ec038c0dba..3d48ab3def 100644
--- a/py/torch_tensorrt/dynamo/_defaults.py
+++ b/py/torch_tensorrt/dynamo/_defaults.py
@@ -26,7 +26,6 @@
 REQUIRE_FULL_COMPILATION = False
 DRYRUN = False
 HARDWARE_COMPATIBLE = False
-OUTPUT_FORMAT = "exported_program"
 
 
 def default_device() -> Device:
diff --git a/py/torch_tensorrt/dynamo/_exporter.py b/py/torch_tensorrt/dynamo/_exporter.py
index c7e2f37795..bae20ac235 100644
--- a/py/torch_tensorrt/dynamo/_exporter.py
+++ b/py/torch_tensorrt/dynamo/_exporter.py
@@ -18,27 +18,16 @@
 def export(
     gm: torch.fx.GraphModule,
     inputs: Sequence[torch.Tensor],
-    output_format: str,
 ) -> ExportedProgram:
     """Export the result of TensorRT compilation into the desired output format.
 
     Arguments:
         gm (torch.fx.GraphModule): Compiled Torch-TensorRT module, generated by ``torch_tensorrt.dynamo.compile``
         inputs (torch.Tensor): Torch input tensors
-        output_format (str): Output format of the result of TRT compilation. Options include "exported_program" (or) "ep" | "torchscript" (or) "ts" | "graph_module" (or) "fx". Default is "exported_program"
     """
-    if output_format == "torchscript" or output_format == "ts":
-        return torch.jit.trace(gm, inputs)
-    elif output_format == "exported_program" or output_format == "ep":
-        patched_module = transform(gm, inputs)
-        exp_program = create_trt_exp_program(patched_module)
-        return exp_program
-    elif output_format == "graph_module" or output_format == "fx":
-        return gm
-    else:
-        raise ValueError(
-            f"Invalid output format {output_format} specified. Supported options include exported_program (or) ep | torchscript (or) ts | graph_module (or) fx"
-        )
+    patched_module = transform(gm, inputs)
+    exp_program = create_trt_exp_program(patched_module)
+    return exp_program
 
 
 def transform(
diff --git a/py/torch_tensorrt/dynamo/_settings.py b/py/torch_tensorrt/dynamo/_settings.py
index c00b049f45..2420a227d8 100644
--- a/py/torch_tensorrt/dynamo/_settings.py
+++ b/py/torch_tensorrt/dynamo/_settings.py
@@ -19,7 +19,6 @@
     MIN_BLOCK_SIZE,
     NUM_AVG_TIMING_ITERS,
     OPTIMIZATION_LEVEL,
-    OUTPUT_FORMAT,
     PASS_THROUGH_BUILD_FAILURES,
     PRECISION,
     REFIT,
@@ -71,7 +70,6 @@ class CompilationSettings:
             TRT Engines. Prints detailed logs of the graph structure and nature of partitioning. Optionally saves the
             ouptut to a file if a string path is specified
         hardware_compatible (bool): Build the TensorRT engines compatible with GPU architectures other than that of the GPU on which the engine was built (currently works for NVIDIA Ampere and newer)
-        output_format (str): Output format of the result of TRT compilation. Options include "exported_program" (or) "ep" | "torchscript" (or) "ts" | "graph_module" (or) "fx". Default is "exported_program"
     """
 
     precision: torch.dtype = PRECISION
@@ -99,4 +97,3 @@ class CompilationSettings:
     dla_global_dram_size: int = DLA_GLOBAL_DRAM_SIZE
     dryrun: Union[bool, str] = DRYRUN
     hardware_compatible: bool = HARDWARE_COMPATIBLE
-    output_format: str = OUTPUT_FORMAT
diff --git a/tests/py/dynamo/models/test_export_serde.py b/tests/py/dynamo/models/test_export_serde.py
index efa593890e..0905c5e859 100644
--- a/tests/py/dynamo/models/test_export_serde.py
+++ b/tests/py/dynamo/models/test_export_serde.py
@@ -42,18 +42,18 @@ def forward(self, x):
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
     deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
-
+    deser_trt_module = deser_trt_exp_program.module()
     # Check Pyt and TRT exported program outputs
-    cos_sim = cosine_similarity(model(input), trt_exp_program(input)[0])
+    cos_sim = cosine_similarity(model(input), trt_module(input)[0])
     assertions.assertTrue(
         cos_sim > COSINE_THRESHOLD,
         msg=f"test_base_model_full_compile TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
     )
     # Check Pyt and deserialized TRT exported program outputs
-    cos_sim = cosine_similarity(model(input), deser_trt_exp_program(input)[0])
+    cos_sim = cosine_similarity(model(input), deser_trt_module(input)[0])
     assertions.assertTrue(
         cos_sim > COSINE_THRESHOLD,
         msg=f"test_base_model_full_compile TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
@@ -93,12 +93,13 @@ def forward(self, x):
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
     deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
+    deser_trt_module = deser_trt_exp_program.module()
     # Check Pyt and TRT exported program outputs
     outputs_pyt = model(input)
-    outputs_trt = trt_exp_program(input)
+    outputs_trt = trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt[idx])
         assertions.assertTrue(
@@ -107,7 +108,7 @@ def forward(self, x):
         )
 
     # Check Pyt and deserialized TRT exported program outputs
-    outputs_trt_deser = deser_trt_exp_program(input)
+    outputs_trt_deser = deser_trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt_deser[idx])
         assertions.assertTrue(
@@ -149,12 +150,13 @@ def forward(self, x):
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
     deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
+    deser_trt_module = deser_trt_exp_program.module()
     # Check Pyt and TRT exported program outputs
     outputs_pyt = model(input)
-    outputs_trt = trt_exp_program(input)
+    outputs_trt = trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt[idx])
         assertions.assertTrue(
@@ -163,7 +165,7 @@ def forward(self, x):
         )
 
     # Check Pyt and deserialized TRT exported program outputs
-    outputs_trt_deser = deser_trt_exp_program(input)
+    outputs_trt_deser = deser_trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt_deser[idx])
         assertions.assertTrue(
@@ -207,12 +209,12 @@ def forward(self, x):
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
     deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
-
+    deser_trt_module = deser_trt_exp_program.module()
     outputs_pyt = model(input)
-    outputs_trt = trt_exp_program(input)
+    outputs_trt = trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt[idx])
         assertions.assertTrue(
@@ -220,7 +222,7 @@ def forward(self, x):
             msg=f"test_hybrid_relu_fallback TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
         )
 
-    outputs_trt_deser = deser_trt_exp_program(input)
+    outputs_trt_deser = deser_trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt_deser[idx])
         assertions.assertTrue(
@@ -248,19 +250,19 @@ def test_resnet18(ir):
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
     deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
-
+    deser_trt_module = deser_trt_exp_program.module()
     outputs_pyt = model(input)
-    outputs_trt = trt_exp_program(input)
+    outputs_trt = trt_module(input)
     cos_sim = cosine_similarity(outputs_pyt, outputs_trt[0])
     assertions.assertTrue(
         cos_sim > COSINE_THRESHOLD,
         msg=f"test_resnet18 TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
     )
 
-    outputs_trt_deser = deser_trt_exp_program(input)
+    outputs_trt_deser = deser_trt_module(input)
 
     cos_sim = cosine_similarity(outputs_pyt, outputs_trt_deser[0])
     assertions.assertTrue(
@@ -303,12 +305,12 @@ def forward(self, x):
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
     deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
-
+    deser_trt_module = deser_trt_exp_program.module()
     outputs_pyt = model(input)
-    outputs_trt = trt_exp_program(input)
+    outputs_trt = trt_module(input)
 
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt[idx])
@@ -317,7 +319,7 @@ def forward(self, x):
             msg=f"test_hybrid_conv_fallback TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
         )
 
-    outputs_trt_deser = deser_trt_exp_program(input)
+    outputs_trt_deser = deser_trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt_deser[idx])
         assertions.assertTrue(

From 31285e5709f8789a6532820df101599bb50c2c0d Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 4 Mar 2024 17:29:42 -0800
Subject: [PATCH 004/122] feat: Add FP8 support including dtype and converters

---
 py/torch_tensorrt/dynamo/_compiler.py         | 13 ++++--
 py/torch_tensorrt/dynamo/backend/backends.py  |  4 +-
 .../dynamo/conversion/aten_ops_converters.py  | 18 ++++++++
 .../dynamo/conversion/impl/__init__.py        |  1 +
 .../dynamo/conversion/impl/quantize.py        | 43 +++++++++++++++++++
 py/torch_tensorrt/dynamo/lowering/__init__.py |  2 +-
 .../lowering/passes/_aten_lowering_pass.py    | 41 +++++++++++++-----
 .../dynamo/lowering/passes/remove_detach.py   | 32 ++++++++++++++
 8 files changed, 137 insertions(+), 17 deletions(-)
 create mode 100644 py/torch_tensorrt/dynamo/conversion/impl/quantize.py
 create mode 100644 py/torch_tensorrt/dynamo/lowering/passes/remove_detach.py

diff --git a/py/torch_tensorrt/dynamo/_compiler.py b/py/torch_tensorrt/dynamo/_compiler.py
index 6312532f1c..1a635b5af5 100644
--- a/py/torch_tensorrt/dynamo/_compiler.py
+++ b/py/torch_tensorrt/dynamo/_compiler.py
@@ -59,7 +59,11 @@
 from torch_tensorrt.dynamo.conversion._ConverterRegistry import (
     DYNAMO_CONVERTERS as CONVERTERS,
 )
-from torch_tensorrt.dynamo.lowering import apply_lowering_passes, get_decompositions
+from torch_tensorrt.dynamo.lowering import (
+    get_decompositions,
+    post_lowering,
+    pre_export_lowering,
+)
 from torch_tensorrt.dynamo.utils import (
     get_torch_inputs,
     parse_complex_tensor_structs,
@@ -181,12 +185,15 @@ def compile(
 
     # Prepare torch_trt inputs
     inputs = prepare_inputs(inputs)
+    torch_inputs = get_torch_inputs(inputs, device)
     device = to_torch_tensorrt_device(device)
 
     if not isinstance(exported_program, ExportedProgram):
         raise AssertionError(
             f"Input graph should be an ExportedProgram but got type {type(exported_program)}"
         )
+
+    exported_program = pre_export_lowering(exported_program, torch_inputs)
     exported_program = exported_program.run_decompositions(
         get_decompositions(enable_experimental_decompositions)
     )
@@ -194,10 +201,8 @@ def compile(
     logger.debug("Input graph: " + str(gm.graph))
 
     # Apply lowering on the graph module
-    torch_inputs = get_torch_inputs(inputs, device)
-    gm = apply_lowering_passes(gm, torch_inputs)
+    gm = post_lowering(gm, torch_inputs)
     logger.debug("Lowered Input graph: " + str(gm.graph))
-
     enabled_precisions = set(enabled_precisions)
 
     if (
diff --git a/py/torch_tensorrt/dynamo/backend/backends.py b/py/torch_tensorrt/dynamo/backend/backends.py
index 1fa2806181..961e1c9344 100644
--- a/py/torch_tensorrt/dynamo/backend/backends.py
+++ b/py/torch_tensorrt/dynamo/backend/backends.py
@@ -11,8 +11,8 @@
 from torch_tensorrt.dynamo import CompilationSettings
 from torch_tensorrt.dynamo._compiler import compile_module
 from torch_tensorrt.dynamo.lowering import (
-    apply_lowering_passes,
     get_decompositions,
+    post_lowering,
     repair_input_aliasing,
 )
 from torch_tensorrt.dynamo.utils import (
@@ -87,7 +87,7 @@ def _pretraced_backend(
 
             logger.debug("Post-AOT Autograd graph:\n" + str(gm.graph))
 
-            gm = apply_lowering_passes(gm, sample_inputs)
+            gm = post_lowering(gm, sample_inputs)
 
             torchtrt_inputs = prepare_inputs(
                 sample_inputs, disable_memory_format_check=True
diff --git a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
index 45949a1c8d..44ccf0546b 100644
--- a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
+++ b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
@@ -573,6 +573,24 @@ def aten_ops_neg(
     )
 
 
+@dynamo_tensorrt_converter(torch.ops.ptq.scaled_e4m3.default)
+def aten_ops_quantize_fp8(
+    ctx: ConversionContext,
+    target: Target,
+    args: Tuple[Argument, ...],
+    kwargs: Dict[str, Argument],
+    name: str,
+) -> Union[TRTTensor, Sequence[TRTTensor]]:
+    return impl.quantize.quantize_fp8(
+        ctx,
+        target,
+        SourceIR.ATEN,
+        name,
+        args[0],
+        args[1],
+    )
+
+
 @dynamo_tensorrt_converter(torch.ops.aten.squeeze.dim)
 @dynamo_tensorrt_converter(torch.ops.aten.squeeze.dims)
 def aten_ops_squeeze(
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/__init__.py b/py/torch_tensorrt/dynamo/conversion/impl/__init__.py
index ca71cb0b0c..a18155d6be 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/__init__.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/__init__.py
@@ -18,6 +18,7 @@
     pad,
     permutation,
     pool,
+    quantize,
     reduce,
     select,
     shape,
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/quantize.py b/py/torch_tensorrt/dynamo/conversion/impl/quantize.py
new file mode 100644
index 0000000000..f5c3a4cd98
--- /dev/null
+++ b/py/torch_tensorrt/dynamo/conversion/impl/quantize.py
@@ -0,0 +1,43 @@
+from typing import Optional
+
+import numpy as np
+import tensorrt as trt
+from torch.fx.node import Target
+from torch_tensorrt.dynamo._SourceIR import SourceIR
+from torch_tensorrt.dynamo.conversion._ConversionContext import ConversionContext
+from torch_tensorrt.dynamo.conversion.converter_utils import get_trt_tensor
+from torch_tensorrt.fx.converters.converter_utils import set_layer_name
+from torch_tensorrt.fx.types import TRTTensor
+
+
+def quantize_fp8(
+    ctx: ConversionContext,
+    target: Target,
+    source_ir: Optional[SourceIR],
+    name: str,
+    input_tensor: TRTTensor,
+    scale: np.ndarray,
+) -> TRTTensor:
+    """
+    Adds quantize and dequantize ops (QDQ) which quantize to INT8 or FP8 based
+    on the output_type set and dequantizes them back.
+    """
+    if (isinstance(input_tensor, TRTTensor)) and not (
+        input_tensor.dtype != trt.float32 or input_tensor.dtype != trt.float16
+    ):
+        raise ValueError(
+            f"quantize_fp8 converter received an input of {input_tensor.dtype} type. Supported types: float32 | float16"
+        )
+
+    if isinstance(scale, np.ndarray):
+        scale = get_trt_tensor(ctx, scale, name + "_scale")
+    # Add Q node
+    quantize_layer = ctx.net.add_quantize(input_tensor, scale)
+    set_layer_name(quantize_layer, target, name + "_quantize", source_ir)
+    q_output = quantize_layer.get_output(0)
+    # Add DQ node
+    dequantize_layer = ctx.net.add_dequantize(q_output, scale)
+    set_layer_name(dequantize_layer, target, name + "_dequantize", source_ir)
+    dq_output = dequantize_layer.get_output(0)
+
+    return dq_output
diff --git a/py/torch_tensorrt/dynamo/lowering/__init__.py b/py/torch_tensorrt/dynamo/lowering/__init__.py
index 7c4e9fdd2d..67a73354ad 100644
--- a/py/torch_tensorrt/dynamo/lowering/__init__.py
+++ b/py/torch_tensorrt/dynamo/lowering/__init__.py
@@ -5,4 +5,4 @@
 from ._decompositions import get_decompositions  # noqa: F401
 from ._fusers import *  # noqa: F401
 from ._repair_input_aliasing import repair_input_aliasing
-from .passes import apply_lowering_passes
+from .passes import post_lowering, pre_export_lowering
diff --git a/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py b/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py
index 489805cb43..05a171e264 100644
--- a/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py
+++ b/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py
@@ -8,12 +8,13 @@
 from .lower_linear import lower_linear
 from .lower_scaled_dot_product_attention import lower_scaled_dot_product_attention
 from .pass_manager import DynamoPassManager
+from .remove_detach import remove_detach
 from .remove_input_alias_fixing_clones import remove_input_alias_fixing_clones
 from .repair_input_as_output import repair_input_as_output
 from .replace_max_pool_with_indices import replace_max_pool_with_indices
 from .view_to_reshape import view_to_reshape
 
-ATEN_LOWERING_PASSES = DynamoPassManager.build_from_passlist(
+ATEN_POST_LOWERING_PASSES = DynamoPassManager.build_from_passlist(
     [
         remove_input_alias_fixing_clones,
         constant_fold,
@@ -26,6 +27,12 @@
     ]
 )
 
+ATEN_PRE_LOWERING_PASSES = DynamoPassManager.build_from_passlist(
+    [
+        remove_detach,
+    ]
+)
+
 logger = logging.getLogger(__name__)
 
 
@@ -48,9 +55,9 @@ def _aten_lowering_pass(
     def add_lowering_pass(
         lowering_pass: LoweringPassSignature,
     ) -> LoweringPassSignature:
-        ATEN_LOWERING_PASSES.add_pass_with_index(lowering_pass, index)
+        ATEN_POST_LOWERING_PASSES.add_pass_with_index(lowering_pass, index)
         logger.debug(
-            f"Added lowering pass {lowering_pass} to list at index {index}, current passlist: {ATEN_LOWERING_PASSES}"
+            f"Added lowering pass {lowering_pass} to list at index {index}, current passlist: {ATEN_POST_LOWERING_PASSES}"
         )
         return lowering_pass
 
@@ -72,23 +79,37 @@ def add_lowering_pass(
 
 def _remove_lowering_pass(*, index: int) -> None:
     """Removes a lowering pass at a specific index from the registry"""
-    ATEN_LOWERING_PASSES.remove_pass_with_index(index)
+    ATEN_POST_LOWERING_PASSES.remove_pass_with_index(index)
     logger.debug(
-        f"Removed lowering pass at index {index}, current passlist: {ATEN_LOWERING_PASSES}"
+        f"Removed lowering pass at index {index}, current passlist: {ATEN_POST_LOWERING_PASSES}"
     )
     return
 
 
-def apply_lowering_passes(
+def post_lowering(
     gm: torch.fx.GraphModule, sample_inputs: Sequence[torch.Tensor]
 ) -> torch.fx.GraphModule:
-    """Applies the lowering passes to a graph module, returns the modified GraphModule"""
+    """Applies the lowering passes to a graph module after torch.export/ torch.compile and their decompositions, returns the modified GraphModule"""
+    logging.debug(
+        f"Invoking DynamoPassManager and applying lowering passes: {ATEN_POST_LOWERING_PASSES}"
+    )
+    return ATEN_POST_LOWERING_PASSES(gm, sample_inputs)
+
+
+def pre_export_lowering(
+    ep: torch.export.ExportedProgram, sample_inputs: Sequence[torch.Tensor]
+) -> torch.fx.GraphModule:
+    """Applies the lowering passes to a graph module after torch.export/ torch.compile and their decompositions, returns the modified GraphModule"""
     logging.debug(
-        f"Invoking DynamoPassManager and applying lowering passes: {ATEN_LOWERING_PASSES}"
+        f"Invoking DynamoPassManager and applying lowering passes: {ATEN_PRE_LOWERING_PASSES}"
     )
-    return ATEN_LOWERING_PASSES(gm, sample_inputs)
+    gm = ep.module()
+    gm = ATEN_PRE_LOWERING_PASSES(gm, sample_inputs)
+    # TODO: Check if re-exporting changes the metadata
+    transformed_ep = torch.export.export(gm, tuple(sample_inputs), strict=False)
+    return transformed_ep
 
 
 def dump_lowering_passes() -> str:
     """Returns a string containing the lowering passes"""
-    return str(ATEN_LOWERING_PASSES)
+    return str(ATEN_POST_LOWERING_PASSES)
diff --git a/py/torch_tensorrt/dynamo/lowering/passes/remove_detach.py b/py/torch_tensorrt/dynamo/lowering/passes/remove_detach.py
new file mode 100644
index 0000000000..5c47a8e288
--- /dev/null
+++ b/py/torch_tensorrt/dynamo/lowering/passes/remove_detach.py
@@ -0,0 +1,32 @@
+import logging
+from typing import Sequence
+
+import torch
+from torch_tensorrt.dynamo.lowering.passes.pass_utils import (
+    clean_up_graph_after_modifications,
+)
+
+logger = logging.getLogger(__name__)
+
+
+def remove_detach(
+    gm: torch.fx.GraphModule, sample_inputs: Sequence[torch.Tensor]
+) -> torch.fx.GraphModule:
+    """Remove detach ops in the graph"""
+
+    modified_graph = False
+    count = 0
+    for node in gm.graph.nodes:
+        # If the node is a detach node
+        if node.target == torch.ops.aten.detach.default:
+            # Detach node has only one input
+            node_input = node.all_input_nodes[0]
+            node.replace_all_uses_with(node_input)
+            gm.graph.erase_node(node)
+            count += 1
+
+    if modified_graph:
+        gm = clean_up_graph_after_modifications(gm)
+        logger.debug(f"Removed {count} detach nodes:\n{gm.graph}")
+
+    return gm

From 7c9c6462c3585932c15d965b58a09b215427c207 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 15 Mar 2024 14:30:10 -0700
Subject: [PATCH 005/122] chore: minor fixes

---
 py/torch_tensorrt/dynamo/_compiler.py         |  4 +-
 .../dynamo/conversion/_TRTInterpreter.py      |  5 ++-
 .../dynamo/conversion/aten_ops_converters.py  | 40 +++++++++++--------
 .../dynamo/conversion/impl/quantize.py        |  3 ++
 4 files changed, 34 insertions(+), 18 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/_compiler.py b/py/torch_tensorrt/dynamo/_compiler.py
index 1a635b5af5..ed1972ce11 100644
--- a/py/torch_tensorrt/dynamo/_compiler.py
+++ b/py/torch_tensorrt/dynamo/_compiler.py
@@ -205,7 +205,9 @@ def compile(
     logger.debug("Lowered Input graph: " + str(gm.graph))
     enabled_precisions = set(enabled_precisions)
 
-    if (
+    if torch.float8_e4m3fn in enabled_precisions:
+        precision = torch.float8_e4m3fn
+    elif (
         torch.float16 in enabled_precisions
         or torch_tensorrt.dtype.half in enabled_precisions
     ):
diff --git a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
index 8b9d730a72..21b181c0c2 100644
--- a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
+++ b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
@@ -172,7 +172,7 @@ def run(
 
         if version.parse(trt.__version__) >= version.parse("8.2"):
             builder_config.profiling_verbosity = (
-                trt.ProfilingVerbosity.VERBOSE
+                trt.ProfilingVerbosity.DETAILED
                 if self.compilation_settings.debug
                 else trt.ProfilingVerbosity.LAYER_NAMES_ONLY
             )
@@ -228,6 +228,9 @@ def run(
         if precision == torch.int8:
             builder_config.set_flag(trt.BuilderFlag.INT8)
 
+        if precision == torch.float8_e4m3fn:
+            builder_config.set_flag(trt.BuilderFlag.FP8)
+
         if self.compilation_settings.sparse_weights:
             builder_config.set_flag(trt.BuilderFlag.SPARSE_WEIGHTS)
 
diff --git a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
index 44ccf0546b..46b40bee06 100644
--- a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
+++ b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
@@ -573,22 +573,30 @@ def aten_ops_neg(
     )
 
 
-@dynamo_tensorrt_converter(torch.ops.ptq.scaled_e4m3.default)
-def aten_ops_quantize_fp8(
-    ctx: ConversionContext,
-    target: Target,
-    args: Tuple[Argument, ...],
-    kwargs: Dict[str, Argument],
-    name: str,
-) -> Union[TRTTensor, Sequence[TRTTensor]]:
-    return impl.quantize.quantize_fp8(
-        ctx,
-        target,
-        SourceIR.ATEN,
-        name,
-        args[0],
-        args[1],
-    )
+try:
+    assert torch.ops.trt.quantize_fp8.default
+except Exception as e:
+    _LOGGER.warn(
+        f"Unable to import quantize_fp8 op.: {e}. Please install nvidia-ammo library in order to register torch.ops.trt.quantize_fp8 op"
+    )
+else:
+
+    @dynamo_tensorrt_converter(torch.ops.trt.quantize_fp8.default)
+    def aten_ops_quantize_fp8(
+        ctx: ConversionContext,
+        target: Target,
+        args: Tuple[Argument, ...],
+        kwargs: Dict[str, Argument],
+        name: str,
+    ) -> Union[TRTTensor, Sequence[TRTTensor]]:
+        return impl.quantize.quantize_fp8(
+            ctx,
+            target,
+            SourceIR.ATEN,
+            name,
+            args[0],
+            args[1],
+        )
 
 
 @dynamo_tensorrt_converter(torch.ops.aten.squeeze.dim)
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/quantize.py b/py/torch_tensorrt/dynamo/conversion/impl/quantize.py
index f5c3a4cd98..478e8a5771 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/quantize.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/quantize.py
@@ -33,11 +33,14 @@ def quantize_fp8(
         scale = get_trt_tensor(ctx, scale, name + "_scale")
     # Add Q node
     quantize_layer = ctx.net.add_quantize(input_tensor, scale)
+    quantize_layer.set_output_type(0, trt.DataType.FP8)
     set_layer_name(quantize_layer, target, name + "_quantize", source_ir)
     q_output = quantize_layer.get_output(0)
     # Add DQ node
     dequantize_layer = ctx.net.add_dequantize(q_output, scale)
     set_layer_name(dequantize_layer, target, name + "_dequantize", source_ir)
+    # Set DQ layer precision to FP8
+    dequantize_layer.precision = trt.DataType.FP8
     dq_output = dequantize_layer.get_output(0)
 
     return dq_output

From eab0dba2955a87550fe12e7b67ae092597b8c453 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 18 Mar 2024 12:43:45 -0700
Subject: [PATCH 006/122] chore: Fix save failures

---
 core/runtime/TRTEngine.cpp                  |   2 +-
 py/torch_tensorrt/_compile.py               |   9 +-
 py/torch_tensorrt/dynamo/_exporter.py       | 135 +++++++++++++-------
 tests/py/dynamo/models/test_export_serde.py |   2 +-
 4 files changed, 100 insertions(+), 48 deletions(-)

diff --git a/core/runtime/TRTEngine.cpp b/core/runtime/TRTEngine.cpp
index 92e5d7a8ff..7a046f6d94 100644
--- a/core/runtime/TRTEngine.cpp
+++ b/core/runtime/TRTEngine.cpp
@@ -241,7 +241,7 @@ std::string TRTEngine::to_str() const {
               exec_ctx->getEngine().getTensorDataType(out_binding_names[o].c_str()))
        << std::endl;
   }
-  ss << "  }" << std::endl;
+  ss << "  ]" << std::endl;
   ss << "  Device: " << device_info << std::endl;
   ss << "  Hardware Compatibility: " << (hardware_compatible ? "Enabled" : "Disabled") << std::endl;
   // clang-format on
diff --git a/py/torch_tensorrt/_compile.py b/py/torch_tensorrt/_compile.py
index aa1bc53a0a..443dec8869 100644
--- a/py/torch_tensorrt/_compile.py
+++ b/py/torch_tensorrt/_compile.py
@@ -397,5 +397,10 @@ def save(
                 exp_program = export(module, inputs)
                 torch.export.save(exp_program, file_path)
             else:
-                exp_program = torch.export.export(module, tuple(inputs), strict=False)
-                torch.export.save(exp_program, file_path)
+                from torch._higher_order_ops.torchbind import enable_torchbind_tracing
+
+                with enable_torchbind_tracing():
+                    exp_program = torch.export.export(
+                        module, tuple(inputs), strict=False
+                    )
+                    torch.export.save(exp_program, file_path)
diff --git a/py/torch_tensorrt/dynamo/_exporter.py b/py/torch_tensorrt/dynamo/_exporter.py
index bae20ac235..cf06bc4531 100644
--- a/py/torch_tensorrt/dynamo/_exporter.py
+++ b/py/torch_tensorrt/dynamo/_exporter.py
@@ -1,3 +1,4 @@
+import copy
 import operator
 from typing import Any, Dict, Sequence, Tuple, cast
 
@@ -6,8 +7,11 @@
 from torch._subclasses.fake_tensor import FakeTensor
 from torch.export import ExportedProgram, ExportGraphSignature
 from torch.export.exported_program import (
+    CustomObjArgument,
     InputKind,
     InputSpec,
+    ModuleCallEntry,
+    ModuleCallSignature,
     OutputKind,
     OutputSpec,
     TensorArgument,
@@ -44,24 +48,27 @@ def transform(
 
     Returns an inlined torch.fx.GraphModule
     """
+    gm_export = copy.deepcopy(gm)
     # Run shape analysis
-    _, outputs_map = partitioning.run_shape_analysis(gm, inputs)
+    _, outputs_map = partitioning.run_shape_analysis(gm_export, inputs)
 
     # Inline TensorRT submodules
-    inline_trt_modules(gm, outputs_map)
+    inline_trt_modules(gm_export, outputs_map)
 
     # Inline pytorch submodules
-    inline_torch_modules(gm)
+    inline_torch_modules(gm_export)
 
     # Clean the graph
-    gm.delete_all_unused_submodules()
-    gm.graph.eliminate_dead_code()
-    gm.graph.lint()
+    gm_export.delete_all_unused_submodules()
+    gm_export.graph.eliminate_dead_code()
+    gm_export.graph.lint()
 
-    return gm
+    return gm_export
 
 
-def lift(gm: torch.fx.GraphModule, graph_signature: Any) -> torch.fx.GraphModule:
+def lift(
+    gm: torch.fx.GraphModule, graph_signature: Any
+) -> Tuple[torch.fx.GraphModule, ExportGraphSignature, Dict[str, Any], Dict[str, Any]]:
     """
     Given an unlifted fx.GraphModule, lift all parameters, buffers into placeholders.
     Arguments:
@@ -75,6 +82,7 @@ def lift(gm: torch.fx.GraphModule, graph_signature: Any) -> torch.fx.GraphModule
     # exp_program.state_dict contains parameters and buffers whereas a graph_module's state_dict
     # has all parameters registered as torch.tensors.
     state_dict = gm.state_dict()
+    constants = {}
 
     fake_mode = detect_fake_mode(
         tuple(node.meta["val"] for node in gm.graph.nodes if node.op == "placeholder")
@@ -89,52 +97,68 @@ def lift(gm: torch.fx.GraphModule, graph_signature: Any) -> torch.fx.GraphModule
             break
 
     # At first the user_inputs are only present in the graph_signature.input_specs and hence non_user_input_idx=0
-    # The input_specs should be of the form [params, buffers, constant_tensors, user_inputs]
+    # The input_specs should be of the form [params, buffers, constant_tensors, custom_obj, user_inputs]
     non_user_input_idx = 0
     for node in gm.graph.nodes:
         if node.op == "get_attr":
-            if node.target not in state_dict:
-                raise ValueError(
-                    f"The get_attr node : {node.name} with target: {node.target} value could not be found in state_dict. Please check the input exported_program's graphmodule parameters."
-                )
 
-            constant_tensor = state_dict[node.target]
-            input_kind = InputKind.CONSTANT_TENSOR
+            lift_val = None
+            input_kind = None
 
-            # state_dict has these parameters/buffers as torch.Tensors. We override them as torch.nn.Parameter/torch.Tensors respectively.
-            for name, _ in gm.named_parameters():
-                if node.target == name:
-                    input_kind = InputKind.PARAMETER
-                    state_dict[name] = torch.nn.Parameter(state_dict[name])
-                    break
-            for name, _ in gm.named_buffers():
-                if node.target == name:
-                    input_kind = InputKind.BUFFER
-                    break
+            if node.target not in state_dict:
+                constants[node.target] = getattr(gm, node.target)
+                input_kind = InputKind.CUSTOM_OBJ
+                lift_val = constants[node.target]
+            else:
+                lift_val = state_dict[node.target]
+
+                input_kind = InputKind.CONSTANT_TENSOR
+
+                # state_dict has these parameters/buffers as torch.Tensors. We override them as torch.nn.Parameter/torch.Tensors respectively.
+                for name, _ in gm.named_parameters():
+                    if node.target == name:
+                        input_kind = InputKind.PARAMETER
+                        state_dict[name] = torch.nn.Parameter(state_dict[name])
+                        break
+                for name, _ in gm.named_buffers():
+                    if node.target == name:
+                        input_kind = InputKind.BUFFER
+                        break
+
+            assert lift_val is not None and input_kind is not None
 
             # Replace get_attr nodes with placeholder nodes and copy metadata.
             with gm.graph.inserting_before(first_user_input):
-                const_placeholder_node = gm.graph.placeholder(node.target)
+                const_placeholder_node = gm.graph.placeholder(
+                    node.target.replace(".", "_")
+                )
                 # Copy the node meta into this new placeholder node
                 const_placeholder_node.meta = node.meta
-                const_placeholder_node.meta["val"] = cast(
-                    FakeTensor,
-                    torch.empty_strided(
-                        tuple(constant_tensor.shape),
-                        tuple([1] * len(constant_tensor.shape)),
-                    ),
-                )
+
+                if isinstance(lift_val, torch.Tensor):
+                    const_placeholder_node.meta["val"] = cast(
+                        FakeTensor,
+                        torch.empty_strided(
+                            tuple(lift_val.shape),
+                            tuple([1] * len(lift_val.shape)),
+                        ),
+                    )
 
                 node.replace_all_uses_with(const_placeholder_node)
                 gm.graph.erase_node(node)
 
                 # Add these parameters/buffers/constants to the existing graph signature
                 # before user inputs. These specs are looked up in the state_dict during ExportedProgram creation.
+                input_spec_arg = TensorArgument(name=const_placeholder_node.name)
+                if input_kind == InputKind.CUSTOM_OBJ:
+                    input_spec_arg = CustomObjArgument(
+                        name=const_placeholder_node.name, class_fqn=""
+                    )
                 graph_signature.input_specs.insert(
                     non_user_input_idx,
                     InputSpec(
                         kind=input_kind,
-                        arg=TensorArgument(name=const_placeholder_node.name),
+                        arg=input_spec_arg,
                         target=node.target,
                     ),
                 )
@@ -143,7 +167,7 @@ def lift(gm: torch.fx.GraphModule, graph_signature: Any) -> torch.fx.GraphModule
     gm.graph.eliminate_dead_code()
     gm.graph.lint()
 
-    return gm, graph_signature, state_dict
+    return gm, graph_signature, state_dict, constants
 
 
 def get_duplicate_nodes(
@@ -281,18 +305,30 @@ def create_trt_exp_program(
         input_specs=input_specs, output_specs=output_specs
     )
 
+    module_call_graph = [
+        ModuleCallEntry(
+            "",
+            ModuleCallSignature(
+                inputs=[],
+                outputs=[],
+                in_spec=gm.graph._codegen.pytree_info.in_spec,
+                out_spec=gm.graph._codegen.pytree_info.out_spec,
+            ),
+        )
+    ]
+
     # Lift parameters/buffers/constants in the graph
     # torch.export serialization expects them to be lifted
-    gm, trt_graph_signature, state_dict = lift(gm, trt_graph_signature)
+    gm, trt_graph_signature, state_dict, constants = lift(gm, trt_graph_signature)
 
     trt_exp_program = ExportedProgram(
-        gm,
-        gm.graph,
-        trt_graph_signature,
-        state_dict,
-        {},
-        [],
-        [],
+        root=gm,
+        graph=gm.graph,
+        graph_signature=trt_graph_signature,
+        state_dict=state_dict,
+        range_constraints={},
+        module_call_graph=module_call_graph,
+        constants=constants,
     )
 
     return trt_exp_program
@@ -319,9 +355,13 @@ def inline_trt_modules(
         num_outputs = len(outputs_map[trt_module_node.name])
         # Insert a call_function node to perform inference on TRT engine
         with gm.graph.inserting_before(trt_module_node):
+            engine_name = f"{name}_engine"
+            setattr(gm, engine_name, trt_module.engine)
+            engine_node = gm.graph.get_attr(engine_name)
+
             trt_node = gm.graph.call_function(
                 torch.ops.tensorrt.execute_engine.default,
-                (trt_module_node.args, trt_module.engine),
+                (trt_module_node.args, engine_node),
             )
             trt_node.meta["val"] = []
             assert num_outputs > 0
@@ -337,6 +377,13 @@ def inline_trt_modules(
                     )
                 )
 
+            # meta["val"] should be a lighter version of a tensor. For eg: it should be a FakeTensor (with output shape and dtype properties)
+            # Lighter version of a custom_obj is not defined clearly. meta["val"] does not have any type expectations but
+            # for custom object nodes, it should be CustomObjArgument
+            engine_node.meta["val"] = CustomObjArgument(
+                name=engine_node.name, class_fqn=""
+            )
+
         if num_outputs == 1:
             # Insert getitem nodes as outputs (for export serialization to work)
             with gm.graph.inserting_after(trt_node):
diff --git a/tests/py/dynamo/models/test_export_serde.py b/tests/py/dynamo/models/test_export_serde.py
index 0905c5e859..40fa01c2c9 100644
--- a/tests/py/dynamo/models/test_export_serde.py
+++ b/tests/py/dynamo/models/test_export_serde.py
@@ -146,7 +146,6 @@ def forward(self, x):
             )
         ],
         "ir": ir,
-        "debug": True,
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
@@ -306,6 +305,7 @@ def forward(self, x):
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
     trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+
     torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
     deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
     deser_trt_module = deser_trt_exp_program.module()

From b191d62bafac9740657cb9dc67ccafb213d4914c Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 18 Mar 2024 16:29:04 -0700
Subject: [PATCH 007/122] chore: update to 2.3 rc build

---
 py/requirements.txt | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/py/requirements.txt b/py/requirements.txt
index cd52d32436..419c325653 100644
--- a/py/requirements.txt
+++ b/py/requirements.txt
@@ -1,9 +1,9 @@
 numpy
 packaging
 pybind11==2.6.2
---extra-index-url https://download.pytorch.org/whl/nightly/cu121
-torch>=2.3.0.dev,<2.4.0
-torchvision>=0.18.0.dev,<0.19.0
+--index-url https://download.pytorch.org/whl/test/cu121
+torch>=2.3.0,<2.4.0
+torchvision>=0.18.0,<0.19.0
 --extra-index-url https://pypi.ngc.nvidia.com
 tensorrt==8.6.1
 pyyaml

From 8674a3c437d767c6e2b09db3a574af9a99c318d3 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 19 Mar 2024 16:18:17 -0700
Subject: [PATCH 008/122] chore: minor fixes

---
 py/torch_tensorrt/dynamo/_exporter.py         |  1 +
 .../lowering/test_aten_lowering_passes.py     | 12 ++++++++----
 tests/py/dynamo/models/test_models_export.py  | 19 ++++++++++---------
 tests/py/dynamo/testing_utilities.py          |  1 +
 4 files changed, 20 insertions(+), 13 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/_exporter.py b/py/torch_tensorrt/dynamo/_exporter.py
index cf06bc4531..d4a9fd3584 100644
--- a/py/torch_tensorrt/dynamo/_exporter.py
+++ b/py/torch_tensorrt/dynamo/_exporter.py
@@ -129,6 +129,7 @@ def lift(
 
             # Replace get_attr nodes with placeholder nodes and copy metadata.
             with gm.graph.inserting_before(first_user_input):
+                # Ensure name doesn't contain period as it is used for submodules
                 const_placeholder_node = gm.graph.placeholder(
                     node.target.replace(".", "_")
                 )
diff --git a/tests/py/dynamo/lowering/test_aten_lowering_passes.py b/tests/py/dynamo/lowering/test_aten_lowering_passes.py
index bc75a8aa3d..3afc5e5923 100644
--- a/tests/py/dynamo/lowering/test_aten_lowering_passes.py
+++ b/tests/py/dynamo/lowering/test_aten_lowering_passes.py
@@ -1,9 +1,12 @@
 import torch
-from torch.testing._internal.common_utils import TestCase, run_tests
-
 import torch_tensorrt
+from torch.testing._internal.common_utils import TestCase, run_tests
 
-from ..testing_utilities import DECIMALS_OF_AGREEMENT, lower_graph_testing
+from ..testing_utilities import (
+    DECIMALS_OF_AGREEMENT,
+    DECIMALS_OF_AGREEMENT_3,
+    lower_graph_testing,
+)
 
 
 class TestInputAsOutput(TestCase):
@@ -444,10 +447,11 @@ def forward(self, input, weight, bias):
         max_diff = float(
             torch.max(torch.abs(optimized_model_results - torch_model_results))
         )
+
         self.assertAlmostEqual(
             max_diff,
             0,
-            DECIMALS_OF_AGREEMENT,
+            DECIMALS_OF_AGREEMENT_3,
             msg=f"Linear TRT outputs don't match with the original model.",
         )
         torch._dynamo.reset()
diff --git a/tests/py/dynamo/models/test_models_export.py b/tests/py/dynamo/models/test_models_export.py
index fd7b40592a..bc8bf12c95 100644
--- a/tests/py/dynamo/models/test_models_export.py
+++ b/tests/py/dynamo/models/test_models_export.py
@@ -159,11 +159,11 @@ def test_bert_base_uncased(ir):
     model = BertModel.from_pretrained("bert-base-uncased").cuda().eval()
     input = torch.randint(0, 1, (1, 14), dtype=torch.int32).to("cuda")
     input2 = torch.randint(0, 1, (1, 14), dtype=torch.int32).to("cuda")
-    model = (
-        transformers_trace(model, input_names=["input_ids", "attention_mask"])
-        .eval()
-        .cuda()
-    )
+    # model = (
+    #     transformers_trace(model, input_names=["input_ids", "attention_mask"])
+    #     .eval()
+    #     .cuda()
+    # )
 
     compile_spec = {
         "inputs": [
@@ -182,8 +182,8 @@ def test_bert_base_uncased(ir):
         "enabled_precisions": {torch.float},
         "truncate_long_and_double": True,
         "ir": ir,
-        "min_block_size": 10,
-        "torch_executed_ops": {"torch.ops.aten.gelu.default"},
+        "min_block_size": 15,
+        "debug": True,
     }
     trt_mod = torchtrt.compile(model, **compile_spec)
     model_outputs = model(input, input2)
@@ -192,8 +192,9 @@ def test_bert_base_uncased(ir):
         len(model_outputs) == len(trt_model_outputs),
         msg=f"Number of outputs for BERT model compilation is different with Pytorch {len(model_outputs)} and TensorRT {len(trt_model_outputs)}. Please check the compilation.",
     )
-    for index, key in enumerate(model_outputs):
-        out, trt_out = model_outputs[key], trt_model_outputs[index]
+
+    for key, _ in model_outputs.items():
+        out, trt_out = model_outputs[key], trt_model_outputs[key]
         cos_sim = cosine_similarity(out, trt_out)
         assertions.assertTrue(
             cos_sim > COSINE_THRESHOLD,
diff --git a/tests/py/dynamo/testing_utilities.py b/tests/py/dynamo/testing_utilities.py
index 742b9fc1a3..c815d2fde4 100644
--- a/tests/py/dynamo/testing_utilities.py
+++ b/tests/py/dynamo/testing_utilities.py
@@ -14,6 +14,7 @@
 )
 
 DECIMALS_OF_AGREEMENT = 4
+DECIMALS_OF_AGREEMENT_3 = 3
 
 
 def fx_dynamo_testing_backend(

From f4e8fe9bc3f114dd8da3760dca510f78a8f58a0d Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 19 Mar 2024 17:04:38 -0700
Subject: [PATCH 009/122] chore: remove duplicate bert test case

---
 tests/py/dynamo/models/test_models_export.py | 53 --------------------
 1 file changed, 53 deletions(-)

diff --git a/tests/py/dynamo/models/test_models_export.py b/tests/py/dynamo/models/test_models_export.py
index bc8bf12c95..4d0f4e2e7f 100644
--- a/tests/py/dynamo/models/test_models_export.py
+++ b/tests/py/dynamo/models/test_models_export.py
@@ -105,55 +105,6 @@ def test_efficientnet_b0(ir):
     torch._dynamo.reset()
 
 
-@pytest.mark.unit
-def test_bert_base_uncased(ir):
-    model = BertModel.from_pretrained("bert-base-uncased").cuda().eval()
-    input = torch.randint(0, 1, (1, 14), dtype=torch.int32).to("cuda")
-    input2 = torch.randint(0, 1, (1, 14), dtype=torch.int32).to("cuda")
-    model = (
-        transformers_trace(model, input_names=["input_ids", "attention_mask"])
-        .eval()
-        .cuda()
-    )
-
-    compile_spec = {
-        "inputs": [
-            torchtrt.Input(
-                input.shape,
-                dtype=input.dtype,
-                format=torch.contiguous_format,
-            ),
-            torchtrt.Input(
-                input.shape,
-                dtype=input.dtype,
-                format=torch.contiguous_format,
-            ),
-        ],
-        "device": torchtrt.Device("cuda:0"),
-        "enabled_precisions": {torch.float},
-        "truncate_long_and_double": True,
-        "ir": ir,
-        "min_block_size": 10,
-    }
-    trt_mod = torchtrt.compile(model, **compile_spec)
-    model_outputs = model(input, input2)
-    trt_model_outputs = trt_mod(input, input2)
-    assertions.assertTrue(
-        len(model_outputs) == len(trt_model_outputs),
-        msg=f"Number of outputs for BERT model compilation is different with Pytorch {len(model_outputs)} and TensorRT {len(trt_model_outputs)}. Please check the compilation.",
-    )
-    for index, key in enumerate(model_outputs):
-        out, trt_out = model_outputs[key], trt_model_outputs[index]
-        cos_sim = cosine_similarity(out, trt_out)
-        assertions.assertTrue(
-            cos_sim > COSINE_THRESHOLD,
-            msg=f"HF BERT base-uncased TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
-        )
-
-    # Clean up model env
-    torch._dynamo.reset()
-
-
 @pytest.mark.unit
 def test_bert_base_uncased(ir):
     model = BertModel.from_pretrained("bert-base-uncased").cuda().eval()
@@ -183,7 +134,6 @@ def test_bert_base_uncased(ir):
         "truncate_long_and_double": True,
         "ir": ir,
         "min_block_size": 15,
-        "debug": True,
     }
     trt_mod = torchtrt.compile(model, **compile_spec)
     model_outputs = model(input, input2)
@@ -204,9 +154,6 @@ def test_bert_base_uncased(ir):
     # Clean up model env
     torch._dynamo.reset()
 
-    with torch.no_grad():
-        torch.cuda.empty_cache()
-
 
 @pytest.mark.unit
 def test_resnet18_half(ir):

From 4ae6ab95a98f5b1f644c3bfd3824ac76df442dc7 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 19 Mar 2024 17:05:51 -0700
Subject: [PATCH 010/122] chore: remove comments

---
 tests/py/dynamo/models/test_models_export.py | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/tests/py/dynamo/models/test_models_export.py b/tests/py/dynamo/models/test_models_export.py
index 4d0f4e2e7f..84f6bf7a36 100644
--- a/tests/py/dynamo/models/test_models_export.py
+++ b/tests/py/dynamo/models/test_models_export.py
@@ -110,11 +110,6 @@ def test_bert_base_uncased(ir):
     model = BertModel.from_pretrained("bert-base-uncased").cuda().eval()
     input = torch.randint(0, 1, (1, 14), dtype=torch.int32).to("cuda")
     input2 = torch.randint(0, 1, (1, 14), dtype=torch.int32).to("cuda")
-    # model = (
-    #     transformers_trace(model, input_names=["input_ids", "attention_mask"])
-    #     .eval()
-    #     .cuda()
-    # )
 
     compile_spec = {
         "inputs": [

From fff1b800f970f8ae56f9d7e48189095d57840a74 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 12 Mar 2024 02:11:29 -0700
Subject: [PATCH 011/122] chore: Upgrade to TRT 10.0

chore: updates to trt api

chore: trt 10 fixes

chore: more fixes
---
 .../converters/impl/constant_pad.cpp          |   2 +-
 .../converters/impl/conv_deconv.cpp           |   6 +-
 .../converters/impl/interpolate.cpp           |  50 +++---
 core/conversion/converters/impl/linear.cpp    |  30 ++--
 core/runtime/TRTEngine.cpp                    |  47 ++++--
 cpp/include/torch_tensorrt/ptq.h              |   8 +-
 py/torch_tensorrt/csrc/torch_tensorrt_py.cpp  |   5 +
 py/torch_tensorrt/dynamo/_compiler.py         |   2 +-
 .../dynamo/conversion/_TRTInterpreter.py      |   6 +-
 .../dynamo/conversion/_conversion.py          |   3 +-
 .../dynamo/conversion/impl/conv.py            |   2 +-
 .../dynamo/conversion/impl/deconv.py          |   2 +-
 .../conversion/impl/elementwise/base.py       |  11 --
 .../dynamo/conversion/impl/pad.py             |   8 +-
 .../dynamo/conversion/impl/permutation.py     |   4 +-
 .../dynamo/conversion/impl/upsample.py        |   6 +-
 .../runtime/_PythonTorchTensorRTModule.py     | 142 +++++++++---------
 .../fx/converters/acc_ops_converters.py       |  27 ++--
 py/torch_tensorrt/fx/utils.py                 |  18 ++-
 .../test_convert_method_to_trt_engine.py      |   8 +-
 20 files changed, 205 insertions(+), 182 deletions(-)

diff --git a/core/conversion/converters/impl/constant_pad.cpp b/core/conversion/converters/impl/constant_pad.cpp
index 4191cb1bab..20a091e730 100644
--- a/core/conversion/converters/impl/constant_pad.cpp
+++ b/core/conversion/converters/impl/constant_pad.cpp
@@ -55,7 +55,7 @@ auto constant_pad_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns
            util::toDims(c10::IntArrayRef(stride)));
        TORCHTRT_CHECK(slice_layer, "Unable to create slice layer from node: " << *n);
        slice_layer->setName((util::node_info(n) + "_slice").c_str());
-       slice_layer->setMode(nvinfer1::SliceMode::kFILL);
+       slice_layer->setMode(nvinfer1::SampleMode::kFILL);
        slice_layer->setInput(4, *value_itensor);
 
        if (ctx->input_is_dynamic) {
diff --git a/core/conversion/converters/impl/conv_deconv.cpp b/core/conversion/converters/impl/conv_deconv.cpp
index 66620197a9..bf0df00c64 100644
--- a/core/conversion/converters/impl/conv_deconv.cpp
+++ b/core/conversion/converters/impl/conv_deconv.cpp
@@ -61,7 +61,7 @@ nvinfer1::ILayer* add_bias_layer(
   auto* sliceLayer = ctx->net->addSlice(*input_tensor, dummy, dummy, stride);
   sliceLayer->setInput(1, *start);
   sliceLayer->setInput(2, *size);
-  sliceLayer->setMode(nvinfer1::SliceMode::kFILL);
+  sliceLayer->setMode(nvinfer1::SampleMode::kFILL);
   nvinfer1::ITensor* slice_output = sliceLayer->getOutput(0);
 
   nvinfer1::Dims constantDims;
@@ -194,7 +194,7 @@ bool add_conv_deconv(ConversionCtx* ctx, const torch::jit::Node* n, args& args)
       nvinfer1::IConvolutionLayer* convLayer =
           ctx->net->addConvolutionNd(*in, num_output_maps, filter_dim, kernel_weights, bias.data);
       convLayer->setStrideNd(stride);
-      convLayer->setPaddingMode(nvinfer1::PaddingMode::kCAFFE_ROUND_DOWN);
+      convLayer->setPaddingMode(nvinfer1::PaddingMode::kEXPLICIT_ROUND_DOWN);
       convLayer->setPaddingNd(padding);
       convLayer->setPostPadding(out_padding);
       convLayer->setDilationNd(dilation);
@@ -293,7 +293,7 @@ bool add_conv_deconv(ConversionCtx* ctx, const torch::jit::Node* n, args& args)
     TORCHTRT_CHECK(conv, "Unable to create convolution layer from node: " << *n);
 
     conv->setStrideNd(stride);
-    conv->setPaddingMode(nvinfer1::PaddingMode::kCAFFE_ROUND_DOWN);
+    conv->setPaddingMode(nvinfer1::PaddingMode::kEXPLICIT_ROUND_DOWN);
     conv->setPaddingNd(padding);
     conv->setPostPadding(out_padding);
     conv->setDilationNd(dilation);
diff --git a/core/conversion/converters/impl/interpolate.cpp b/core/conversion/converters/impl/interpolate.cpp
index fad2ca5121..61721e3d2c 100644
--- a/core/conversion/converters/impl/interpolate.cpp
+++ b/core/conversion/converters/impl/interpolate.cpp
@@ -72,7 +72,7 @@ void resize_layer_size(
     nvinfer1::ITensor* in,
     std::vector<int64_t> out_shape,
     std::vector<float> scales,
-    nvinfer1::ResizeMode mode,
+    nvinfer1::InterpolationMode mode,
     bool align_corners = false) {
   TORCHTRT_CHECK((out_shape.size() > 0) ^ (scales.size() > 0), "only one of out_shape or scales should be defined");
   auto resize_layer = ctx->net->addResize(*in);
@@ -141,7 +141,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  float scale = args[2].IValue()->toDouble();
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 1] = scale;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -150,7 +150,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -172,7 +172,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  float scale = scale_factors[0];
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 1] = scale;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -181,7 +181,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -203,7 +203,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -212,7 +212,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -236,7 +236,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -245,7 +245,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -270,7 +270,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  padded_scales[padded_scales.size() - 3] = scale_d;
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -279,7 +279,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -306,7 +306,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  padded_scales[padded_scales.size() - 3] = scale_d;
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kNEAREST);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -315,7 +315,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kNEAREST);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kNEAREST);
                }
 
                return true;
@@ -336,7 +336,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  float scale = args[3].IValue()->toDouble();
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 1] = scale;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -345,7 +345,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
@@ -368,7 +368,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  float scale = scale_factors[0];
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 1] = scale;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -377,7 +377,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
@@ -400,7 +400,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -410,7 +410,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
@@ -435,7 +435,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  std::vector<float> padded_scales(in_shape.size(), 1);
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -445,7 +445,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
@@ -470,7 +470,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  padded_scales[padded_scales.size() - 3] = scale_d;
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -480,7 +480,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
@@ -507,7 +507,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
                  padded_scales[padded_scales.size() - 3] = scale_d;
                  padded_scales[padded_scales.size() - 2] = scale_h;
                  padded_scales[padded_scales.size() - 1] = scale_w;
-                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, {}, padded_scales, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                } else {
                  // Case 2: user uses output size
                  auto out_size = util::toVec(util::toDims(args[1].unwrapToIntList()));
@@ -517,7 +517,7 @@ auto interpolate_registrations TORCHTRT_UNUSED =
 
                  auto out_shape = in_shape;
                  std::copy(out_size.begin(), out_size.end(), out_shape.begin() + (in_shape.size() - out_size.size()));
-                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::ResizeMode::kLINEAR, align_corners);
+                 resize_layer_size(ctx, n, in, out_shape, {}, nvinfer1::InterpolationMode::kLINEAR, align_corners);
                }
 
                return true;
diff --git a/core/conversion/converters/impl/linear.cpp b/core/conversion/converters/impl/linear.cpp
index 6289334736..39f9cb055d 100644
--- a/core/conversion/converters/impl/linear.cpp
+++ b/core/conversion/converters/impl/linear.cpp
@@ -40,22 +40,26 @@ auto linear_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns().pat
          in = in_shuffle->getOutput(0);
        }
 
-       auto w_tensor = args[1].IValue()->toTensor();
-       Weights w = Weights(ctx, w_tensor);
+       // Convert w_tensor to ITensor
+       auto weight = args[1].IValue()->toTensor();
+       auto weight_tensor = tensor_to_const(ctx, weight, util::node_info(n) + "_weight");
+       auto mm_layer = ctx->net->addMatrixMultiply(
+           *in, nvinfer1::MatrixOperation::kNONE, *weight_tensor, nvinfer1::MatrixOperation::kNONE);
 
-       nvinfer1::ILayer* new_layer;
-       if (!args[2].IValue()->isNone()) {
-         Weights b(ctx, args[2].IValue()->toTensor());
-         new_layer = ctx->net->addFullyConnected(*in, w.num_output_maps, w.data, b.data);
-       } else {
-         LOG_DEBUG("There is no bias for the linear layer");
-         new_layer = ctx->net->addFullyConnected(*in, w.num_output_maps, w.data, Weights().data);
-       }
+       TORCHTRT_CHECK(mm_layer, "Unable to create linear layer from node: " << *n);
+       mm_layer->setName(util::node_info(n).c_str());
 
-       TORCHTRT_CHECK(new_layer, "Unable to create linear layer from node: " << *n);
+       auto mm_output = mm_layer->getOutput(0);
 
-       new_layer->setName(util::node_info(n).c_str());
-       auto out_tensor = ctx->AssociateValueAndTensor(n->outputs()[0], new_layer->getOutput(0));
+       if (!args[2].IValue()->isNone()) {
+         // Convert bias to ITensor
+         auto bias = args[2].IValue()->toTensor();
+         auto bias_tensor = tensor_to_const(ctx, bias, util::node_info(n) + "_bias");
+         auto bias_add_layer = add_elementwise(
+             ctx, nvinfer1::ElementWiseOperation::kSUM, mm_output, bias_tensor, util::node_info(n) + "_bias_add");
+         mm_output = bias_add_layer->getOutput(0);
+       }
+       auto out_tensor = ctx->AssociateValueAndTensor(n->outputs()[0], mm_output);
 
        LOG_DEBUG("Output tensor shape: " << out_tensor->getDimensions());
 
diff --git a/core/runtime/TRTEngine.cpp b/core/runtime/TRTEngine.cpp
index 7a046f6d94..fcbb403e2c 100644
--- a/core/runtime/TRTEngine.cpp
+++ b/core/runtime/TRTEngine.cpp
@@ -120,16 +120,25 @@ TRTEngine::TRTEngine(
   } else {
     uint64_t inputs_size = _in_binding_names.size();
     in_binding_names.resize(inputs_size);
-    for (size_t pyt_idx = 0; pyt_idx < inputs_size; pyt_idx++) {
+    for (uint64_t pyt_idx = 0; pyt_idx < inputs_size; pyt_idx++) {
       auto binding_name = _in_binding_names[pyt_idx];
-      auto trt_idx = cuda_engine->getBindingIndex(binding_name.c_str());
-      std::string engine_binded_name = cuda_engine->getIOTensorName(trt_idx);
-      TORCHTRT_CHECK(
-          (binding_name == engine_binded_name),
-          "Could not find a TensorRT engine binding for input named " << binding_name);
+      // Check if the binding name provided is in the list of engine's bindings
+      // by iterating through nbIOTensors and verify it is an input binding
+      bool is_binding = false, is_input = false;
+      int32_t trt_idx;
+      for (int32_t idx = 0; idx < cuda_engine->getNbIOTensors(); idx++) {
+        std::string curr_bind_name = cuda_engine->getIOTensorName(idx);
+        if (curr_bind_name == binding_name) {
+          is_binding = true;
+          trt_idx = idx;
+          if (cuda_engine->getTensorIOMode(binding_name.c_str()) == nvinfer1::TensorIOMode::kINPUT) {
+            is_input = true;
+          }
+        }
+      }
+      TORCHTRT_CHECK(is_binding, "Could not find a TensorRT engine binding for input named " << binding_name);
       TORCHTRT_CHECK(
-          (cuda_engine->getTensorIOMode(binding_name.c_str()) == nvinfer1::TensorIOMode::kINPUT),
-          "Binding " << binding_name << " specified as input but found as output in TensorRT engine");
+          is_input, "Binding " << binding_name << " specified as input but found as output in TensorRT engine");
       LOG_DEBUG(
           "Input binding name: " << binding_name << " has TensorRT binding index: " << trt_idx
                                  << ", Torch binding index: " << pyt_idx);
@@ -141,11 +150,25 @@ TRTEngine::TRTEngine(
     out_binding_names.resize(outputs);
     for (size_t pyt_idx = 0; pyt_idx < outputs; pyt_idx++) {
       auto binding_name = _out_binding_names[pyt_idx];
-      auto trt_idx = cuda_engine->getBindingIndex(binding_name.c_str());
-      TORCHTRT_CHECK((trt_idx != -1), "Could not find a TensorRT engine binding for output named " << binding_name);
+      // Check if the binding name provided is in the list of engine's bindings
+      // by iterating through nbIOTensors and verify it is an output binding
+      bool is_binding = false, is_output = false;
+      int32_t trt_idx;
+      for (int32_t idx = 0; idx < cuda_engine->getNbIOTensors(); idx++) {
+        std::string curr_bind_name = cuda_engine->getIOTensorName(idx);
+        if (curr_bind_name == binding_name) {
+          is_binding = true;
+          trt_idx = idx;
+          if (cuda_engine->getTensorIOMode(binding_name.c_str()) == nvinfer1::TensorIOMode::kOUTPUT) {
+            is_output = true;
+          }
+        }
+      }
+
+      TORCHTRT_CHECK(is_binding, "Could not find a TensorRT engine binding for output named " << binding_name);
       TORCHTRT_CHECK(
-          !(cuda_engine->getTensorIOMode(binding_name.c_str()) == nvinfer1::TensorIOMode::kINPUT),
-          "Binding " << binding_name << " specified as output but found as input in TensorRT engine");
+          is_output, "Binding " << binding_name << " specified as output but found as input in TensorRT engine");
+
       LOG_DEBUG(
           "Output binding name: " << binding_name << " has TensorRT binding index: " << trt_idx
                                   << ", Torch binding index: " << inputs_size + pyt_idx);
diff --git a/cpp/include/torch_tensorrt/ptq.h b/cpp/include/torch_tensorrt/ptq.h
index d8570f0e6e..e88da06b0c 100644
--- a/cpp/include/torch_tensorrt/ptq.h
+++ b/cpp/include/torch_tensorrt/ptq.h
@@ -21,10 +21,10 @@
 #include "torch_tensorrt/macros.h"
 
 #ifndef DOXYGEN_SHOULD_SKIP_THIS
-namespace nvinfer1 {
-class IInt8Calibrator;
-class IInt8EntropyCalibrator2;
-} // namespace nvinfer1
+// namespace nvinfer1 {
+// class IInt8Calibrator;
+// class IInt8EntropyCalibrator2;
+// } // namespace nvinfer1
 
 namespace torch_tensorrt {
 namespace ptq {
diff --git a/py/torch_tensorrt/csrc/torch_tensorrt_py.cpp b/py/torch_tensorrt/csrc/torch_tensorrt_py.cpp
index 33c7e27398..c0655d9907 100644
--- a/py/torch_tensorrt/csrc/torch_tensorrt_py.cpp
+++ b/py/torch_tensorrt/csrc/torch_tensorrt_py.cpp
@@ -2,6 +2,7 @@
 #include "pybind11/stl.h"
 
 #include "ATen/core/jit_type.h"
+#include "NvInferRuntimeBase.h"
 #include "Python.h"
 #include "core/compiler.h"
 #include "core/conversion/conversion.h"
@@ -77,6 +78,10 @@ class pyIInt8Calibrator : public pyCalibratorTrampoline<nvinfer1::IInt8Calibrato
   using Derived = pyCalibratorTrampoline<nvinfer1::IInt8Calibrator>;
   using Derived::Derived;
 
+  nvinfer1::InterfaceInfo getInterfaceInfo() const noexcept override {
+    return nvinfer1::InterfaceInfo{"PYTHON CALIBRATOR", 1, 0};
+  }
+
   nvinfer1::CalibrationAlgoType getAlgorithm() noexcept override {
     try {
       PYBIND11_OVERLOAD_PURE_NAME(
diff --git a/py/torch_tensorrt/dynamo/_compiler.py b/py/torch_tensorrt/dynamo/_compiler.py
index b321eabcb2..ac430bf883 100644
--- a/py/torch_tensorrt/dynamo/_compiler.py
+++ b/py/torch_tensorrt/dynamo/_compiler.py
@@ -634,7 +634,7 @@ def convert_module_to_trt_engine(
     import io
 
     with io.BytesIO() as engine_bytes:
-        engine_bytes.write(interpreter_result.engine.serialize())
+        engine_bytes.write(interpreter_result.engine)
         engine_bytearray = engine_bytes.getvalue()
 
     return engine_bytearray
diff --git a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
index 06ae596ed0..ffcc9c195e 100644
--- a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
+++ b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
@@ -172,7 +172,7 @@ def run(
 
         if version.parse(trt.__version__) >= version.parse("8.2"):
             builder_config.profiling_verbosity = (
-                trt.ProfilingVerbosity.VERBOSE
+                trt.ProfilingVerbosity.DETAILED
                 if self.compilation_settings.debug
                 else trt.ProfilingVerbosity.LAYER_NAMES_ONLY
             )
@@ -252,7 +252,7 @@ def run(
         if tactic_sources is not None:
             builder_config.set_tactic_sources(tactic_sources=tactic_sources)
 
-        engine = self.builder.build_engine(self.ctx.net, builder_config)
+        engine = self.builder.build_serialized_network(self.ctx.net, builder_config)
         assert engine
 
         serialized_cache = (
@@ -263,7 +263,7 @@ def run(
         _LOGGER.info(
             f"Build TRT engine elapsed time: {datetime.now() - build_engine_start_time}"
         )
-        _LOGGER.info(f"TRT Engine uses: {engine.device_memory_size} bytes of Memory")
+        _LOGGER.info(f"TRT Engine uses: {engine.nbytes} bytes of Memory")
 
         return TRTInterpreterResult(
             engine, self._input_names, self._output_names, serialized_cache
diff --git a/py/torch_tensorrt/dynamo/conversion/_conversion.py b/py/torch_tensorrt/dynamo/conversion/_conversion.py
index 844cb6789a..f1f4af9236 100644
--- a/py/torch_tensorrt/dynamo/conversion/_conversion.py
+++ b/py/torch_tensorrt/dynamo/conversion/_conversion.py
@@ -87,8 +87,9 @@ def convert_module(
         from torch_tensorrt.dynamo.runtime import TorchTensorRTModule
 
         with io.BytesIO() as engine_bytes:
-            engine_bytes.write(interpreter_result.engine.serialize())
+            engine_bytes.write(interpreter_result.engine)
             engine_str = engine_bytes.getvalue()
+
         return TorchTensorRTModule(
             serialized_engine=engine_str,
             name=name,
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/conv.py b/py/torch_tensorrt/dynamo/conversion/impl/conv.py
index 26e0d59b8f..6c15b4b5fe 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/conv.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/conv.py
@@ -63,7 +63,7 @@ def convNd(
         )
 
     # Process weight terms
-    if ctx.net.has_explicit_precision or isinstance(weight, TRTTensor):
+    if isinstance(weight, TRTTensor):
         weight = get_trt_tensor(ctx, weight, f"{name}_weight")
         # Append new dimension (unsqueeze) if the convolution is 1d
         if is_conv1d:
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/deconv.py b/py/torch_tensorrt/dynamo/conversion/impl/deconv.py
index f66bff7c82..03a209e2a5 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/deconv.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/deconv.py
@@ -63,7 +63,7 @@ def deconvNd(
         )
 
     # Process weight terms
-    if ctx.net.has_explicit_precision or isinstance(weight, TRTTensor):
+    if isinstance(weight, TRTTensor):
         weight = get_trt_tensor(ctx, weight, f"{name}_weight")
         # Append new dimension (unsqueeze) if the deconvolution is 1d
         if is_deconv1d:
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py b/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
index 8282ee8698..6664a67cfe 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
@@ -147,17 +147,6 @@ def convert_binary_elementwise(
             ctx, rhs_val, trt_promoted_type, name, target, source_ir
         )
 
-    # Check the limitation in the doc string.
-    if ctx.net.has_implicit_batch_dimension:
-        if is_lhs_trt_tensor and not is_rhs_trt_tensor:
-            assert len(lhs_val.shape) >= len(
-                rhs_val.shape
-            ), f"{lhs_val.shape} >= {rhs_val.shape}"
-        elif not is_lhs_trt_tensor and is_rhs_trt_tensor:
-            assert len(rhs_val.shape) >= len(
-                lhs_val.shape
-            ), f"{rhs_val.shape} >= {lhs_val.shape}"
-
     lhs_val, rhs_val = broadcast(
         ctx.net, lhs_val, rhs_val, f"{name}_lhs", f"{name}_rhs"
     )
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/pad.py b/py/torch_tensorrt/dynamo/conversion/impl/pad.py
index 3764667ffb..9031426c5c 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/pad.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/pad.py
@@ -53,7 +53,7 @@ def constant_padNd(
     )
     value_const = get_trt_tensor(ctx, value, f"{name}_value", input.dtype)
     layer.set_input(4, value_const)
-    layer.mode = trt.SliceMode.FILL
+    layer.mode = trt.SampleMode.FILL
 
     set_layer_name(layer, target, name, source_ir)
     return layer.get_output(0)
@@ -91,7 +91,7 @@ def reflection_padNd(
         shape=tuple(new_shape),
         stride=tuple(stride_list),
     )
-    layer.mode = trt.SliceMode.REFLECT
+    layer.mode = trt.SampleMode.REFLECT
 
     set_layer_name(layer, target, name, source_ir)
     return layer.get_output(0)
@@ -129,7 +129,7 @@ def replication_padNd(
         shape=tuple(new_shape),
         stride=tuple(stride_list),
     )
-    layer.mode = trt.SliceMode.CLAMP
+    layer.mode = trt.SampleMode.CLAMP
 
     set_layer_name(layer, target, name, source_ir)
     return layer.get_output(0)
@@ -167,7 +167,7 @@ def circular_padNd(
         shape=tuple(new_shape),
         stride=tuple(stride_list),
     )
-    layer.mode = trt.SliceMode.WRAP
+    layer.mode = trt.SampleMode.WRAP
 
     set_layer_name(layer, target, name, source_ir)
     return layer.get_output(0)
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/permutation.py b/py/torch_tensorrt/dynamo/conversion/impl/permutation.py
index 48a91faa40..4fabebd176 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/permutation.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/permutation.py
@@ -66,7 +66,7 @@ def roll(
             shape=shape,
             stride=stride,
         )
-        layer.mode = trt.SliceMode.WRAP
+        layer.mode = trt.SampleMode.WRAP
         set_layer_name(layer, target, f"{name}_slice_wrap", source_ir)
         return layer.get_output(0)
 
@@ -83,7 +83,7 @@ def roll(
             shape=flatten_shape,
             stride=stride,
         )
-        layer.mode = trt.SliceMode.WRAP
+        layer.mode = trt.SampleMode.WRAP
         set_layer_name(layer, target, f"{name}_slice_wrap", source_ir)
         output = layer.get_output(0)
         output = impl.shuffle.reshape(
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/upsample.py b/py/torch_tensorrt/dynamo/conversion/impl/upsample.py
index 3313730ec3..c61aad4290 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/upsample.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/upsample.py
@@ -29,14 +29,14 @@ def upsample(
         resize_layer.scales = [1.0, 1.0] + list(scale_factors)
     else:
         raise RuntimeError(
-            f"At least one of out_shape and scale_factors should be specified."
+            "At least one of out_shape and scale_factors should be specified."
         )
 
     # interpolate mode
     if resize_mode == "nearest" or None:
-        resize_layer.resize_mode = trt.ResizeMode.NEAREST
+        resize_layer.resize_mode = trt.InterpolationMode.NEAREST
     elif resize_mode == "bilinear":
-        resize_layer.resize_mode = trt.ResizeMode.LINEAR
+        resize_layer.resize_mode = trt.InterpolationMode.LINEAR
         if align_corners is None or not align_corners:
             raise RuntimeError(
                 f"Interpolation works differently is align_corners is False for {resize_mode} mode in PyTorch and TensorRT."
diff --git a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
index 3a66ed3716..82f5817b01 100644
--- a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
+++ b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
@@ -2,7 +2,7 @@
 
 import logging
 from contextlib import nullcontext
-from typing import Any, Dict, List, Optional, Sequence, Tuple
+from typing import Any, Dict, List, Optional, Tuple
 
 import tensorrt as trt
 import torch
@@ -55,73 +55,69 @@ def __init__(
 
     def _initialize(self) -> None:
         self.initialized = True
+        logger = trt.Logger()
+        runtime = trt.Runtime(logger)
+        self.engine = runtime.deserialize_cuda_engine(self.engine)
         self.context = self.engine.create_execution_context()
 
         # Indices of inputs/outputs in the trt engine bindings, in the order
         # as they are in the original PyTorch model.
-        self.input_binding_indices_in_order: Sequence[int] = [
-            self.engine.get_binding_index(name) for name in self.input_names
-        ]
-        self.output_binding_indices_in_order: Sequence[int] = [
-            self.engine.get_binding_index(name) for name in self.output_names
-        ]
-        primary_input_outputs = set()
-        primary_input_outputs.update(self.input_binding_indices_in_order)
-        primary_input_outputs.update(self.output_binding_indices_in_order)
-        self.hidden_output_binding_indices_in_order: Sequence[int] = []
-        self.hidden_output_names: Sequence[str] = []
-        for i in range(
-            self.engine.num_bindings // self.engine.num_optimization_profiles
-        ):
-            if i not in primary_input_outputs:
-                self.hidden_output_binding_indices_in_order.append(i)
-                self.hidden_output_names.append(self.engine.get_binding_name(i))
 
-        assert (self.engine.num_bindings // self.engine.num_optimization_profiles) == (
+        # TODO: Verify if the following is required especially the hidden outputs
+        # self.input_binding_indices_in_order: Sequence[int] = [
+        #     self.engine.get_binding_index(name) for name in self.input_names
+        # ]
+        # self.output_binding_indices_in_order: Sequence[int] = [
+        #     self.engine.get_binding_index(name) for name in self.output_names
+        # ]
+        # primary_input_outputs = set()
+        # primary_input_outputs.update(self.input_binding_indices_in_order)
+        # primary_input_outputs.update(self.output_binding_indices_in_order)
+        # self.hidden_output_binding_indices_in_order: Sequence[int] = []
+        # self.hidden_output_names: Sequence[str] = []
+        # for i in range(
+        #     self.engine.num_bindings // self.engine.num_optimization_profiles
+        # ):
+        #     if i not in primary_input_outputs:
+        #         self.hidden_output_binding_indices_in_order.append(i)
+        #         self.hidden_output_names.append(self.engine.get_binding_name(i))
+
+        assert (
+            self.engine.num_io_tensors // self.engine.num_optimization_profiles
+        ) == (
             len(self.input_names)
             + len(self.output_names)
-            + len(self.hidden_output_names)
+            # + len(self.hidden_output_names) #TODO: Verify if this is required
         )
 
         self.input_dtypes = [
             unified_dtype_converter(
-                self.engine.get_binding_dtype(idx), Frameworks.TORCH
+                self.engine.get_tensor_dtype(input_name), Frameworks.TORCH
             )
-            for idx in self.input_binding_indices_in_order
+            for input_name in self.input_names
         ]
-        self.input_shapes: Sequence[Sequence[int]] = [
-            tuple(self.engine.get_binding_shape(idx))
-            for idx in self.input_binding_indices_in_order
+        self.input_shapes = [
+            self.engine.get_tensor_shape(input_name) for input_name in self.input_names
         ]
         self.output_dtypes = [
             unified_dtype_converter(
-                self.engine.get_binding_dtype(idx), Frameworks.TORCH
+                self.engine.get_tensor_dtype(output_name), Frameworks.TORCH
             )
-            for idx in self.output_binding_indices_in_order
+            for output_name in self.output_names
         ]
         self.output_shapes = [
-            (
-                tuple(self.engine.get_binding_shape(idx))
-                if self.engine.has_implicit_batch_dimension
-                else tuple()
-            )
-            for idx in self.output_binding_indices_in_order
-        ]
-        self.hidden_output_dtypes = [
-            unified_dtype_converter(
-                self.engine.get_binding_dtype(idx), Frameworks.TORCH
-            )
-            for idx in self.hidden_output_binding_indices_in_order
-        ]
-        self.hidden_output_shapes = [
-            (
-                tuple(self.engine.get_binding_shape(idx))
-                if self.engine.has_implicit_batch_dimension
-                else tuple()
-            )
-            for idx in self.hidden_output_binding_indices_in_order
+            self.engine.get_tensor_shape(output_name)
+            for output_name in self.output_names
         ]
 
+        # TODO: Verify what this is for ?
+        # self.hidden_output_dtypes = [
+        #     unified_dtype_converter(
+        #         self.engine.get_binding_dtype(idx), Frameworks.TORCH
+        #     )
+        #     for idx in self.hidden_output_binding_indices_in_order
+        # ]
+
     def _check_initialized(self) -> None:
         if not self.initialized:
             raise RuntimeError("PythonTorchTensorRTModule is not initialized.")
@@ -217,12 +213,12 @@ def forward(self, *inputs: torch.Tensor) -> torch.Tensor | Tuple[torch.Tensor, .
                 ), f"Wrong number of inputs, expect {len(self.input_names)} get {len(inputs)}."
 
                 contiguous_inputs: List[torch.Tensor] = [i.contiguous() for i in inputs]
-                bindings: List[Any] = [None] * (
-                    len(self.input_names)
-                    + len(self.output_names)
-                    + len(self.hidden_output_names)
-                )
-
+                bindings = []
+                # [None] * (
+                #     len(self.input_names)
+                #     + len(self.output_names)
+                #     # + len(self.hidden_output_names) # TODO: Verify if this is required
+                # )
                 for i, input_name in enumerate(self.input_names):
                     if not contiguous_inputs[i].is_cuda:
                         logger.warning(
@@ -241,11 +237,9 @@ def forward(self, *inputs: torch.Tensor) -> torch.Tensor | Tuple[torch.Tensor, .
                         contiguous_inputs[i].dtype == self.input_dtypes[i]
                     ), f"Dtype mismatch for {i}th input({input_name}). Expect {self.input_dtypes[i]}, got {contiguous_inputs[i].dtype}."
 
-                    idx = self.input_binding_indices_in_order[i]
-                    bindings[idx] = contiguous_inputs[i].data_ptr()
-
-                    self.context.set_binding_shape(
-                        idx, tuple(contiguous_inputs[i].shape)
+                    bindings.append(contiguous_inputs[i].data_ptr())
+                    self.context.set_input_shape(
+                        input_name, tuple(contiguous_inputs[i].shape)
                     )
 
             with (
@@ -258,26 +252,32 @@ def forward(self, *inputs: torch.Tensor) -> torch.Tensor | Tuple[torch.Tensor, .
                 # create output tensors
                 outputs: List[torch.Tensor] = []
 
-                for i, idx in enumerate(self.output_binding_indices_in_order):
-                    shape = tuple(self.context.get_binding_shape(idx))
+                for i, output_name in enumerate(self.output_names):
+                    shape = tuple(self.context.get_tensor_shape(output_name))
 
                     output = torch.empty(
                         size=shape,
                         dtype=self.output_dtypes[i],
                         device=torch.cuda.current_device(),
                     )
+                    bindings.append(output.data_ptr())
                     outputs.append(output)
-                    bindings[idx] = output.data_ptr()
 
-                for i, idx in enumerate(self.hidden_output_binding_indices_in_order):
-                    shape = tuple(self.context.get_binding_shape(idx))
+                # TODO: Check what is this for ?
+                # for i, idx in enumerate(self.hidden_output_binding_indices_in_order):
+                #     shape = tuple(self.context.get_binding_shape(idx))
 
-                    output = torch.empty(
-                        size=shape,
-                        dtype=self.hidden_output_dtypes[i],
-                        device=torch.cuda.current_device(),
-                    )
-                    bindings[idx] = output.data_ptr()
+                #     output = torch.empty(
+                #         size=shape,
+                #         dtype=self.hidden_output_dtypes[i],
+                #         device=torch.cuda.current_device(),
+                #     )
+
+            # Assign tensor address appropriately
+            for idx in range(self.engine.num_io_tensors):
+                self.context.set_tensor_address(
+                    self.engine.get_tensor_name(idx), bindings[idx]
+                )
 
             with (
                 torch.autograd.profiler.record_function(
@@ -286,9 +286,7 @@ def forward(self, *inputs: torch.Tensor) -> torch.Tensor | Tuple[torch.Tensor, .
                 if self.profiling_enabled
                 else nullcontext()
             ):
-                self.context.execute_async_v2(
-                    bindings, torch.cuda.current_stream().cuda_stream
-                )
+                self.context.execute_async_v3(torch.cuda.current_stream().cuda_stream)
 
             if len(outputs) == 1:
                 return outputs[0]
diff --git a/py/torch_tensorrt/fx/converters/acc_ops_converters.py b/py/torch_tensorrt/fx/converters/acc_ops_converters.py
index 1765077930..f998ddb27a 100644
--- a/py/torch_tensorrt/fx/converters/acc_ops_converters.py
+++ b/py/torch_tensorrt/fx/converters/acc_ops_converters.py
@@ -3,30 +3,27 @@
 import math
 import operator
 import warnings
-from typing import cast, Dict, Optional, Sequence, Tuple, Union
+from typing import Dict, Optional, Sequence, Tuple, Union, cast
 
 import numpy as np
 
 # @manual=//deeplearning/trt/python:py_tensorrt
 import tensorrt as trt
 import torch
-
-from ..converter_registry import tensorrt_converter
-
-from ..tracer.acc_tracer import acc_ops
-from ..types import *  # noqa: F403
 from torch.fx.immutable_collections import immutable_list
 from torch.fx.node import Argument, Target
-
-from ..utils import get_dynamic_dims, unified_dtype_converter, Frameworks
-
-from .converter_utils import *  # noqa: F403
+from torch_tensorrt.fx.converters.impl import activation, convolution
 from torch_tensorrt.fx.passes.lower_basic_pass import (
     trt_transposed_linear,
     trt_transposed_matmul,
 )
 from torch_tensorrt.fx.tracer.acc_tracer.acc_ops import contiguous
-from torch_tensorrt.fx.converters.impl import activation, convolution
+
+from ..converter_registry import tensorrt_converter
+from ..tracer.acc_tracer import acc_ops
+from ..types import *  # noqa: F403
+from ..utils import Frameworks, get_dynamic_dims, unified_dtype_converter
+from .converter_utils import *  # noqa: F403
 
 _LOGGER: logging.Logger = logging.getLogger(__name__)
 
@@ -323,7 +320,7 @@ def acc_ops_pad_with_slice_layer(
     )
 
     layer.set_input(4, value_const)
-    layer.mode = trt.SliceMode.FILL
+    layer.mode = trt.SampleMode.FILL
     set_layer_name(layer, target, name)
 
     return layer.get_output(0)
@@ -840,7 +837,7 @@ def acc_ops_tile(
         shapes = [1] * len(dims)
     strides = [1] * len(dims)
     layer = network.add_slice(input_val, starts, shapes, strides)
-    layer.mode = trt.SliceMode.WRAP
+    layer.mode = trt.SampleMode.WRAP
     set_layer_name(layer, target, name)
 
     if has_dynamic_shape(input_val.shape):  # type: ignore[union-attr]
@@ -3536,9 +3533,9 @@ def acc_ops_interpolate(
                 layer.scales = [1, 1] + list(scale_factor)
 
     if mode.lower() in ["linear", "bilinear", "trilinear"]:
-        layer.resize_mode = trt.ResizeMode.LINEAR
+        layer.resize_mode = trt.InterpolationMode.LINEAR
     else:
-        layer.resize_mode = trt.ResizeMode.NEAREST
+        layer.resize_mode = trt.InterpolationMode.NEAREST
 
     if (align_corners is not None) and align_corners:
         layer.coordinate_transformation = (
diff --git a/py/torch_tensorrt/fx/utils.py b/py/torch_tensorrt/fx/utils.py
index 4202e1e96b..9acc53ffc8 100644
--- a/py/torch_tensorrt/fx/utils.py
+++ b/py/torch_tensorrt/fx/utils.py
@@ -1,18 +1,21 @@
 from enum import Enum
-from typing import Dict, List, Optional, Callable, Union
+from typing import Callable, Dict, List, Optional, Union
+
 import numpy as np
-from packaging import version
 
 # @manual=//deeplearning/trt/python:py_tensorrt
 import tensorrt as trt
 import torch
 from functorch import make_fx
 from functorch.experimental import functionalize
+from torch_tensorrt._utils import sanitized_torch_version
 from torch_tensorrt.fx.passes.lower_basic_pass import (
     replace_op_with_indices,
     run_const_fold,
 )
-from torch_tensorrt._utils import sanitized_torch_version
+
+from packaging import version
+
 from .types import Shape, TRTDataType
 
 
@@ -45,6 +48,11 @@ class Frameworks(Enum):
         Frameworks.TORCH: torch.float32,
         Frameworks.TRT: trt.float32,
     },
+    trt.bool: {
+        Frameworks.NUMPY: bool,
+        Frameworks.TORCH: torch.bool,
+        Frameworks.TRT: trt.bool,
+    },
 }
 
 if trt.__version__ >= "7.0":
@@ -89,10 +97,10 @@ def unified_dtype_converter(
         The equivalent data type in the requested framework.
     """
     assert to in Frameworks, f"Expected valid Framework for translation, got {to}"
-
+    trt_major_version = int(trt.__version__.split(".")[0])
     if dtype in (np.int8, torch.int8, trt.int8):
         return DataTypeEquivalence[trt.int8][to]
-    elif trt.__version__ >= "7.0" and dtype in (np.bool_, torch.bool, trt.bool):
+    elif trt_major_version >= 7 and dtype in (np.bool_, torch.bool, trt.bool):
         return DataTypeEquivalence[trt.bool][to]
     elif dtype in (np.int32, torch.int32, trt.int32):
         return DataTypeEquivalence[trt.int32][to]
diff --git a/tests/py/dynamo/runtime/test_convert_method_to_trt_engine.py b/tests/py/dynamo/runtime/test_convert_method_to_trt_engine.py
index b10cae23fa..46a9ab392c 100644
--- a/tests/py/dynamo/runtime/test_convert_method_to_trt_engine.py
+++ b/tests/py/dynamo/runtime/test_convert_method_to_trt_engine.py
@@ -25,12 +25,10 @@ def forward(self, a, b):
             symbolic_traced_gm, "forward", inputs=[input_data_0, input_data_1]
         )
 
-        # Deserialize the TensorRT engine
-        with trt.Logger() as logger, trt.Runtime(logger) as runtime:
-            engine = runtime.deserialize_cuda_engine(trt_engine_str)
-
         # Inference on TRT Engine
-        py_trt_module = PythonTorchTensorRTModule(engine, ["a", "b"], ["output0"])
+        py_trt_module = PythonTorchTensorRTModule(
+            trt_engine_str, ["a", "b"], ["output0"]
+        )
         trt_output = py_trt_module(input_data_0, input_data_1).cpu()
 
         # Inference on PyTorch model

From 39ca77df3345179ec1560bfb54da5975fc67ca6b Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 21 Mar 2024 16:53:35 -0700
Subject: [PATCH 012/122] chore: more fixes

---
 .../conversion/impl/elementwise/base.py       |  1 +
 .../dynamo/conversion/impl/elementwise/ops.py |  1 +
 .../dynamo/conversion/impl/select.py          | 23 ++++++++++++-------
 .../dynamo/conversion/impl/shape.py           | 14 +++++++----
 .../fx/converters/converter_utils.py          | 10 +++++---
 py/torch_tensorrt/fx/utils.py                 |  7 ++++++
 tests/py/dynamo/conversion/test_erf_aten.py   |  6 +----
 tests/py/dynamo/conversion/test_neg_aten.py   |  6 +----
 8 files changed, 42 insertions(+), 26 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py b/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
index 6664a67cfe..615cd0bd62 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
@@ -150,6 +150,7 @@ def convert_binary_elementwise(
     lhs_val, rhs_val = broadcast(
         ctx.net, lhs_val, rhs_val, f"{name}_lhs", f"{name}_rhs"
     )
+
     layer = ctx.net.add_elementwise(lhs_val, rhs_val, op_type)
     set_layer_name(layer, target, name, source_ir)
     output = layer.get_output(0)
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/elementwise/ops.py b/py/torch_tensorrt/dynamo/conversion/impl/elementwise/ops.py
index d0f6d29482..77ec68629b 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/elementwise/ops.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/elementwise/ops.py
@@ -244,6 +244,7 @@ def add(
     lhs_val: Union[TRTTensor, int, float],
     rhs_val: Union[TRTTensor, int, float],
 ) -> TRTTensor:
+
     return convert_binary_elementwise(
         ctx, target, source_ir, name, trt.ElementWiseOperation.SUM, lhs_val, rhs_val
     )
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/select.py b/py/torch_tensorrt/dynamo/conversion/impl/select.py
index db586be65f..955ef2bb76 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/select.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/select.py
@@ -1,5 +1,5 @@
 import logging
-from typing import Optional, Sequence, Union, cast
+from typing import Any, Optional, cast
 
 import numpy as np
 import tensorrt as trt
@@ -9,6 +9,7 @@
 from torch_tensorrt.dynamo.conversion._ConversionContext import ConversionContext
 from torch_tensorrt.dynamo.conversion.converter_utils import (
     broadcastable,
+    cast_trt_tensor,
     get_positive_dim,
     get_trt_tensor,
     to_numpy,
@@ -81,7 +82,7 @@ def index(
     source_ir: Optional[SourceIR],
     name: str,
     input: TRTTensor,
-    index: Sequence[Union[TRTTensor, np.ndarray, torch.Tensor]],
+    index: Any,
 ) -> TRTTensor:
     adv_indx_indices = []
     tensor_indices = []
@@ -90,7 +91,7 @@ def index(
     # is_numpy is a flag to specify if all the indices are numpy or torchTensor.
     # If any is not this flag will be set to False
     _LOGGER.debug(
-        f"Determining whether aten.index constant-index optimization can be invoked"
+        "Determining whether aten.index constant-index optimization can be invoked"
     )
     is_numpy = all(
         isinstance(ind, (torch.Tensor, np.ndarray)) for ind in index if ind is not None
@@ -123,7 +124,7 @@ def index(
         return identity_layer.get_output(0)
     elif len(tensor_indices) == 1:
         indices_tensor = get_trt_tensor(
-            ctx, tensor_indices[0], name + f"_parameter_to_fp32_tensor"
+            ctx, tensor_indices[0], name + "_parameter_to_fp32_tensor"
         )
         index = adv_indx_indices[0]
         _LOGGER.debug(f"The advanced index indices is {adv_indx_indices}")
@@ -204,7 +205,7 @@ def index(
                 cum_adv_index = cum_adv_index + adv_index
                 multiplier = multiplier * input_shape[adv_indx_indices[i]]
             cum_adv_index = get_trt_tensor(
-                ctx, cum_adv_index, name + f"_index_sum_intermediate"
+                ctx, cum_adv_index, name + "_index_sum_intermediate"
             )
         else:
             multiplier = get_trt_tensor(
@@ -255,6 +256,12 @@ def index(
             cum_adv_index_shape_layer, target, name + "_cum_adv_index_shape", source_ir
         )
         cum_adv_index_shape_tensor = cum_adv_index_shape_layer.get_output(0)
+        cum_adv_index_shape_tensor = cast_trt_tensor(
+            ctx,
+            cum_adv_index_shape_tensor,
+            trt.int32,
+            name + "_cum_adv_index_shape_casted",
+        )
         cum_adv_index_shape = cum_adv_index.shape
         _LOGGER.debug(f"The shape for cumulative adv index is {cum_adv_index_shape}")
         # check if all advanced indices are consecutive
@@ -263,7 +270,7 @@ def index(
             adv_indx_count
             == adv_indx_indices[adv_indx_count - 1] - adv_indx_indices[0] + 1
         ):
-            _LOGGER.debug(f"The indices are continuous in this case")
+            _LOGGER.debug("The indices are continuous in this case")
             concat_tensor_reshape.append(
                 get_trt_tensor(ctx, -1, name + "_dynamic_concat")
             )
@@ -287,7 +294,7 @@ def index(
                 source_ir,
             )
             unfold_tensor = regular_index_shuffle_layer.get_output(0)
-            _LOGGER.debug(f"The tensor is unfolded now")
+            _LOGGER.debug("The tensor is unfolded now")
             _LOGGER.debug(f"The unfolded tensor shape is {unfold_tensor.shape}")
 
             # Transpose folded advanced indexed axis to its original location.
@@ -342,7 +349,7 @@ def index(
             reshape_output = unfold_advanced_shuffle_layer.get_output(0)
 
         else:
-            _LOGGER.debug(f"The indices are not continuous in this case")
+            _LOGGER.debug("The indices are not continuous in this case")
             concat_final_tensor = []
             concat_final_tensor.append(cum_adv_index_shape_tensor)
             for i in range(0, rank):
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/shape.py b/py/torch_tensorrt/dynamo/conversion/impl/shape.py
index ef30b186c1..7551d58059 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/shape.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/shape.py
@@ -8,11 +8,14 @@
 from torch.fx.node import Target
 from torch_tensorrt.dynamo._SourceIR import SourceIR
 from torch_tensorrt.dynamo.conversion._ConversionContext import ConversionContext
-from torch_tensorrt.dynamo.conversion.converter_utils import to_numpy
 from torch_tensorrt.dynamo.conversion.impl.elementwise.base import (
     convert_binary_elementwise,
 )
-from torch_tensorrt.fx.converters.converter_utils import set_layer_name
+from torch_tensorrt.fx.converters.converter_utils import (
+    Frameworks,
+    set_layer_name,
+    unified_dtype_converter,
+)
 from torch_tensorrt.fx.types import TRTTensor
 
 
@@ -48,16 +51,17 @@ def get_shape_with_dynamic_shape(
     """
     # Ger real shape info for input_val
     input_shape = ctx.net.add_shape(input_val).get_output(0)
-
+    # input_shape.dtype is int64 in TRT 10.0
+    input_np_dtype = unified_dtype_converter(input_shape.dtype, Frameworks.NUMPY)
     scale_layer = ctx.net.add_constant(
-        input_shape.shape, np.ascontiguousarray(shape, dtype=np.int32)
+        input_shape.shape, np.ascontiguousarray(shape, dtype=input_np_dtype)
     )
     set_layer_name(scale_layer, target, f"{name}_scale")
     scale_res = scale_layer.get_output(0)
 
     length = input_shape.shape[0]
     zero_layer = ctx.net.add_constant(
-        input_shape.shape, to_numpy(torch.zeros((length), dtype=torch.int32))
+        input_shape.shape, np.zeros(length, dtype=input_np_dtype)
     )
     set_layer_name(zero_layer, target, f"{name}_zeros")
 
diff --git a/py/torch_tensorrt/fx/converters/converter_utils.py b/py/torch_tensorrt/fx/converters/converter_utils.py
index 49bf401f58..510d4ef69b 100644
--- a/py/torch_tensorrt/fx/converters/converter_utils.py
+++ b/py/torch_tensorrt/fx/converters/converter_utils.py
@@ -1,8 +1,8 @@
 import operator
 import warnings
+from enum import Enum, auto
 from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
 
-from enum import Enum, auto
 import numpy as np
 
 # @manual=//deeplearning/trt/python:py_tensorrt
@@ -20,7 +20,7 @@
     TRTPluginFieldCollection,
     TRTTensor,
 )
-from ..utils import unified_dtype_converter, Frameworks
+from ..utils import Frameworks, unified_dtype_converter
 
 
 class SourceIR(Enum):
@@ -351,13 +351,17 @@ def prepend_ones(
     # compute the final shape.
     if has_dynamic_shape(tensor.shape):
         tensor_shape_layer = network.add_shape(tensor)
+        tensor_shape = tensor_shape_layer.get_output(0)
+        tensor_shape = type_cast(
+            network, "shape", name + "shape_casted", tensor_shape, trt.int32
+        )
         tensor_shape_layer.name = f"{name}_broadcast_orig_shape"
         prepend_shape_layer = network.add_constant(
             (num_prepend_ones,), np.ones((num_prepend_ones,), dtype=np.int32)
         )
         prepend_shape_layer.name = f"{name}_broadcast_prepend_ones"
         reshape_dim_layer = network.add_concatenation(
-            [prepend_shape_layer.get_output(0), tensor_shape_layer.get_output(0)]
+            [prepend_shape_layer.get_output(0), tensor_shape]
         )
         reshape_dim_layer.axis = 0
         reshape_dim_layer.name = f"{name}_broadcast_final_shape"
diff --git a/py/torch_tensorrt/fx/utils.py b/py/torch_tensorrt/fx/utils.py
index 9acc53ffc8..5bef21b6be 100644
--- a/py/torch_tensorrt/fx/utils.py
+++ b/py/torch_tensorrt/fx/utils.py
@@ -38,6 +38,11 @@ class Frameworks(Enum):
         Frameworks.TORCH: torch.int32,
         Frameworks.TRT: trt.int32,
     },
+    trt.int64: {
+        Frameworks.NUMPY: np.int64,
+        Frameworks.TORCH: torch.int64,
+        Frameworks.TRT: trt.int64,
+    },
     trt.float16: {
         Frameworks.NUMPY: np.float16,
         Frameworks.TORCH: torch.float16,
@@ -104,6 +109,8 @@ def unified_dtype_converter(
         return DataTypeEquivalence[trt.bool][to]
     elif dtype in (np.int32, torch.int32, trt.int32):
         return DataTypeEquivalence[trt.int32][to]
+    elif dtype in (np.int64, torch.int64, trt.int64):
+        return DataTypeEquivalence[trt.int64][to]
     elif dtype in (np.float16, torch.float16, trt.float16):
         return DataTypeEquivalence[trt.float16][to]
     elif dtype in (np.float32, torch.float32, trt.float32):
diff --git a/tests/py/dynamo/conversion/test_erf_aten.py b/tests/py/dynamo/conversion/test_erf_aten.py
index 3f52e436b4..d65788bc85 100644
--- a/tests/py/dynamo/conversion/test_erf_aten.py
+++ b/tests/py/dynamo/conversion/test_erf_aten.py
@@ -22,11 +22,7 @@ def forward(self, input):
                 return torch.ops.aten.erf.default(input)
 
         inputs = [torch.randn(x, dtype=type)]
-        self.run_test(
-            erf(),
-            inputs,
-            precision=type,
-        )
+        self.run_test(erf(), inputs, precision=type, output_dtypes=[type])
 
     @parameterized.expand(
         [
diff --git a/tests/py/dynamo/conversion/test_neg_aten.py b/tests/py/dynamo/conversion/test_neg_aten.py
index c49fc32c23..818d9c5a83 100644
--- a/tests/py/dynamo/conversion/test_neg_aten.py
+++ b/tests/py/dynamo/conversion/test_neg_aten.py
@@ -22,11 +22,7 @@ def forward(self, input):
                 return torch.ops.aten.neg.default(input)
 
         inputs = [torch.randn(x, dtype=type)]
-        self.run_test(
-            neg(),
-            inputs,
-            precision=type,
-        )
+        self.run_test(neg(), inputs, precision=type, output_dtypes=[type])
 
     @parameterized.expand(
         [

From 5431ee37dfe879a9bd2cdfbe3779227228dc630b Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 25 Mar 2024 09:54:01 -0700
Subject: [PATCH 013/122] chore: update trt version

---
 py/requirements.txt | 2 +-
 pyproject.toml      | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/py/requirements.txt b/py/requirements.txt
index 334f1e9c76..19c39c8647 100644
--- a/py/requirements.txt
+++ b/py/requirements.txt
@@ -5,5 +5,5 @@ pybind11==2.6.2
 torch==2.3.0
 torchvision==0.18.0
 --extra-index-url https://pypi.ngc.nvidia.com
-tensorrt==8.6.1
+tensorrt>=10.0
 pyyaml
diff --git a/pyproject.toml b/pyproject.toml
index 5c42700ef8..6c4940013d 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,7 +8,7 @@ requires = [
     "cffi>=1.15.1",
     "typing-extensions>=4.7.0",
     "future>=0.18.3",
-    "tensorrt>=8.6,<8.7",
+    "tensorrt>=10.0",
     "torch >=2.3.0.dev,<2.4.0",
     "pybind11==2.6.2",
     "numpy",
@@ -42,7 +42,7 @@ requires-python = ">=3.8"
 keywords = ["pytorch", "torch", "tensorrt", "trt", "ai", "artificial intelligence", "ml", "machine learning", "dl", "deep learning", "compiler", "dynamo", "torchscript", "inference"]
 dependencies = [
     "torch >=2.3.0.dev,<2.4.0",
-    "tensorrt>=8.6,<8.7",
+    "tensorrt>=10.0",
     "packaging>=23",
     "numpy",
     "typing-extensions>=4.7.0",

From 0c03de5ca11d7c77adf3ce8cbe609bd832eced4e Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 25 Mar 2024 18:51:39 -0700
Subject: [PATCH 014/122] chore: more updates

---
 core/conversion/converters/converter_util.cpp    |  9 +++++++--
 core/conversion/converters/converter_util.h      |  3 +++
 core/conversion/converters/impl/constant_pad.cpp |  9 +++------
 core/conversion/converters/impl/conv_deconv.cpp  |  2 +-
 core/conversion/converters/impl/cumsum.cpp       |  2 +-
 core/conversion/converters/impl/expand.cpp       |  9 ++++-----
 core/conversion/converters/impl/interpolate.cpp  |  2 +-
 core/conversion/converters/impl/linear.cpp       |  7 +++++--
 core/conversion/converters/impl/select.cpp       | 13 +++++--------
 9 files changed, 30 insertions(+), 26 deletions(-)

diff --git a/core/conversion/converters/converter_util.cpp b/core/conversion/converters/converter_util.cpp
index 3dcd2e9d80..39afe9945f 100644
--- a/core/conversion/converters/converter_util.cpp
+++ b/core/conversion/converters/converter_util.cpp
@@ -39,6 +39,12 @@ nvinfer1::ITensor* addPadding(
   }
 }
 
+nvinfer1::ITensor* getShapeOutput(ConversionCtx* ctx, nvinfer1::ITensor* input_tensor, const std::string& name) {
+  nvinfer1::ITensor* input_shape = ctx->net->addShape(*input_tensor)->getOutput(0);
+  input_shape = castITensor(ctx, input_shape, nvinfer1::DataType::kINT32, name);
+  return input_shape;
+}
+
 nvinfer1::ITensor* addUnpadding(
     ConversionCtx* ctx,
     const torch::jit::Node* n,
@@ -134,7 +140,7 @@ nvinfer1::ILayer* add_elementwise(
       }
       auto otherStaticShapeMask = tensor_to_const(ctx, thOtherStaticShapeMask);
       auto otherDynamicShapeMask = tensor_to_const(ctx, thOtherDynamicShapeMask);
-      auto selfShape = ctx->net->addShape(*self)->getOutput(0);
+      nvinfer1::ITensor* selfShape = getShapeOutput(ctx, self, std::string(name + "_shape_cast").c_str());
       // size of dynamic dimension of other need to the same as that of
       // corresponding dimension of self
       auto otherDynamicShape =
@@ -348,7 +354,6 @@ nvinfer1::ITensor* normalize_indices(
   auto neg_itensor = tensor_to_const(ctx, neg);
   // find the indices that = -1
   auto signs = clamp(ctx, indices, neg_itensor, zero_itensor, "clamp layer for " + name);
-
   // get the inputDim value where indices == -1, else 0
   auto mul = add_elementwise(ctx, nvinfer1::ElementWiseOperation::kPROD, signs, input_dim, "prod layer for " + name);
   TORCHTRT_CHECK(mul, "Unable to create mul layer in normalize_indices");
diff --git a/core/conversion/converters/converter_util.h b/core/conversion/converters/converter_util.h
index 3342302431..ad57c476e1 100644
--- a/core/conversion/converters/converter_util.h
+++ b/core/conversion/converters/converter_util.h
@@ -62,6 +62,9 @@ nvinfer1::ITensor* castITensor(
     nvinfer1::DataType dtype,
     const std::string& layer_name_prefix = "");
 
+// Get the shape of the input tensor and cast it to INT32 type
+nvinfer1::ITensor* getShapeOutput(ConversionCtx* ctx, nvinfer1::ITensor* input_tensor, const std::string& name = "");
+
 // Freeze an at::Tensor in a IConstant layer
 nvinfer1::ITensor* tensor_to_const(ConversionCtx* ctx, at::Tensor t, const std::string& name = std::string());
 
diff --git a/core/conversion/converters/impl/constant_pad.cpp b/core/conversion/converters/impl/constant_pad.cpp
index 20a091e730..42947e1c03 100644
--- a/core/conversion/converters/impl/constant_pad.cpp
+++ b/core/conversion/converters/impl/constant_pad.cpp
@@ -60,13 +60,10 @@ auto constant_pad_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns
 
        if (ctx->input_is_dynamic) {
          // build the size using inetwork layers
-         auto shape_layer = ctx->net->addShape(*in);
-         TORCHTRT_CHECK(shape_layer, "Unable to create shape layer from node: " << *n);
-         shape_layer->setName((util::node_info(n) + "_shape").c_str());
          auto total_padding_itensor = tensor_to_const(ctx, torch::tensor(total_padding, torch::kInt32));
-
-         auto add_layer = ctx->net->addElementWise(
-             *shape_layer->getOutput(0), *total_padding_itensor, nvinfer1::ElementWiseOperation::kSUM);
+         nvinfer1::ITensor* shapeOutput = getShapeOutput(ctx, in, (util::node_info(n) + "_shape").c_str());
+         auto add_layer =
+             ctx->net->addElementWise(*shapeOutput, *total_padding_itensor, nvinfer1::ElementWiseOperation::kSUM);
          TORCHTRT_CHECK(add_layer, "Unable to create add layer from node: " << *n);
          add_layer->setName((util::node_info(n) + "_add").c_str());
          slice_layer->setInput(2, *add_layer->getOutput(0));
diff --git a/core/conversion/converters/impl/conv_deconv.cpp b/core/conversion/converters/impl/conv_deconv.cpp
index bf0df00c64..aa7acc9cc4 100644
--- a/core/conversion/converters/impl/conv_deconv.cpp
+++ b/core/conversion/converters/impl/conv_deconv.cpp
@@ -33,7 +33,7 @@ nvinfer1::ILayer* add_bias_layer(
     nvinfer1::Dims& input_dims,
     nvinfer1::Dims& output_padding,
     Weights& bias) {
-  nvinfer1::ITensor* input_shape = ctx->net->addShape(*input_tensor)->getOutput(0);
+  nvinfer1::ITensor* input_shape = getShapeOutput(ctx, input_tensor, std::string("bias_shape_cast").c_str());
   // Add padding layer
   nvinfer1::ITensor* start;
   nvinfer1::ITensor* totalPadding;
diff --git a/core/conversion/converters/impl/cumsum.cpp b/core/conversion/converters/impl/cumsum.cpp
index 5c518fd635..f856ca5d4e 100644
--- a/core/conversion/converters/impl/cumsum.cpp
+++ b/core/conversion/converters/impl/cumsum.cpp
@@ -36,7 +36,7 @@ auto cumsum_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns().pat
          torch::Tensor axis = torch::tensor(input_dims.d[dim], torch::kInt32);
          tripLimit = tensor_to_const(ctx, axis);
        } else {
-         nvinfer1::ITensor* inpShape = ctx->net->addShape(*in)->getOutput(0);
+         nvinfer1::ITensor* inpShape = getShapeOutput(ctx, in);
          torch::Tensor dimValue = torch::tensor(dim, torch::kInt32);
          nvinfer1::ITensor* axis = tensor_to_const(ctx, dimValue);
          tripLimit = ctx->net->addGather(*inpShape, *axis, 0)->getOutput(0);
diff --git a/core/conversion/converters/impl/expand.cpp b/core/conversion/converters/impl/expand.cpp
index 6b22fea8d4..0e68768e15 100644
--- a/core/conversion/converters/impl/expand.cpp
+++ b/core/conversion/converters/impl/expand.cpp
@@ -19,11 +19,11 @@ nvinfer1::ITensor* concat(int max_rank, int old_rank, ConversionCtx* ctx, nvinfe
   if (max_rank - old_rank > 0) {
     torch::Tensor thOne = torch::tensor(std::vector<int32_t>(max_rank - old_rank, 1), torch::kInt32);
     auto one_tensor = tensor_to_const(ctx, thOne);
-    auto in_shape_tensor = ctx->net->addShape(*tensor)->getOutput(0);
+    auto in_shape_tensor = getShapeOutput(ctx, tensor);
     nvinfer1::ITensor* const args[2] = {one_tensor, in_shape_tensor};
     return ctx->net->addConcatenation(args, 2)->getOutput(0);
   } else { // max_rank - old_rank == 0
-    return ctx->net->addShape(*tensor)->getOutput(0);
+    return getShapeOutput(ctx, tensor);
   }
 }
 
@@ -221,8 +221,7 @@ auto expand_registrations TORCHTRT_UNUSED =
                auto targetDims = targetTensor->getDimensions();
                LOG_DEBUG("(expand_as layer) Expand input from " << input_dims << " to " << targetDims);
                if (ctx->input_is_dynamic) {
-                 return add_expand_dynamic(
-                     ctx, n, in, ctx->net->addShape(*targetTensor)->getOutput(0), targetDims, false);
+                 return add_expand_dynamic(ctx, n, in, getShapeOutput(ctx, targetTensor), targetDims, false);
                } else {
                  return add_expand(ctx, n, in, targetDims);
                }
@@ -357,7 +356,7 @@ auto expand_registrations TORCHTRT_UNUSED =
                if (ctx->input_is_dynamic) {
                  auto start_tensor = tensor_to_const(ctx, torch::tensor(start_vec, torch::kInt32));
 
-                 auto expand_output_shape = ctx->net->addShape(*expand->getOutput(0))->getOutput(0);
+                 auto expand_output_shape = getShapeOutput(ctx, expand->getOutput(0));
                  std::vector<int64_t> repeat_const_vec(repeat_shape_dims.nbDims, 1);
                  repeat_const_vec[dim + 1] = repeats;
                  auto repeat_const = tensor_to_const(ctx, torch::tensor(repeat_const_vec, torch::kInt32));
diff --git a/core/conversion/converters/impl/interpolate.cpp b/core/conversion/converters/impl/interpolate.cpp
index 61721e3d2c..748e3c9e1a 100644
--- a/core/conversion/converters/impl/interpolate.cpp
+++ b/core/conversion/converters/impl/interpolate.cpp
@@ -91,7 +91,7 @@ void resize_layer_size(
 
     auto dynamic_shape_mask = tensor_to_const(ctx, th_dynamic_shape_mask);
     auto static_shape_mask = tensor_to_const(ctx, th_static_shape_mask);
-    auto input_shape = ctx->net->addShape(*in)->getOutput(0);
+    nvinfer1::ITensor* input_shape = getShapeOutput(ctx, in);
     auto dynamic_shape =
         ctx->net->addElementWise(*input_shape, *dynamic_shape_mask, nvinfer1::ElementWiseOperation::kPROD)
             ->getOutput(0);
diff --git a/core/conversion/converters/impl/linear.cpp b/core/conversion/converters/impl/linear.cpp
index 39f9cb055d..0e4452dec0 100644
--- a/core/conversion/converters/impl/linear.cpp
+++ b/core/conversion/converters/impl/linear.cpp
@@ -40,11 +40,14 @@ auto linear_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns().pat
          in = in_shuffle->getOutput(0);
        }
 
-       // Convert w_tensor to ITensor
+       // Convert w_tensor to ITensor and broadcast 2d to 4d if needed
        auto weight = args[1].IValue()->toTensor();
        auto weight_tensor = tensor_to_const(ctx, weight, util::node_info(n) + "_weight");
+       auto weight_shape = util::toVec(weight_tensor->getDimensions());
+       weight_tensor = addPadding(ctx, n, weight_tensor, in->getDimensions().nbDims, false, false);
+
        auto mm_layer = ctx->net->addMatrixMultiply(
-           *in, nvinfer1::MatrixOperation::kNONE, *weight_tensor, nvinfer1::MatrixOperation::kNONE);
+           *in, nvinfer1::MatrixOperation::kNONE, *weight_tensor, nvinfer1::MatrixOperation::kTRANSPOSE);
 
        TORCHTRT_CHECK(mm_layer, "Unable to create linear layer from node: " << *n);
        mm_layer->setName(util::node_info(n).c_str());
diff --git a/core/conversion/converters/impl/select.cpp b/core/conversion/converters/impl/select.cpp
index 8334205879..d6b49aa609 100644
--- a/core/conversion/converters/impl/select.cpp
+++ b/core/conversion/converters/impl/select.cpp
@@ -368,8 +368,7 @@ auto select_registrations TORCHTRT_UNUSED =
                  int rank = inDims.nbDims;
                  LOG_WARNING("If indices include negative values, the exported graph will produce incorrect results.");
                  int adv_idx_count = adv_idx_indices.size();
-                 auto in_shape_itensor = ctx->net->addShape(*in)->getOutput(0);
-
+                 nvinfer1::ITensor* in_shape_itensor = getShapeOutput(ctx, in);
                  std::vector<nvinfer1::ITensor*> dim_tensor_list;
                  for (int i = 0; i < rank; i++) {
                    auto dim_tensor =
@@ -401,7 +400,7 @@ auto select_registrations TORCHTRT_UNUSED =
                  //  t: [x_1, x_2, ..., x_m, y_1, y_2, ..., y_n] -> t: [x_1*x_2* ...*x_m, y_1*y_2* ...*y_n]
                  nvinfer1::ITensor* flatten_tensor = NULL;
                  {
-                   auto shuffle_shape_tensor = ctx->net->addShape(*shuffle_out)->getOutput(0);
+                   nvinfer1::ITensor* shuffle_shape_tensor = getShapeOutput(ctx, shuffle_out);
                    auto d0 = tensor_to_const(ctx, torch::tensor({1}, torch::kInt32));
                    for (int i = 0; i < adv_idx_count; i++) {
                      auto dim_tensor =
@@ -479,7 +478,7 @@ auto select_registrations TORCHTRT_UNUSED =
 
                  nvinfer1::ITensor* reshape_output = NULL;
                  {
-                   auto cum_adv_index_shape_tensor = ctx->net->addShape(*cum_adv_index)->getOutput(0);
+                   nvinfer1::ITensor* cum_adv_index_shape_tensor = getShapeOutput(ctx, cum_adv_index);
                    // check if all advanced indices are consecutive.
                    if (adv_idx_count == (adv_idx_indices[adv_idx_count - 1] - adv_idx_indices[0] + 1)) {
                      // unfold regular index axes
@@ -559,8 +558,7 @@ auto select_registrations TORCHTRT_UNUSED =
                bool dynamic_shape = ctx->input_is_dynamic;
                auto input_dim = in->getDimensions();
                // add Shape Tensor
-               auto ishape_layer = ctx->net->addShape(*in);
-               auto ishape_tensor = ishape_layer->getOutput(0); // input shape
+               nvinfer1::ITensor* ishape_tensor = getShapeOutput(ctx, in);
                std::string node_name = n->outputs()[0]->debugName().c_str();
 
                int startIdx = 0;
@@ -605,6 +603,7 @@ auto select_registrations TORCHTRT_UNUSED =
                    stride_.d[i] = 1;
                  }
                }
+
                if (!dynamic_shape) {
                  auto slice_layer = ctx->net->addSlice(*in, start_, size_, stride_);
                  LOG_DEBUG("start_:" << start_);
@@ -617,7 +616,6 @@ auto select_registrations TORCHTRT_UNUSED =
                  LOG_DEBUG("Using dynamic version of slice");
                  // start tensor
                  at::Tensor start_tensor = torch::zeros({nbdims}).to(torch::kI32);
-                 ;
                  start_tensor[axis] = startIdx;
                  auto start_itensor = tensor_to_const(ctx, start_tensor);
 
@@ -647,7 +645,6 @@ auto select_registrations TORCHTRT_UNUSED =
 
                  // calculate size
                  auto size_itensor = get_slice_size(ctx, out_start, out_end, stride_itensor, nbdims, node_name);
-
                  // update slice layer
                  auto slice_layer = ctx->net->addSlice(*in, start_, size_, stride_);
                  slice_layer->setInput(1, *out_start); // start

From 982dbd25b3ffd2f4edbf5bd8c2fc321f2a35ab56 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 25 Mar 2024 11:57:39 -0700
Subject: [PATCH 015/122] parent f39e89e3964bc3d6ea3a6989b1e4099e1bb3e6dd
 author Dheeraj Peri <peri.dheeraj@gmail.com> 1711393059 -0700 committer
 Dheeraj Peri <peri.dheeraj@gmail.com> 1711393072 -0700

chore: minor updates

chore: Fix save failures

chore: minor fixes

chore: remove duplicate bert test case

chore: remove comments

chore: add load api

chore: minor updates

chore: minor updates

chore: minor updates

chore: more updates
---
 core/runtime/TRTEngine.cpp                    |   2 +-
 docsrc/user_guide/saving_models.rst           |  71 +++++----
 py/torch_tensorrt/_compile.py                 | 111 +++++++++++++-
 py/torch_tensorrt/dynamo/_compiler.py         |   9 +-
 py/torch_tensorrt/dynamo/_defaults.py         |   1 -
 py/torch_tensorrt/dynamo/_exporter.py         | 142 +++++++++++-------
 py/torch_tensorrt/dynamo/_settings.py         |   3 -
 .../lowering/test_aten_lowering_passes.py     |   4 +-
 tests/py/dynamo/models/test_export_serde.py   | 104 ++++++++-----
 tests/py/dynamo/models/test_models_export.py  |  63 +-------
 tests/py/dynamo/models/test_output_format.py  |  62 --------
 11 files changed, 311 insertions(+), 261 deletions(-)
 delete mode 100644 tests/py/dynamo/models/test_output_format.py

diff --git a/core/runtime/TRTEngine.cpp b/core/runtime/TRTEngine.cpp
index 92e5d7a8ff..7a046f6d94 100644
--- a/core/runtime/TRTEngine.cpp
+++ b/core/runtime/TRTEngine.cpp
@@ -241,7 +241,7 @@ std::string TRTEngine::to_str() const {
               exec_ctx->getEngine().getTensorDataType(out_binding_names[o].c_str()))
        << std::endl;
   }
-  ss << "  }" << std::endl;
+  ss << "  ]" << std::endl;
   ss << "  Device: " << device_info << std::endl;
   ss << "  Hardware Compatibility: " << (hardware_compatible ? "Enabled" : "Disabled") << std::endl;
   // clang-format on
diff --git a/docsrc/user_guide/saving_models.rst b/docsrc/user_guide/saving_models.rst
index 8379b44f0f..73fee6e23c 100644
--- a/docsrc/user_guide/saving_models.rst
+++ b/docsrc/user_guide/saving_models.rst
@@ -9,23 +9,22 @@ Saving models compiled with Torch-TensorRT
    :undoc-members:
    :show-inheritance:
 
-Saving models compiled with Torch-TensorRT varies slightly with the `ir` that has been used for compilation.
+Saving models compiled with Torch-TensorRT can be done using `torch_tensorrt.save` API.
 
 Dynamo IR
 -------------
 
-The output type of `ir=dynamo` compilation of Torch-TensorRT is `torch.export.ExportedProgram` object by default. 
-In addition, we provide a new parameter `output_format` in the `CompilationSetting` object provided before compilation.
-The `output_format` can take the following options 
+The output type of `ir=dynamo` compilation of Torch-TensorRT is `torch.fx.GraphModule` object by default. 
+We can save this object in either `TorchScript` (`torch.jit.ScriptModule`) or `ExportedProgram` (`torch.export.ExportedProgram`) formats by 
+specifying the `output_format` flag. Here are the options `output_format` will accept
 
-* `exported_program` (or) `ep` : This is the default. Returns an ExportedProgram 
-* `torchscript` (or) `ts` : This returns a TorchScript module
-* `graph_module` (or) `fx` : This returns a torch.fx.GraphModule which can be traced into Torchscript to save to disk.
+* `exported_program` : This is the default. We perform transformations on the graphmodule first and use `torch.export.save` to save the module.
+* `torchscript` : We trace the graphmodule via `torch.jit.trace` and save it via `torch.jit.save`.
 
-a) Torchscript
+a) ExportedProgram
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-If you set the `output_format="torchscript"`, this will return a `ScriptModule` which can be serialized via torch.jit.save
+Here's an example usage
 
 .. code-block:: python
 
@@ -34,19 +33,17 @@ If you set the `output_format="torchscript"`, this will return a `ScriptModule`
 
     model = MyModel().eval().cuda()
     inputs = [torch.randn((1, 3, 224, 224)).cuda()]
-    # trt_ts is a torch.jit.ScriptModule object
-    trt_ts = torch_tensorrt.compile(model, ir="dynamo", inputs, output_format="torchscript")
-    torch.jit.save(trt_ts, "trt_model.ts")
+    # trt_ep is a torch.fx.GraphModule object
+    trt_gm = torch_tensorrt.compile(model, ir="dynamo", inputs) 
+    torchtrt.save(trt_gm, "trt.ep", inputs=inputs)
 
     # Later, you can load it and run inference
-    model = torch.jit.load("trt_model.ts").cuda()
+    model = torch.export.load("trt.ep").module()
     model(*inputs)
 
-b) ExportedProgram
+b) Torchscript
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-`torch.export.ExportedProgram`, a new format introduced in Pytorch 2.X is the default return type of Torch-TensorRT compilation.
-
 .. code-block:: python
 
     import torch
@@ -54,30 +51,14 @@ b) ExportedProgram
 
     model = MyModel().eval().cuda()
     inputs = [torch.randn((1, 3, 224, 224)).cuda()]
-    # trt_ep is a torch.export.ExportedProgram object
-    trt_ep = torch_tensorrt.compile(model, ir="dynamo", inputs) 
-    torch.export.save(trt_ep, "trt_model.ep")
+    # trt_gm is a torch.fx.GraphModule object
+    trt_gm = torch_tensorrt.compile(model, ir="dynamo", inputs)
+    torch_tensorrt.save(trt_gm, "trt.ts", output_format="torchscript", inputs=inputs)
 
     # Later, you can load it and run inference
-    model = torch.export.load("trt_model.ep")
+    model = torch.jit.load("trt.ts").cuda()
     model(*inputs)
 
-c) GraphModule
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-We can also return a `torch.fx.GraphModule` object as the output of Torch-TensorRT compilation by setting `output_format="graph_module"`.
-Internally, partitioning, lowering, conversion phases operate using GraphModule objects. These can be either traced into a Torchscript modules or 
-exported into `ExportedProgram` objects
-
-.. code-block:: python
-
-    import torch
-    import torch_tensorrt
-
-    model = MyModel().eval().cuda()
-    inputs = [torch.randn((1, 3, 224, 224)).cuda()]
-    # trt_gm is a torch.fx.GraphModule object
-    trt_gm = torch_tensorrt.compile(model, ir="dynamo", inputs, output_format="graph_module") 
 
 Torchscript IR
 -------------
@@ -99,3 +80,21 @@ For `ir=ts`, this behavior stays the same in 2.X versions as well.
   model = torch.jit.load("trt_model.ts").cuda()
   model(*inputs)
 
+
+Loading the models
+--------------------
+
+We can load torchscript or exported_program models using `torch.jit.load` and `torch.export.load` APIs from PyTorch directly.
+Alternatively, we provide a light wrapper `torch_tensorrt.load(file_path)` which can load either of the above model types.
+
+Here's an example usage
+
+.. code-block:: python
+
+    import torch
+    import torch_tensorrt
+
+    # file_path can be trt.ep or trt.ts file obtained via saving the model (refer to the above section)
+    inputs = [torch.randn((1, 3, 224, 224)).cuda()]
+    model = torch_tensorrt.load(<file_path>).module()
+    model(*inputs)
\ No newline at end of file
diff --git a/py/torch_tensorrt/_compile.py b/py/torch_tensorrt/_compile.py
index 9dd816e633..7acf83124a 100644
--- a/py/torch_tensorrt/_compile.py
+++ b/py/torch_tensorrt/_compile.py
@@ -6,6 +6,7 @@
 
 import torch
 import torch.fx
+import torch_tensorrt.dynamo
 import torch_tensorrt.ts
 from torch_tensorrt._enums import dtype
 from torch_tensorrt._Input import Input
@@ -26,10 +27,7 @@
 
 logger = logging.getLogger(__name__)
 
-__all__ = [
-    "compile",
-    "convert_method_to_trt_engine",
-]
+__all__ = ["compile", "convert_method_to_trt_engine", "save", "load"]
 
 
 def _non_fx_input_interface(
@@ -332,3 +330,108 @@ def convert_method_to_trt_engine(
         )
     else:
         raise RuntimeError("Module is an unknown format or the ir requested is unknown")
+
+
+def load(file_path: str = "") -> Any:
+    """
+    Load either a Torchscript model or ExportedProgram. Autodetect the type using
+    try, except
+    """
+    try:
+        logger.debug("Loading the provided file using torch.jit.load()")
+        ts_module = torch.jit.load(file_path)
+        return ts_module
+    except Exception:
+        logger.debug(
+            "Loading the provided file via torch.jit.load() failed with the following error",
+            exc_info=True,
+        )
+        pass
+
+    try:
+        logger.debug("Loading the provided file using torch.export.load()")
+        exp_program = torch.export.load(file_path)
+        return exp_program
+    except Exception:
+        logger.debug(
+            "Loading the provided file via torch.export.load() failed with the following error",
+            exc_info=True,
+        )
+        raise ValueError(
+            "The file doesn't correspond to a valid Torchscript module or ExportedProgram. Please verify the file path."
+        )
+
+
+def save(
+    module: Any,
+    file_path: str = "",
+    *,
+    output_format: str = "exported_program",
+    inputs: Optional[Sequence[torch.Tensor]] = None,
+    retrace: bool = False,
+) -> None:
+    """
+    Save the model to disk in the specified output format.
+    Arguments:
+        module : Compiled Torch-TensorRT module (Options include torch.jit.ScriptModule | torch.export.ExportedProgram | torch.fx.GraphModule)
+        inputs (torch.Tensor): Torch input tensors
+        output_format: Format to save the model. Options include exported_program | torchscript.
+        retrace: When the module type is a fx.GraphModule, this option re-exports the graph using torch.export.export(strict=False) to save it.
+                This flag is experimental for now.
+    """
+    module_type = _parse_module_type(module)
+    accepted_formats = {"exported_program", "torchscript"}
+    if inputs is not None and not all(
+        isinstance(input, torch.Tensor) for input in inputs
+    ):
+        raise ValueError(
+            "Not all inputs provided are torch.tensors. Please provide torch.tensors as inputs"
+        )
+    if output_format not in accepted_formats:
+        raise ValueError(
+            f"Provided output_format {output_format} is not supported. Supported options are exported_program | torchscript"
+        )
+    if not file_path:
+        raise ValueError("File path cannot be empty. Please provide a valid file path")
+
+    if module_type == _ModuleType.nn:
+        raise ValueError(
+            "Input model is of type nn.Module. Saving nn.Module directly is not supported. Supported model types torch.jit.ScriptModule | torch.fx.GraphModule | torch.export.ExportedProgram."
+        )
+    elif module_type == _ModuleType.ts:
+        if output_format == "exported_program":
+            raise ValueError(
+                "Provided model is a torch.jit.ScriptModule but the output_format specified is exported_program. Please verify the output_format"
+            )
+        else:
+            torch.jit.save(module, file_path)
+    elif module_type == _ModuleType.ep:
+        if output_format == "torchscript":
+            raise ValueError(
+                "Provided model is a torch.export.ExportedProgram but the output_format specified is torchscript. Please verify the output_format"
+            )
+        else:
+            torch.export.save(module, file_path)
+    elif module_type == _ModuleType.fx:
+        if inputs is None:
+            raise ValueError(
+                "Provided model is a torch.fx.GraphModule however the inputs are empty. Please provide valid torch.tensors as inputs to trace and save the model"
+            )
+        # The module type is torch.fx.GraphModule
+        if output_format == "torchscript":
+            module_ts = torch.jit.trace(module, inputs)
+            torch.jit.save(module_ts, file_path)
+        else:
+            if not retrace:
+                from torch_tensorrt.dynamo._exporter import export
+
+                exp_program = export(module, inputs)
+                torch.export.save(exp_program, file_path)
+            else:
+                from torch._higher_order_ops.torchbind import enable_torchbind_tracing
+
+                with enable_torchbind_tracing():
+                    exp_program = torch.export.export(
+                        module, tuple(inputs), strict=False
+                    )
+                    torch.export.save(exp_program, file_path)
diff --git a/py/torch_tensorrt/dynamo/_compiler.py b/py/torch_tensorrt/dynamo/_compiler.py
index 6312532f1c..b321eabcb2 100644
--- a/py/torch_tensorrt/dynamo/_compiler.py
+++ b/py/torch_tensorrt/dynamo/_compiler.py
@@ -30,7 +30,6 @@
     MIN_BLOCK_SIZE,
     NUM_AVG_TIMING_ITERS,
     OPTIMIZATION_LEVEL,
-    OUTPUT_FORMAT,
     PASS_THROUGH_BUILD_FAILURES,
     PRECISION,
     REFIT,
@@ -48,7 +47,6 @@
     dryrun_stats_display,
     parse_non_trt_nodes,
 )
-from torch_tensorrt.dynamo._exporter import export
 from torch_tensorrt.dynamo.conversion import (
     CompilationSettings,
     UnsupportedOperatorException,
@@ -102,9 +100,8 @@ def compile(
     enable_experimental_decompositions: bool = ENABLE_EXPERIMENTAL_DECOMPOSITIONS,
     dryrun: bool = DRYRUN,
     hardware_compatible: bool = HARDWARE_COMPATIBLE,
-    output_format: str = OUTPUT_FORMAT,
     **kwargs: Any,
-) -> Union[ExportedProgram, torch.jit.ScriptModule, torch.fx.GraphModule]:
+) -> torch.fx.GraphModule:
     """Compile a TorchScript module for NVIDIA GPUs using TensorRT
 
     Takes a existing TorchScript module and a set of settings to configure the compiler
@@ -246,14 +243,12 @@ def compile(
         "dla_global_dram_size": dla_global_dram_size,
         "dryrun": dryrun,
         "hardware_compatible": hardware_compatible,
-        "output_format": output_format,
     }
 
     settings = CompilationSettings(**compilation_options)
     logger.info("Compilation Settings: %s\n", settings)
     trt_gm = compile_module(gm, inputs, settings)
-    trt_result = export(trt_gm, torch_inputs, output_format)
-    return trt_result
+    return trt_gm
 
 
 def compile_module(
diff --git a/py/torch_tensorrt/dynamo/_defaults.py b/py/torch_tensorrt/dynamo/_defaults.py
index ec038c0dba..3d48ab3def 100644
--- a/py/torch_tensorrt/dynamo/_defaults.py
+++ b/py/torch_tensorrt/dynamo/_defaults.py
@@ -26,7 +26,6 @@
 REQUIRE_FULL_COMPILATION = False
 DRYRUN = False
 HARDWARE_COMPATIBLE = False
-OUTPUT_FORMAT = "exported_program"
 
 
 def default_device() -> Device:
diff --git a/py/torch_tensorrt/dynamo/_exporter.py b/py/torch_tensorrt/dynamo/_exporter.py
index c7e2f37795..e9d166a1cc 100644
--- a/py/torch_tensorrt/dynamo/_exporter.py
+++ b/py/torch_tensorrt/dynamo/_exporter.py
@@ -1,3 +1,4 @@
+import copy
 import operator
 from typing import Any, Dict, Sequence, Tuple, cast
 
@@ -6,8 +7,11 @@
 from torch._subclasses.fake_tensor import FakeTensor
 from torch.export import ExportedProgram, ExportGraphSignature
 from torch.export.exported_program import (
+    CustomObjArgument,
     InputKind,
     InputSpec,
+    ModuleCallEntry,
+    ModuleCallSignature,
     OutputKind,
     OutputSpec,
     TensorArgument,
@@ -18,27 +22,16 @@
 def export(
     gm: torch.fx.GraphModule,
     inputs: Sequence[torch.Tensor],
-    output_format: str,
 ) -> ExportedProgram:
     """Export the result of TensorRT compilation into the desired output format.
 
     Arguments:
         gm (torch.fx.GraphModule): Compiled Torch-TensorRT module, generated by ``torch_tensorrt.dynamo.compile``
         inputs (torch.Tensor): Torch input tensors
-        output_format (str): Output format of the result of TRT compilation. Options include "exported_program" (or) "ep" | "torchscript" (or) "ts" | "graph_module" (or) "fx". Default is "exported_program"
     """
-    if output_format == "torchscript" or output_format == "ts":
-        return torch.jit.trace(gm, inputs)
-    elif output_format == "exported_program" or output_format == "ep":
-        patched_module = transform(gm, inputs)
-        exp_program = create_trt_exp_program(patched_module)
-        return exp_program
-    elif output_format == "graph_module" or output_format == "fx":
-        return gm
-    else:
-        raise ValueError(
-            f"Invalid output format {output_format} specified. Supported options include exported_program (or) ep | torchscript (or) ts | graph_module (or) fx"
-        )
+    patched_module = transform(gm, inputs)
+    exp_program = create_trt_exp_program(patched_module)
+    return exp_program
 
 
 def transform(
@@ -55,6 +48,10 @@ def transform(
 
     Returns an inlined torch.fx.GraphModule
     """
+    # Make a copy the graph since this function transforms the input graph and changes it's attributes.
+    # This transformed graph is meant to be consumed by `create_trt_exp_program`
+    gm = copy.deepcopy(gm)
+
     # Run shape analysis
     _, outputs_map = partitioning.run_shape_analysis(gm, inputs)
 
@@ -72,7 +69,9 @@ def transform(
     return gm
 
 
-def lift(gm: torch.fx.GraphModule, graph_signature: Any) -> torch.fx.GraphModule:
+def lift(
+    gm: torch.fx.GraphModule, graph_signature: Any
+) -> Tuple[torch.fx.GraphModule, ExportGraphSignature, Dict[str, Any], Dict[str, Any]]:
     """
     Given an unlifted fx.GraphModule, lift all parameters, buffers into placeholders.
     Arguments:
@@ -86,6 +85,7 @@ def lift(gm: torch.fx.GraphModule, graph_signature: Any) -> torch.fx.GraphModule
     # exp_program.state_dict contains parameters and buffers whereas a graph_module's state_dict
     # has all parameters registered as torch.tensors.
     state_dict = gm.state_dict()
+    constants = {}
 
     fake_mode = detect_fake_mode(
         tuple(node.meta["val"] for node in gm.graph.nodes if node.op == "placeholder")
@@ -100,52 +100,69 @@ def lift(gm: torch.fx.GraphModule, graph_signature: Any) -> torch.fx.GraphModule
             break
 
     # At first the user_inputs are only present in the graph_signature.input_specs and hence non_user_input_idx=0
-    # The input_specs should be of the form [params, buffers, constant_tensors, user_inputs]
+    # The input_specs should be of the form [params, buffers, constant_tensors, custom_obj, user_inputs]
     non_user_input_idx = 0
     for node in gm.graph.nodes:
         if node.op == "get_attr":
-            if node.target not in state_dict:
-                raise ValueError(
-                    f"The get_attr node : {node.name} with target: {node.target} value could not be found in state_dict. Please check the input exported_program's graphmodule parameters."
-                )
 
-            constant_tensor = state_dict[node.target]
-            input_kind = InputKind.CONSTANT_TENSOR
+            lift_val = None
+            input_kind = None
 
-            # state_dict has these parameters/buffers as torch.Tensors. We override them as torch.nn.Parameter/torch.Tensors respectively.
-            for name, _ in gm.named_parameters():
-                if node.target == name:
-                    input_kind = InputKind.PARAMETER
-                    state_dict[name] = torch.nn.Parameter(state_dict[name])
-                    break
-            for name, _ in gm.named_buffers():
-                if node.target == name:
-                    input_kind = InputKind.BUFFER
-                    break
+            if node.target not in state_dict:
+                constants[node.target] = getattr(gm, node.target)
+                input_kind = InputKind.CUSTOM_OBJ
+                lift_val = constants[node.target]
+            else:
+                lift_val = state_dict[node.target]
+
+                input_kind = InputKind.CONSTANT_TENSOR
+
+                # state_dict has these parameters/buffers as torch.Tensors. We override them as torch.nn.Parameter/torch.Tensors respectively.
+                for name, _ in gm.named_parameters():
+                    if node.target == name:
+                        input_kind = InputKind.PARAMETER
+                        state_dict[name] = torch.nn.Parameter(state_dict[name])
+                        break
+                for name, _ in gm.named_buffers():
+                    if node.target == name:
+                        input_kind = InputKind.BUFFER
+                        break
+
+            assert lift_val is not None and input_kind is not None
 
             # Replace get_attr nodes with placeholder nodes and copy metadata.
             with gm.graph.inserting_before(first_user_input):
-                const_placeholder_node = gm.graph.placeholder(node.target)
+                # Ensure name doesn't contain period as it is used for submodules
+                const_placeholder_node = gm.graph.placeholder(
+                    node.target.replace(".", "_")
+                )
                 # Copy the node meta into this new placeholder node
                 const_placeholder_node.meta = node.meta
-                const_placeholder_node.meta["val"] = cast(
-                    FakeTensor,
-                    torch.empty_strided(
-                        tuple(constant_tensor.shape),
-                        tuple([1] * len(constant_tensor.shape)),
-                    ),
-                )
+
+                if isinstance(lift_val, torch.Tensor):
+                    const_placeholder_node.meta["val"] = cast(
+                        FakeTensor,
+                        torch.empty_strided(
+                            tuple(lift_val.shape),
+                            tuple([1] * len(lift_val.shape)),
+                        ),
+                    )
 
                 node.replace_all_uses_with(const_placeholder_node)
                 gm.graph.erase_node(node)
 
                 # Add these parameters/buffers/constants to the existing graph signature
                 # before user inputs. These specs are looked up in the state_dict during ExportedProgram creation.
+                input_spec_arg = TensorArgument(name=const_placeholder_node.name)
+                if input_kind == InputKind.CUSTOM_OBJ:
+                    input_spec_arg = CustomObjArgument(
+                        name=const_placeholder_node.name, class_fqn=""
+                    )
                 graph_signature.input_specs.insert(
                     non_user_input_idx,
                     InputSpec(
                         kind=input_kind,
-                        arg=TensorArgument(name=const_placeholder_node.name),
+                        arg=input_spec_arg,
                         target=node.target,
                     ),
                 )
@@ -154,7 +171,7 @@ def lift(gm: torch.fx.GraphModule, graph_signature: Any) -> torch.fx.GraphModule
     gm.graph.eliminate_dead_code()
     gm.graph.lint()
 
-    return gm, graph_signature, state_dict
+    return gm, graph_signature, state_dict, constants
 
 
 def get_duplicate_nodes(
@@ -292,18 +309,30 @@ def create_trt_exp_program(
         input_specs=input_specs, output_specs=output_specs
     )
 
+    module_call_graph = [
+        ModuleCallEntry(
+            "",
+            ModuleCallSignature(
+                inputs=[],
+                outputs=[],
+                in_spec=gm.graph._codegen.pytree_info.in_spec,
+                out_spec=gm.graph._codegen.pytree_info.out_spec,
+            ),
+        )
+    ]
+
     # Lift parameters/buffers/constants in the graph
     # torch.export serialization expects them to be lifted
-    gm, trt_graph_signature, state_dict = lift(gm, trt_graph_signature)
+    gm, trt_graph_signature, state_dict, constants = lift(gm, trt_graph_signature)
 
     trt_exp_program = ExportedProgram(
-        gm,
-        gm.graph,
-        trt_graph_signature,
-        state_dict,
-        {},
-        [],
-        [],
+        root=gm,
+        graph=gm.graph,
+        graph_signature=trt_graph_signature,
+        state_dict=state_dict,
+        range_constraints={},
+        module_call_graph=module_call_graph,
+        constants=constants,
     )
 
     return trt_exp_program
@@ -330,9 +359,13 @@ def inline_trt_modules(
         num_outputs = len(outputs_map[trt_module_node.name])
         # Insert a call_function node to perform inference on TRT engine
         with gm.graph.inserting_before(trt_module_node):
+            engine_name = f"{name}_engine"
+            setattr(gm, engine_name, trt_module.engine)
+            engine_node = gm.graph.get_attr(engine_name)
+
             trt_node = gm.graph.call_function(
                 torch.ops.tensorrt.execute_engine.default,
-                (trt_module_node.args, trt_module.engine),
+                (trt_module_node.args, engine_node),
             )
             trt_node.meta["val"] = []
             assert num_outputs > 0
@@ -348,6 +381,13 @@ def inline_trt_modules(
                     )
                 )
 
+            # meta["val"] should be a lighter version of a tensor. For eg: it should be a FakeTensor (with output shape and dtype properties)
+            # Lighter version of a custom_obj is not defined clearly. meta["val"] does not have any type expectations but
+            # for custom object nodes, it should be CustomObjArgument
+            engine_node.meta["val"] = CustomObjArgument(
+                name=engine_node.name, class_fqn=""
+            )
+
         if num_outputs == 1:
             # Insert getitem nodes as outputs (for export serialization to work)
             with gm.graph.inserting_after(trt_node):
diff --git a/py/torch_tensorrt/dynamo/_settings.py b/py/torch_tensorrt/dynamo/_settings.py
index c00b049f45..2420a227d8 100644
--- a/py/torch_tensorrt/dynamo/_settings.py
+++ b/py/torch_tensorrt/dynamo/_settings.py
@@ -19,7 +19,6 @@
     MIN_BLOCK_SIZE,
     NUM_AVG_TIMING_ITERS,
     OPTIMIZATION_LEVEL,
-    OUTPUT_FORMAT,
     PASS_THROUGH_BUILD_FAILURES,
     PRECISION,
     REFIT,
@@ -71,7 +70,6 @@ class CompilationSettings:
             TRT Engines. Prints detailed logs of the graph structure and nature of partitioning. Optionally saves the
             ouptut to a file if a string path is specified
         hardware_compatible (bool): Build the TensorRT engines compatible with GPU architectures other than that of the GPU on which the engine was built (currently works for NVIDIA Ampere and newer)
-        output_format (str): Output format of the result of TRT compilation. Options include "exported_program" (or) "ep" | "torchscript" (or) "ts" | "graph_module" (or) "fx". Default is "exported_program"
     """
 
     precision: torch.dtype = PRECISION
@@ -99,4 +97,3 @@ class CompilationSettings:
     dla_global_dram_size: int = DLA_GLOBAL_DRAM_SIZE
     dryrun: Union[bool, str] = DRYRUN
     hardware_compatible: bool = HARDWARE_COMPATIBLE
-    output_format: str = OUTPUT_FORMAT
diff --git a/tests/py/dynamo/lowering/test_aten_lowering_passes.py b/tests/py/dynamo/lowering/test_aten_lowering_passes.py
index bc75a8aa3d..b7c895ec11 100644
--- a/tests/py/dynamo/lowering/test_aten_lowering_passes.py
+++ b/tests/py/dynamo/lowering/test_aten_lowering_passes.py
@@ -1,7 +1,6 @@
 import torch
-from torch.testing._internal.common_utils import TestCase, run_tests
-
 import torch_tensorrt
+from torch.testing._internal.common_utils import TestCase, run_tests
 
 from ..testing_utilities import DECIMALS_OF_AGREEMENT, lower_graph_testing
 
@@ -444,6 +443,7 @@ def forward(self, input, weight, bias):
         max_diff = float(
             torch.max(torch.abs(optimized_model_results - torch_model_results))
         )
+
         self.assertAlmostEqual(
             max_diff,
             0,
diff --git a/tests/py/dynamo/models/test_export_serde.py b/tests/py/dynamo/models/test_export_serde.py
index efa593890e..b6519815a4 100644
--- a/tests/py/dynamo/models/test_export_serde.py
+++ b/tests/py/dynamo/models/test_export_serde.py
@@ -42,18 +42,17 @@ def forward(self, x):
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
-    deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
-
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
+    deser_trt_module = torchtrt.load("/tmp/trt.ep").module()
     # Check Pyt and TRT exported program outputs
-    cos_sim = cosine_similarity(model(input), trt_exp_program(input)[0])
+    cos_sim = cosine_similarity(model(input), trt_module(input)[0])
     assertions.assertTrue(
         cos_sim > COSINE_THRESHOLD,
         msg=f"test_base_model_full_compile TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
     )
     # Check Pyt and deserialized TRT exported program outputs
-    cos_sim = cosine_similarity(model(input), deser_trt_exp_program(input)[0])
+    cos_sim = cosine_similarity(model(input), deser_trt_module(input)[0])
     assertions.assertTrue(
         cos_sim > COSINE_THRESHOLD,
         msg=f"test_base_model_full_compile TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
@@ -93,12 +92,12 @@ def forward(self, x):
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
-    deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
+    deser_trt_module = torchtrt.load("/tmp/trt.ep").module()
     # Check Pyt and TRT exported program outputs
     outputs_pyt = model(input)
-    outputs_trt = trt_exp_program(input)
+    outputs_trt = trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt[idx])
         assertions.assertTrue(
@@ -107,7 +106,7 @@ def forward(self, x):
         )
 
     # Check Pyt and deserialized TRT exported program outputs
-    outputs_trt_deser = deser_trt_exp_program(input)
+    outputs_trt_deser = deser_trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt_deser[idx])
         assertions.assertTrue(
@@ -145,16 +144,15 @@ def forward(self, x):
             )
         ],
         "ir": ir,
-        "debug": True,
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
-    deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
+    deser_trt_module = torchtrt.load("/tmp/trt.ep").module()
     # Check Pyt and TRT exported program outputs
     outputs_pyt = model(input)
-    outputs_trt = trt_exp_program(input)
+    outputs_trt = trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt[idx])
         assertions.assertTrue(
@@ -163,7 +161,7 @@ def forward(self, x):
         )
 
     # Check Pyt and deserialized TRT exported program outputs
-    outputs_trt_deser = deser_trt_exp_program(input)
+    outputs_trt_deser = deser_trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt_deser[idx])
         assertions.assertTrue(
@@ -207,12 +205,11 @@ def forward(self, x):
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
-    deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
-
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
+    deser_trt_module = torchtrt.load("/tmp/trt.ep").module()
     outputs_pyt = model(input)
-    outputs_trt = trt_exp_program(input)
+    outputs_trt = trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt[idx])
         assertions.assertTrue(
@@ -220,7 +217,7 @@ def forward(self, x):
             msg=f"test_hybrid_relu_fallback TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
         )
 
-    outputs_trt_deser = deser_trt_exp_program(input)
+    outputs_trt_deser = deser_trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt_deser[idx])
         assertions.assertTrue(
@@ -248,19 +245,18 @@ def test_resnet18(ir):
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
-    deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
-
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
+    deser_trt_module = torchtrt.load("/tmp/trt.ep").module()
     outputs_pyt = model(input)
-    outputs_trt = trt_exp_program(input)
+    outputs_trt = trt_module(input)
     cos_sim = cosine_similarity(outputs_pyt, outputs_trt[0])
     assertions.assertTrue(
         cos_sim > COSINE_THRESHOLD,
         msg=f"test_resnet18 TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
     )
 
-    outputs_trt_deser = deser_trt_exp_program(input)
+    outputs_trt_deser = deser_trt_module(input)
 
     cos_sim = cosine_similarity(outputs_pyt, outputs_trt_deser[0])
     assertions.assertTrue(
@@ -303,12 +299,12 @@ def forward(self, x):
     }
 
     exp_program = torchtrt.dynamo.trace(model, **compile_spec)
-    trt_exp_program = torchtrt.dynamo.compile(exp_program, **compile_spec)
-    torch.export.save(trt_exp_program, "/tmp/trt.ep")
-    deser_trt_exp_program = torch.export.load("/tmp/trt.ep")
+    trt_module = torchtrt.dynamo.compile(exp_program, **compile_spec)
 
+    torchtrt.save(trt_module, "/tmp/trt.ep", inputs=[input])
+    deser_trt_module = torchtrt.load("/tmp/trt.ep").module()
     outputs_pyt = model(input)
-    outputs_trt = trt_exp_program(input)
+    outputs_trt = trt_module(input)
 
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt[idx])
@@ -317,10 +313,50 @@ def forward(self, x):
             msg=f"test_hybrid_conv_fallback TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
         )
 
-    outputs_trt_deser = deser_trt_exp_program(input)
+    outputs_trt_deser = deser_trt_module(input)
     for idx in range(len(outputs_pyt)):
         cos_sim = cosine_similarity(outputs_pyt[idx], outputs_trt_deser[idx])
         assertions.assertTrue(
             cos_sim > COSINE_THRESHOLD,
             msg=f"test_hybrid_conv_fallback deserialized TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
         )
+
+
+@pytest.mark.unit
+def test_save_load_ts(ir):
+    """
+    This tests save/load API on Torchscript format (model still compiled using dynamo workflow)
+    """
+
+    class MyModule(torch.nn.Module):
+        def __init__(self):
+            super().__init__()
+            self.conv = torch.nn.Conv2d(3, 16, 3, stride=1, bias=True)
+            self.relu = torch.nn.ReLU()
+
+        def forward(self, x):
+            conv = self.conv(x)
+            relu = self.relu(conv)
+            mul = relu * 0.5
+            return mul
+
+    model = MyModule().eval().cuda()
+    input = torch.randn((1, 3, 224, 224)).to("cuda")
+
+    trt_gm = torchtrt.compile(model, ir=ir, inputs=[input], min_block_size=1)
+    assertions.assertTrue(
+        isinstance(trt_gm, torch.fx.GraphModule),
+        msg=f"test_save_load_ts output type does not match with torch.fx.GraphModule",
+    )
+    outputs_trt = trt_gm(input)
+    # Save it as torchscript representation
+    torchtrt.save(trt_gm, "/tmp/trt.ts", output_format="torchscript", inputs=[input])
+
+    trt_ts_module = torchtrt.load("/tmp/trt.ts")
+    outputs_trt_deser = trt_ts_module(input)
+
+    cos_sim = cosine_similarity(outputs_trt, outputs_trt_deser)
+    assertions.assertTrue(
+        cos_sim > COSINE_THRESHOLD,
+        msg=f"test_save_load_ts TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
+    )
diff --git a/tests/py/dynamo/models/test_models_export.py b/tests/py/dynamo/models/test_models_export.py
index fd7b40592a..84f6bf7a36 100644
--- a/tests/py/dynamo/models/test_models_export.py
+++ b/tests/py/dynamo/models/test_models_export.py
@@ -110,11 +110,6 @@ def test_bert_base_uncased(ir):
     model = BertModel.from_pretrained("bert-base-uncased").cuda().eval()
     input = torch.randint(0, 1, (1, 14), dtype=torch.int32).to("cuda")
     input2 = torch.randint(0, 1, (1, 14), dtype=torch.int32).to("cuda")
-    model = (
-        transformers_trace(model, input_names=["input_ids", "attention_mask"])
-        .eval()
-        .cuda()
-    )
 
     compile_spec = {
         "inputs": [
@@ -133,7 +128,7 @@ def test_bert_base_uncased(ir):
         "enabled_precisions": {torch.float},
         "truncate_long_and_double": True,
         "ir": ir,
-        "min_block_size": 10,
+        "min_block_size": 15,
     }
     trt_mod = torchtrt.compile(model, **compile_spec)
     model_outputs = model(input, input2)
@@ -142,58 +137,9 @@ def test_bert_base_uncased(ir):
         len(model_outputs) == len(trt_model_outputs),
         msg=f"Number of outputs for BERT model compilation is different with Pytorch {len(model_outputs)} and TensorRT {len(trt_model_outputs)}. Please check the compilation.",
     )
-    for index, key in enumerate(model_outputs):
-        out, trt_out = model_outputs[key], trt_model_outputs[index]
-        cos_sim = cosine_similarity(out, trt_out)
-        assertions.assertTrue(
-            cos_sim > COSINE_THRESHOLD,
-            msg=f"HF BERT base-uncased TRT outputs don't match with the original model. Cosine sim score: {cos_sim} Threshold: {COSINE_THRESHOLD}",
-        )
-
-    # Clean up model env
-    torch._dynamo.reset()
-
-
-@pytest.mark.unit
-def test_bert_base_uncased(ir):
-    model = BertModel.from_pretrained("bert-base-uncased").cuda().eval()
-    input = torch.randint(0, 1, (1, 14), dtype=torch.int32).to("cuda")
-    input2 = torch.randint(0, 1, (1, 14), dtype=torch.int32).to("cuda")
-    model = (
-        transformers_trace(model, input_names=["input_ids", "attention_mask"])
-        .eval()
-        .cuda()
-    )
 
-    compile_spec = {
-        "inputs": [
-            torchtrt.Input(
-                input.shape,
-                dtype=input.dtype,
-                format=torch.contiguous_format,
-            ),
-            torchtrt.Input(
-                input.shape,
-                dtype=input.dtype,
-                format=torch.contiguous_format,
-            ),
-        ],
-        "device": torchtrt.Device("cuda:0"),
-        "enabled_precisions": {torch.float},
-        "truncate_long_and_double": True,
-        "ir": ir,
-        "min_block_size": 10,
-        "torch_executed_ops": {"torch.ops.aten.gelu.default"},
-    }
-    trt_mod = torchtrt.compile(model, **compile_spec)
-    model_outputs = model(input, input2)
-    trt_model_outputs = trt_mod(input, input2)
-    assertions.assertTrue(
-        len(model_outputs) == len(trt_model_outputs),
-        msg=f"Number of outputs for BERT model compilation is different with Pytorch {len(model_outputs)} and TensorRT {len(trt_model_outputs)}. Please check the compilation.",
-    )
-    for index, key in enumerate(model_outputs):
-        out, trt_out = model_outputs[key], trt_model_outputs[index]
+    for key, _ in model_outputs.items():
+        out, trt_out = model_outputs[key], trt_model_outputs[key]
         cos_sim = cosine_similarity(out, trt_out)
         assertions.assertTrue(
             cos_sim > COSINE_THRESHOLD,
@@ -203,9 +149,6 @@ def test_bert_base_uncased(ir):
     # Clean up model env
     torch._dynamo.reset()
 
-    with torch.no_grad():
-        torch.cuda.empty_cache()
-
 
 @pytest.mark.unit
 def test_resnet18_half(ir):
diff --git a/tests/py/dynamo/models/test_output_format.py b/tests/py/dynamo/models/test_output_format.py
deleted file mode 100644
index 3d2e747ceb..0000000000
--- a/tests/py/dynamo/models/test_output_format.py
+++ /dev/null
@@ -1,62 +0,0 @@
-import unittest
-
-import pytest
-import timm
-import torch
-import torch_tensorrt as torchtrt
-import torchvision.models as models
-from torch_tensorrt.dynamo.utils import COSINE_THRESHOLD, cosine_similarity
-
-assertions = unittest.TestCase()
-
-
-@pytest.mark.unit
-def test_output_format(ir):
-    """
-    This tests output_format type in the compilation setting
-    """
-
-    class MyModule(torch.nn.Module):
-        def __init__(self):
-            super().__init__()
-            self.conv = torch.nn.Conv2d(3, 16, 3, stride=1, bias=True)
-            self.relu = torch.nn.ReLU()
-
-        def forward(self, x):
-            conv = self.conv(x)
-            relu = self.relu(conv)
-            mul = relu * 0.5
-            return mul
-
-    model = MyModule().eval().cuda()
-    input = torch.randn((1, 3, 224, 224)).to("cuda")
-
-    trt_ep = torchtrt.compile(model, ir="dynamo", inputs=[input], min_block_size=1)
-    assertions.assertTrue(
-        isinstance(trt_ep, torch.export.ExportedProgram),
-        msg=f"test_output_format output type does not match with torch.export.ExportedProgram",
-    )
-
-    trt_ts = torchtrt.compile(
-        model,
-        ir="dynamo",
-        inputs=[input],
-        min_block_size=1,
-        output_format="torchscript",
-    )
-    assertions.assertTrue(
-        isinstance(trt_ts, torch.jit.ScriptModule),
-        msg=f"test_output_format output type does not match with torch.jit.ScriptModule",
-    )
-
-    trt_gm = torchtrt.compile(
-        model,
-        ir="dynamo",
-        inputs=[input],
-        min_block_size=1,
-        output_format="graph_module",
-    )
-    assertions.assertTrue(
-        isinstance(trt_gm, torch.fx.GraphModule),
-        msg=f"test_output_format output type does not match with torch.fx.GraphModule",
-    )

From 1ae46e9c3cfd1fe3d13beeac28919fc6e24b1cf2 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 27 Mar 2024 09:07:47 -0700
Subject: [PATCH 016/122] chore: more updates

---
 core/conversion/converters/impl/conv_deconv.cpp |  9 ++++-----
 core/conversion/evaluators/eval_util.cpp        | 14 +++++---------
 py/requirements.txt                             |  2 +-
 pyproject.toml                                  |  4 ++--
 tests/core/partitioning/test_loading_model.cpp  |  2 +-
 tests/cpp/test_compiled_modules.cpp             |  2 +-
 tests/cpp/test_modules_as_engines.cpp           |  2 +-
 7 files changed, 15 insertions(+), 20 deletions(-)

diff --git a/core/conversion/converters/impl/conv_deconv.cpp b/core/conversion/converters/impl/conv_deconv.cpp
index aa7acc9cc4..a779a3c1b9 100644
--- a/core/conversion/converters/impl/conv_deconv.cpp
+++ b/core/conversion/converters/impl/conv_deconv.cpp
@@ -146,9 +146,9 @@ bool add_conv_deconv(ConversionCtx* ctx, const torch::jit::Node* n, args& args)
       // TensorRT expects nbSpatialDims = 2 or 3
       filter_dim = util::unsqueezeDims(filter_dim, filter_dim.nbDims, 1, false);
       // Reshape input dimensions
-      in = addPadding(ctx, n, in, 4);
+      in = addPadding(ctx, n, in, 4, true, true, std::string(util::node_info(n) + "_input_shuffle"));
       LOG_DEBUG("Reshaping input dimensions to: " << in->getDimensions());
-      kernel = addPadding(ctx, n, kernel, 4);
+      kernel = addPadding(ctx, n, kernel, 4, true, true, std::string(util::node_info(n) + "_kernel_shuffle"));
       LOG_DEBUG("Reshaping kernel dimensions to: " << kernel->getDimensions());
       if (transposed) {
         num_output_maps = kernel_dims.d[1];
@@ -291,11 +291,10 @@ bool add_conv_deconv(ConversionCtx* ctx, const torch::jit::Node* n, args& args)
     // shape of convolution's weight: [out, in/groups, ...]
     auto conv = ctx->net->addConvolutionNd(*in, w.shape.d[0], w.kernel_shape, w.data, bias.data);
     TORCHTRT_CHECK(conv, "Unable to create convolution layer from node: " << *n);
-
     conv->setStrideNd(stride);
     conv->setPaddingMode(nvinfer1::PaddingMode::kEXPLICIT_ROUND_DOWN);
-    conv->setPaddingNd(padding);
-    conv->setPostPadding(out_padding);
+    conv->setPrePadding(padding);
+    conv->setPostPadding(padding);
     conv->setDilationNd(dilation);
     conv->setNbGroups(groups);
     new_layer = conv;
diff --git a/core/conversion/evaluators/eval_util.cpp b/core/conversion/evaluators/eval_util.cpp
index 71b6de9eb2..9b6139073d 100644
--- a/core/conversion/evaluators/eval_util.cpp
+++ b/core/conversion/evaluators/eval_util.cpp
@@ -34,11 +34,8 @@ c10::IValue dynamic_size_layer(ConversionCtx* ctx, const torch::jit::Node* n, kw
   auto in = args.at(n->input(0)).ITensorOrFreeze(ctx);
   auto input_dims = in->getDimensions();
   LOG_DEBUG("Input dimensions: " << input_dims);
-
-  auto shape_layer = ctx->net->addShape(*in);
-  TORCHTRT_CHECK(shape_layer, "Unable to create shape layer from node: " << *n);
-  auto shape_1d_tensor = shape_layer->getOutput(0);
-
+  nvinfer1::ITensor* shape_1d_tensor = torch_tensorrt::core::conversion::converters::getShapeOutput(
+      ctx, in, std::string(util::node_info(n) + "_dynamic_shape_layer_cast").c_str());
   if (n->inputs().size() != 1) {
     auto maxDim = static_cast<int64_t>(in->getDimensions().nbDims);
     auto dim = args.at(n->input(1)).unwrapToInt();
@@ -423,13 +420,12 @@ c10::optional<torch::jit::IValue> newTensorLikeImplementation(
     // broadcast constant to output shape
     std::vector<int64_t> start_vec(self->getDimensions().nbDims, 0);
     auto start_offset = util::toDims(c10::IntArrayRef(start_vec));
-    auto shape_layer = ctx->net->addShape(*self);
-    TORCHTRT_CHECK(shape_layer, "Unable to create shape layer from node: " << *n);
-    shape_layer->setName((util::node_info(n) + "_shape").c_str());
+    nvinfer1::ITensor* shape_output = torch_tensorrt::core::conversion::converters::getShapeOutput(
+        ctx, self, std::string(util::node_info(n) + "_shape").c_str());
     // slice implements expand
     auto slice_layer = ctx->net->addSlice(*constant_itensor, start_offset, self->getDimensions(), start_offset);
     TORCHTRT_CHECK(slice_layer, "Unable to create slice layer from node: " << *n);
-    slice_layer->setInput(2, *shape_layer->getOutput(0));
+    slice_layer->setInput(2, *shape_output);
     slice_layer->setName((util::node_info(n) + "_slice").c_str());
     auto out_tensor = ctx->AssociateValueAndTensor(n->outputs()[0], slice_layer->getOutput(0));
     LOG_DEBUG("Output tensor shape: " << out_tensor->getDimensions());
diff --git a/py/requirements.txt b/py/requirements.txt
index 19c39c8647..565395b59b 100644
--- a/py/requirements.txt
+++ b/py/requirements.txt
@@ -5,5 +5,5 @@ pybind11==2.6.2
 torch==2.3.0
 torchvision==0.18.0
 --extra-index-url https://pypi.ngc.nvidia.com
-tensorrt>=10.0
+tensorrt==10.0.0b6
 pyyaml
diff --git a/pyproject.toml b/pyproject.toml
index 6c4940013d..7468484f48 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,7 +8,7 @@ requires = [
     "cffi>=1.15.1",
     "typing-extensions>=4.7.0",
     "future>=0.18.3",
-    "tensorrt>=10.0",
+    "tensorrt==10.0.0b6",
     "torch >=2.3.0.dev,<2.4.0",
     "pybind11==2.6.2",
     "numpy",
@@ -42,7 +42,7 @@ requires-python = ">=3.8"
 keywords = ["pytorch", "torch", "tensorrt", "trt", "ai", "artificial intelligence", "ml", "machine learning", "dl", "deep learning", "compiler", "dynamo", "torchscript", "inference"]
 dependencies = [
     "torch >=2.3.0.dev,<2.4.0",
-    "tensorrt>=10.0",
+    "tensorrt==10.0.0b6",
     "packaging>=23",
     "numpy",
     "typing-extensions>=4.7.0",
diff --git a/tests/core/partitioning/test_loading_model.cpp b/tests/core/partitioning/test_loading_model.cpp
index b42368fe3e..67c42caef2 100644
--- a/tests/core/partitioning/test_loading_model.cpp
+++ b/tests/core/partitioning/test_loading_model.cpp
@@ -7,7 +7,7 @@
 
 #ifndef DISABLE_TEST_IN_CI
 
-TEST(Partitioning, ComputeResNet50FallbackGraphCorrectly) {
+TEST(Partitioning, ComputeConditionalLoadingGraphCorrectly) {
   torch::jit::script::Module mod;
   try {
     mod = torch::jit::load("tests/modules/conditional_scripted.jit.pt");
diff --git a/tests/cpp/test_compiled_modules.cpp b/tests/cpp/test_compiled_modules.cpp
index 62bae5756d..7def168249 100644
--- a/tests/cpp/test_compiled_modules.cpp
+++ b/tests/cpp/test_compiled_modules.cpp
@@ -58,7 +58,7 @@ INSTANTIATE_TEST_SUITE_P(
         PathAndInput({"tests/modules/resnet18_scripted.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}}),
         PathAndInput({"tests/modules/mobilenet_v2_scripted.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}}),
         PathAndInput({"tests/modules/efficientnet_b0_scripted.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}}),
-        PathAndInput({"tests/modules/bert_base_uncased_traced.jit.pt", {{1, 14}, {1, 14}}, {at::kInt, at::kInt}}),
+        PathAndInput({"tests/modules/bert_base_uncased_traced.jit.pt", {{1, 14}, {1, 14}}, {at::kInt, at::kInt}})));
 // NOTE: ViT tests are disabled until Python 3.11 issue is resolved
 // https://github.com/huggingface/pytorch-image-models/issues/1946 PathAndInput({"tests/modules/vit_scripted.jit.pt",
 // {{1, 3, 224, 224}}, {at::kFloat}})));
diff --git a/tests/cpp/test_modules_as_engines.cpp b/tests/cpp/test_modules_as_engines.cpp
index 4cb9dd9f8d..cc9fdd24a4 100644
--- a/tests/cpp/test_modules_as_engines.cpp
+++ b/tests/cpp/test_modules_as_engines.cpp
@@ -29,7 +29,7 @@ INSTANTIATE_TEST_SUITE_P(
     testing::Values(
         PathAndInput({"tests/modules/resnet18_scripted.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}}),
         PathAndInput({"tests/modules/mobilenet_v2_scripted.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}}),
-        PathAndInput({"tests/modules/efficientnet_b0_scripted.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}}),
+        PathAndInput({"tests/modules/efficientnet_b0_scripted.jit.pt", {{1, 3, 224, 224}}, {at::kFloat}})));
 // NOTE: ViT tests are disabled until Python 3.11 issue is resolved
 // https://github.com/huggingface/pytorch-image-models/issues/1946 PathAndInput({"tests/modules/vit_scripted.jit.pt",
 // {{1, 3, 224, 224}}, {at::kFloat}})));

From beb59206d082d8f0842ccca6d30b714dffccc07f Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 27 Mar 2024 09:22:53 -0700
Subject: [PATCH 017/122] chore: Update versions

---
 README.md | 4 ++--
 WORKSPACE | 6 +++---
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/README.md b/README.md
index 875b640304..eecae762cf 100644
--- a/README.md
+++ b/README.md
@@ -116,10 +116,10 @@ torch.jit.save(trt_ts_module, "trt_torchscript_module.ts") # save the TRT embedd
 These are the following dependencies used to verify the testcases. Torch-TensorRT can work with other versions, but the tests are not guaranteed to pass.
 
 - Bazel 5.2.0
-- Libtorch 2.3.0.dev (latest nightly) (built with CUDA 12.1)
+- Libtorch 2.3.0 (built with CUDA 12.1)
 - CUDA 12.1
 - cuDNN 8.9.5
-- TensorRT 8.6.1
+- TensorRT 10.0.0.6
 
 ## Prebuilt Binaries and Wheel files
 
diff --git a/WORKSPACE b/WORKSPACE
index edc5c9a050..76e9a602fa 100644
--- a/WORKSPACE
+++ b/WORKSPACE
@@ -81,10 +81,10 @@ http_archive(
 http_archive(
     name = "tensorrt",
     build_file = "@//third_party/tensorrt/archive:BUILD",
-    sha256 = "0f8157a5fc5329943b338b893591373350afa90ca81239cdadd7580cd1eba254",
-    strip_prefix = "TensorRT-8.6.1.6",
+    sha256 = "7ad5c8eab8fe8803bef5d8cee54ec1f407797ac8edb8ea3186cb9f24af726486",
+    strip_prefix = "TensorRT-10.0.0.6",
     urls = [
-        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/secure/8.6.1/tars/TensorRT-8.6.1.6.Linux.x86_64-gnu.cuda-12.0.tar.gz",
+        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.0/tars/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz",
     ],
 )
 

From f0068c64ba4b5d214a3e1beb52bf15eaaae7cf21 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 27 Mar 2024 10:15:38 -0700
Subject: [PATCH 018/122] chore: update tensorrt version in CI

---
 dev_dep_versions.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/dev_dep_versions.yml b/dev_dep_versions.yml
index 442485474c..b07db5533f 100644
--- a/dev_dep_versions.yml
+++ b/dev_dep_versions.yml
@@ -1,4 +1,4 @@
-__version__: "2.3.0.dev0"
+__version__: "2.3.0"
 __cuda_version__: "12.1"
 __cudnn_version__: "8.9"
-__tensorrt_version__: "8.6"
+__tensorrt_version__: "10.0.0b6"

From 39261b9d2d421496df5bd1d99b237aa459b9862f Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 27 Mar 2024 14:28:17 -0700
Subject: [PATCH 019/122] chore: more updates

---
 core/conversion/converters/impl/conv_deconv.cpp     |  3 +--
 core/conversion/converters/impl/interpolate.cpp     | 13 ++++++++-----
 .../passes/unpack_scaled_dot_product_attention.cpp  |  8 ++++----
 .../test_scaled_dot_product_attention.cpp           |  9 ++++++---
 4 files changed, 19 insertions(+), 14 deletions(-)

diff --git a/core/conversion/converters/impl/conv_deconv.cpp b/core/conversion/converters/impl/conv_deconv.cpp
index a779a3c1b9..c71007ac03 100644
--- a/core/conversion/converters/impl/conv_deconv.cpp
+++ b/core/conversion/converters/impl/conv_deconv.cpp
@@ -293,8 +293,7 @@ bool add_conv_deconv(ConversionCtx* ctx, const torch::jit::Node* n, args& args)
     TORCHTRT_CHECK(conv, "Unable to create convolution layer from node: " << *n);
     conv->setStrideNd(stride);
     conv->setPaddingMode(nvinfer1::PaddingMode::kEXPLICIT_ROUND_DOWN);
-    conv->setPrePadding(padding);
-    conv->setPostPadding(padding);
+    conv->setPaddingNd(padding);
     conv->setDilationNd(dilation);
     conv->setNbGroups(groups);
     new_layer = conv;
diff --git a/core/conversion/converters/impl/interpolate.cpp b/core/conversion/converters/impl/interpolate.cpp
index 748e3c9e1a..64542d14f6 100644
--- a/core/conversion/converters/impl/interpolate.cpp
+++ b/core/conversion/converters/impl/interpolate.cpp
@@ -77,7 +77,6 @@ void resize_layer_size(
   TORCHTRT_CHECK((out_shape.size() > 0) ^ (scales.size() > 0), "only one of out_shape or scales should be defined");
   auto resize_layer = ctx->net->addResize(*in);
   TORCHTRT_CHECK(resize_layer, "Unable to create interpolation (resizing) layer from node" << *n);
-
   if (out_shape.size() > 0) {
     auto th_dynamic_shape_mask = torch::zeros(out_shape.size(), torch::kInt32);
     auto th_static_shape_mask = torch::zeros(out_shape.size(), torch::kInt32);
@@ -108,13 +107,17 @@ void resize_layer_size(
 
   resize_layer->setResizeMode(mode);
   resize_layer->setName(util::node_info(n).c_str());
-#if NV_TENSORRT_MAJOR < 8
-  resize_layer->setAlignCorners(align_corners);
-#else
+
   if (align_corners) {
     resize_layer->setCoordinateTransformation(nvinfer1::ResizeCoordinateTransformation::kALIGN_CORNERS);
+  } else {
+    if (mode == nvinfer1::InterpolationMode::kLINEAR) {
+      resize_layer->setCoordinateTransformation(nvinfer1::ResizeCoordinateTransformation::kHALF_PIXEL);
+    } else {
+      // kASYMMETRIC is the default transformation in TensorRT
+      resize_layer->setCoordinateTransformation(nvinfer1::ResizeCoordinateTransformation::kASYMMETRIC);
+    }
   }
-#endif
   auto layer_output = ctx->AssociateValueAndTensor(n->outputs()[0], resize_layer->getOutput(0));
 
   LOG_DEBUG("Output tensor shape: " << layer_output->getDimensions());
diff --git a/core/lowering/passes/unpack_scaled_dot_product_attention.cpp b/core/lowering/passes/unpack_scaled_dot_product_attention.cpp
index bfe0004bd6..3c347f65ca 100644
--- a/core/lowering/passes/unpack_scaled_dot_product_attention.cpp
+++ b/core/lowering/passes/unpack_scaled_dot_product_attention.cpp
@@ -12,12 +12,12 @@ namespace passes {
 // https://pytorch.org/docs/stable/generated/torch.nn.functional.scaled_dot_product_attention.html
 void UnpackScaledDotProductAttention(std::shared_ptr<torch::jit::Graph>& graph) {
   std::string sdpa_pattern = R"IR(
-    graph(%query, %key, %value, %attn_mask, %dropout_p, %is_causal):
-      %out: Tensor = aten::scaled_dot_product_attention(%query, %key, %value, %attn_mask, %dropout_p, %is_causal)
+    graph(%query, %key, %value, %attn_mask, %dropout_p, %is_causal, %scale):
+      %out: Tensor = aten::scaled_dot_product_attention(%query, %key, %value, %attn_mask, %dropout_p, %is_causal, %scale)
       return (%out))IR";
 
   std::string unpacked_sdpa_pattern = R"IR(
-    graph(%query, %key, %value, %attn_mask, %dropout_p, %is_causal):
+    graph(%query, %key, %value, %attn_mask, %dropout_p, %is_causal, %scale):
       %none : NoneType = prim::Constant()
       %1 : int = prim::Constant[value=-1]()
       %2 : int = prim::Constant[value=-2]()
@@ -33,7 +33,7 @@ void UnpackScaledDotProductAttention(std::shared_ptr<torch::jit::Graph>& graph)
       return(%out))IR";
 
   std::string unpacked_sdpa_attn_biased_pattern = R"IR(
-    graph(%query, %key, %value, %attn_mask, %dropout_p, %is_causal):
+    graph(%query, %key, %value, %attn_mask, %dropout_p, %is_causal, %scale):
       %none : NoneType = prim::Constant()
       %0 : int = prim::Constant[value=1]()
       %1 : int = prim::Constant[value=-1]()
diff --git a/tests/core/conversion/converters/test_scaled_dot_product_attention.cpp b/tests/core/conversion/converters/test_scaled_dot_product_attention.cpp
index 785363ccca..7fa859e324 100644
--- a/tests/core/conversion/converters/test_scaled_dot_product_attention.cpp
+++ b/tests/core/conversion/converters/test_scaled_dot_product_attention.cpp
@@ -10,8 +10,9 @@ TEST(Converters, ATenScaledDotProductAttentionConvertsCorrectly) {
       graph(%query : Tensor, %key : Tensor, %value : Tensor):
         %none : NoneType = prim::Constant()
         %0 : float = prim::Constant[value=0.]()
+        %scale : float = prim::Constant[value=1.]()
         %false : bool = prim::Constant[value=0]()
-        %3 : Tensor = aten::scaled_dot_product_attention(%query, %key, %value, %none, %0, %false)
+        %3 : Tensor = aten::scaled_dot_product_attention(%query, %key, %value, %none, %0, %false, %scale)
         return (%3))IR";
 
   auto g = std::make_shared<torch::jit::Graph>();
@@ -36,7 +37,8 @@ TEST(Converters, ATenScaledDotProductAttnMaskFloatConvertsCorrectly) {
       graph(%query : Tensor, %key : Tensor, %value : Tensor, %attn_mask : Tensor):
         %0 : float = prim::Constant[value=0.]()
         %false : bool = prim::Constant[value=0]()
-        %3 : Tensor = aten::scaled_dot_product_attention(%query, %key, %value, %attn_mask, %0, %false)
+        %scale : float = prim::Constant[value=1.]()
+        %3 : Tensor = aten::scaled_dot_product_attention(%query, %key, %value, %attn_mask, %0, %false, %scale)
         return (%3))IR";
 
   auto g = std::make_shared<torch::jit::Graph>();
@@ -62,7 +64,8 @@ TEST(Converters, ATenScaledDotProductAttnMaskBoolConvertsCorrectly) {
       graph(%query : Tensor, %key : Tensor, %value : Tensor, %attn_mask : Tensor):
         %0 : float = prim::Constant[value=0.]()
         %false : bool = prim::Constant[value=0]()
-        %3 : Tensor = aten::scaled_dot_product_attention(%query, %key, %value, %attn_mask, %0, %false)
+        %scale : float = prim::Constant[value=1.]()
+        %3 : Tensor = aten::scaled_dot_product_attention(%query, %key, %value, %attn_mask, %0, %false, %scale)
         return (%3))IR";
 
   auto g = std::make_shared<torch::jit::Graph>();

From 3753150fb75e9a6637acffa35f2f3b4b63d15afa Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 2 Apr 2024 05:12:26 -0700
Subject: [PATCH 020/122] chore: more fixes

---
 .../test_scaled_dot_product_attention.cpp     |  6 ++---
 .../test_trt_intercompatibility.py            | 24 ++++++++++---------
 2 files changed, 16 insertions(+), 14 deletions(-)

diff --git a/tests/core/conversion/converters/test_scaled_dot_product_attention.cpp b/tests/core/conversion/converters/test_scaled_dot_product_attention.cpp
index 7fa859e324..5550d5409b 100644
--- a/tests/core/conversion/converters/test_scaled_dot_product_attention.cpp
+++ b/tests/core/conversion/converters/test_scaled_dot_product_attention.cpp
@@ -10,7 +10,7 @@ TEST(Converters, ATenScaledDotProductAttentionConvertsCorrectly) {
       graph(%query : Tensor, %key : Tensor, %value : Tensor):
         %none : NoneType = prim::Constant()
         %0 : float = prim::Constant[value=0.]()
-        %scale : float = prim::Constant[value=1.]()
+        %scale : NoneType = prim::Constant()
         %false : bool = prim::Constant[value=0]()
         %3 : Tensor = aten::scaled_dot_product_attention(%query, %key, %value, %none, %0, %false, %scale)
         return (%3))IR";
@@ -37,7 +37,7 @@ TEST(Converters, ATenScaledDotProductAttnMaskFloatConvertsCorrectly) {
       graph(%query : Tensor, %key : Tensor, %value : Tensor, %attn_mask : Tensor):
         %0 : float = prim::Constant[value=0.]()
         %false : bool = prim::Constant[value=0]()
-        %scale : float = prim::Constant[value=1.]()
+        %scale : NoneType = prim::Constant()
         %3 : Tensor = aten::scaled_dot_product_attention(%query, %key, %value, %attn_mask, %0, %false, %scale)
         return (%3))IR";
 
@@ -64,7 +64,7 @@ TEST(Converters, ATenScaledDotProductAttnMaskBoolConvertsCorrectly) {
       graph(%query : Tensor, %key : Tensor, %value : Tensor, %attn_mask : Tensor):
         %0 : float = prim::Constant[value=0.]()
         %false : bool = prim::Constant[value=0]()
-        %scale : float = prim::Constant[value=1.]()
+        %scale : NoneType = prim::Constant()
         %3 : Tensor = aten::scaled_dot_product_attention(%query, %key, %value, %attn_mask, %0, %false, %scale)
         return (%3))IR";
 
diff --git a/tests/py/ts/integrations/test_trt_intercompatibility.py b/tests/py/ts/integrations/test_trt_intercompatibility.py
index b938e4a1ac..4c84ad088f 100644
--- a/tests/py/ts/integrations/test_trt_intercompatibility.py
+++ b/tests/py/ts/integrations/test_trt_intercompatibility.py
@@ -1,9 +1,10 @@
 import unittest
-import torch_tensorrt as torchtrt
+
+import tensorrt as trt
 import torch
+import torch_tensorrt as torchtrt
 import torchvision.models as models
-import tensorrt as trt
-from utils import cosine_similarity, COSINE_THRESHOLD
+from utils import COSINE_THRESHOLD, cosine_similarity
 
 
 class TestPyTorchToTRTEngine(unittest.TestCase):
@@ -31,18 +32,19 @@ def test_pt_to_trt(self):
         with trt.Runtime(TRT_LOGGER) as rt:
             engine = rt.deserialize_cuda_engine(trt_engine)
             with engine.create_execution_context() as ctx:
-                out = torch.empty(size=tuple(engine.get_binding_shape(1))).to("cuda:0")
+                out = torch.empty(
+                    size=tuple(engine.get_tensor_shape(engine.get_tensor_name(1)))
+                ).to("cuda:0")
                 bindings = [
                     self.input.contiguous().data_ptr(),
                     out.contiguous().data_ptr(),
                 ]
-                ctx.execute_async(
-                    batch_size=1,
-                    bindings=bindings,
-                    stream_handle=torch.cuda.current_stream(
-                        device="cuda:0"
-                    ).cuda_stream,
-                )
+
+                # Assign tensor address appropriately
+                for idx in range(engine.num_io_tensors):
+                    ctx.set_tensor_address(engine.get_tensor_name(idx), bindings[idx])
+                ctx.execute_async_v3(torch.cuda.current_stream().cuda_stream)
+
                 cos_sim = cosine_similarity(self.model(self.input), out)
                 self.assertTrue(
                     cos_sim > COSINE_THRESHOLD,

From c355766f659f15fe02bf373e004e10039047d58d Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 2 Apr 2024 05:54:57 -0700
Subject: [PATCH 021/122] chore: remove NvUtils.h

---
 third_party/tensorrt/local/BUILD | 16 ++++------------
 1 file changed, 4 insertions(+), 12 deletions(-)

diff --git a/third_party/tensorrt/local/BUILD b/third_party/tensorrt/local/BUILD
index 9cbe98a41e..59d0ef01d8 100644
--- a/third_party/tensorrt/local/BUILD
+++ b/third_party/tensorrt/local/BUILD
@@ -29,9 +29,7 @@ config_setting(
 cc_library(
     name = "nvinfer_headers",
     hdrs = select({
-        ":aarch64_linux": [
-            "include/aarch64-linux-gnu/NvUtils.h",
-        ] + glob(
+        ":aarch64_linux": glob(
             [
                 "include/aarch64-linux-gnu/NvInfer*.h",
             ],
@@ -40,9 +38,7 @@ cc_library(
                 "include/aarch64-linux-gnu/NvInferPluginUtils.h",
             ],
         ),
-        ":ci_rhel_x86_64_linux": [
-            "include/NvUtils.h",
-        ] + glob(
+        ":ci_rhel_x86_64_linux": glob(
             [
                 "include/NvInfer*.h",
             ],
@@ -51,9 +47,7 @@ cc_library(
                 "include/NvInferPluginUtils.h",
             ],
         ),
-        ":windows": [
-            "include/NvUtils.h",
-        ] + glob(
+        ":windows": glob(
             [
                 "include/NvInfer*.h",
             ],
@@ -62,9 +56,7 @@ cc_library(
                 "include/NvInferPluginUtils.h",
             ],
         ),
-        "//conditions:default": [
-            "include/x86_64-linux-gnu/NvUtils.h",
-        ] + glob(
+        "//conditions:default": glob(
             [
                 "include/x86_64-linux-gnu/NvInfer*.h",
             ],

From 2d237dca528d0743c4b748e60c7969de46660464 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 2 Apr 2024 07:14:43 -0700
Subject: [PATCH 022/122] chore: more updates

---
 WORKSPACE                                              | 10 ----------
 core/conversion/converters/impl/chunk.cpp              |  4 ----
 core/ir/ir.cpp                                         |  1 -
 core/plugins/impl/interpolate_plugin.h                 |  1 -
 core/plugins/impl/normalize_plugin.h                   |  1 -
 third_party/tensorrt/local/BUILD                       |  2 --
 .../ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl   |  6 ------
 7 files changed, 25 deletions(-)

diff --git a/WORKSPACE b/WORKSPACE
index 76e9a602fa..95abcea2d3 100644
--- a/WORKSPACE
+++ b/WORKSPACE
@@ -68,16 +68,6 @@ http_archive(
 # Either place them in the distdir directory in third_party and use the --distdir flag
 # or modify the urls to "file:///<PATH TO TARBALL>/<TARBALL NAME>.tar.gz
 
-http_archive(
-    name = "cudnn",
-    build_file = "@//third_party/cudnn/archive:BUILD",
-    sha256 = "2a2eb89a2ab51071151c6082f1e816c702167a711a9372f9f73a7b5c4b06e01a",
-    strip_prefix = "cudnn-linux-x86_64-8.9.5.30_cuda12-archive",
-    urls = [
-        "https://developer.nvidia.com/downloads/compute/cudnn/secure/8.9.5/local_installers/12.x/cudnn-linux-x86_64-8.9.5.30_cuda12-archive.tar.xz",
-    ],
-)
-
 http_archive(
     name = "tensorrt",
     build_file = "@//third_party/tensorrt/archive:BUILD",
diff --git a/core/conversion/converters/impl/chunk.cpp b/core/conversion/converters/impl/chunk.cpp
index a7191133fb..b3d2441706 100644
--- a/core/conversion/converters/impl/chunk.cpp
+++ b/core/conversion/converters/impl/chunk.cpp
@@ -17,7 +17,6 @@ auto cat_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns()
               auto chunks = args[1].unwrapToInt();
               auto dim = args[2].unwrapToInt();
               bool dynamic_shape = ctx->input_is_dynamic;
-              int size = in->getDimensions().nbDims;
               int maxDim = static_cast<int32_t>(in->getDimensions().d[dim]);
 
               c10::ListTypePtr lt = n->output()->type()->expect<c10::ListType>();
@@ -41,9 +40,6 @@ auto cat_registrations TORCHTRT_UNUSED = RegisterNodeConversionPatterns()
               size_.nbDims = nbdims;
               stride_.nbDims = nbdims;
 
-              int startIdx = 0;
-              int endIdx = maxDim;
-
               for (int i = 0; i < nbdims; i++) {
                 start_.d[i] = 0;
                 size_.d[i] = 0;
diff --git a/core/ir/ir.cpp b/core/ir/ir.cpp
index c98d17c5ef..b67e228f1f 100644
--- a/core/ir/ir.cpp
+++ b/core/ir/ir.cpp
@@ -151,7 +151,6 @@ c10::optional<at::ScalarType> get_value_first_calc_dtype_opt(torch::jit::Block*
 
     // If node outputs a Tensor it might be a result of tensor calcuation so check to see
     // if any inputs to the calculation can give us hints
-    c10::optional<torch::jit::Node*> const_tensor_n = {};
 
     // Backtrace to constants which will immediately give us the Tensor type if possible
     for (auto in : ins) {
diff --git a/core/plugins/impl/interpolate_plugin.h b/core/plugins/impl/interpolate_plugin.h
index ced4cbee20..ce009af03e 100644
--- a/core/plugins/impl/interpolate_plugin.h
+++ b/core/plugins/impl/interpolate_plugin.h
@@ -3,7 +3,6 @@
 #include <ATen/ATen.h>
 #include <ATen/cuda/CUDAEvent.h>
 #include <cuda_runtime_api.h>
-#include <cudnn.h>
 #include <iostream>
 #include <sstream>
 #include <string>
diff --git a/core/plugins/impl/normalize_plugin.h b/core/plugins/impl/normalize_plugin.h
index 28c3a5c5da..5d51a68293 100644
--- a/core/plugins/impl/normalize_plugin.h
+++ b/core/plugins/impl/normalize_plugin.h
@@ -3,7 +3,6 @@
 #include <ATen/ATen.h>
 #include <ATen/cuda/CUDAEvent.h>
 #include <cuda_runtime_api.h>
-#include <cudnn.h>
 #include <iostream>
 #include <sstream>
 #include <string>
diff --git a/third_party/tensorrt/local/BUILD b/third_party/tensorrt/local/BUILD
index 59d0ef01d8..c317e16688 100644
--- a/third_party/tensorrt/local/BUILD
+++ b/third_party/tensorrt/local/BUILD
@@ -104,7 +104,6 @@ cc_library(
         "nvinfer_headers",
         "nvinfer_lib",
         "@cuda//:cudart",
-        "@cudnn",
     ],
 )
 
@@ -358,7 +357,6 @@ cc_library(
     deps = [
         "nvinfer",
         "@cuda//:cudart",
-        "@cudnn",
     ],
     alwayslink = True,
 )
diff --git a/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl b/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl
index db6cfb0b5d..8ff4f74aaf 100644
--- a/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl
+++ b/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl
@@ -73,12 +73,6 @@ http_archive(
 # Locally installed dependencies (use in cases of custom dependencies or aarch64)
 ####################################################################################
 
-new_local_repository(
-    name = "cudnn",
-    path = "/usr/",
-    build_file = "@//third_party/cudnn/local:BUILD"
-)
-
 new_local_repository(
    name = "tensorrt",
    path = "/usr/",

From e4b442913b7200d66af92c90ebb54d77321bd536 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 2 Apr 2024 07:30:35 -0700
Subject: [PATCH 023/122] chore: change lib64 to lib in rhel BUILD file

---
 third_party/tensorrt/local/BUILD | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/third_party/tensorrt/local/BUILD b/third_party/tensorrt/local/BUILD
index c317e16688..1967308243 100644
--- a/third_party/tensorrt/local/BUILD
+++ b/third_party/tensorrt/local/BUILD
@@ -329,7 +329,7 @@ cc_library(
     name = "nvinferplugin",
     srcs = select({
         ":aarch64_linux": ["lib/aarch64-linux-gnu/libnvinfer_plugin.so"],
-        ":ci_rhel_x86_64_linux": ["lib64/libnvinfer_plugin.so"],
+        ":ci_rhel_x86_64_linux": ["lib/libnvinfer_plugin.so"],
         ":windows": ["lib/nvinfer_plugin.dll"],
         "//conditions:default": ["lib/x86_64-linux-gnu/libnvinfer_plugin.so"],
     }),

From fa4fb9cea4946d702e4cb869e76942fbaf4bcfda Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 2 Apr 2024 07:40:28 -0700
Subject: [PATCH 024/122] chore: more updates

---
 third_party/tensorrt/local/BUILD | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/third_party/tensorrt/local/BUILD b/third_party/tensorrt/local/BUILD
index 1967308243..31aa906ba4 100644
--- a/third_party/tensorrt/local/BUILD
+++ b/third_party/tensorrt/local/BUILD
@@ -79,7 +79,7 @@ cc_import(
     name = "nvinfer_static_lib",
     static_library = select({
         ":aarch64_linux": "lib/aarch64-linux-gnu/libnvinfer_static.a",
-        ":ci_rhel_x86_64_linux": "lib64/libnvinfer_static.a",
+        ":ci_rhel_x86_64_linux": "lib/libnvinfer_static.a",
         ":windows": "lib/nvinfer.lib",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvinfer_static.a",
     }),
@@ -90,7 +90,7 @@ cc_import(
     name = "nvinfer_lib",
     shared_library = select({
         ":aarch64_linux": "lib/aarch64-linux-gnu/libnvinfer.so",
-        ":ci_rhel_x86_64_linux": "lib64/libnvinfer.so",
+        ":ci_rhel_x86_64_linux": "lib/libnvinfer.so",
         ":windows": "lib/nvinfer.dll",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvinfer.so",
     }),
@@ -113,7 +113,7 @@ cc_import(
     name = "nvparsers_lib",
     shared_library = select({
         ":aarch64_linux": "lib/aarch64-linux-gnu/libnvparsers.so",
-        ":ci_rhel_x86_64_linux": "lib64/libnvparsers.so",
+        ":ci_rhel_x86_64_linux": "lib/libnvparsers.so",
         ":windows": "lib/nvparsers.dll",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvparsers.so",
     }),
@@ -177,7 +177,7 @@ cc_import(
     name = "nvonnxparser_lib",
     shared_library = select({
         ":aarch64_linux": "lib/aarch64-linux-gnu/libnvonnxparser.so",
-        ":ci_rhel_x86_64_linux": "lib64/libnvonnxparser.so",
+        ":ci_rhel_x86_64_linux": "lib/libnvonnxparser.so",
         ":windows": "lib/nvonnxparser.dll",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvonnxparser.so",
     }),
@@ -233,7 +233,7 @@ cc_import(
     name = "nvonnxparser_runtime_lib",
     shared_library = select({
         ":aarch64_linux": "lib/x86_64-linux-gnu/libnvonnxparser_runtime.so",
-        ":ci_rhel_x86_64_linux": "lib64/libnvonnxparser_runtime.so",
+        ":ci_rhel_x86_64_linux": "lib/libnvonnxparser_runtime.so",
         ":windows": "lib/nvonnxparser_runtime.dll",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvonnxparser_runtime.so",
     }),
@@ -281,7 +281,7 @@ cc_import(
     name = "nvcaffeparser_lib",
     shared_library = select({
         ":aarch64_linux": "lib/aarch64-linux-gnu/libnvcaffe_parsers.so",
-        ":ci_rhel_x86_64_linux": "lib64/libnvcaffe_parsers.so",
+        ":ci_rhel_x86_64_linux": "lib/libnvcaffe_parsers.so",
         ":windows": "lib/nvcaffe_parsers.dll",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvcaffe_parsers.so",
     }),

From e11eb60edd8718c775f23b753d658a43f83edbe5 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 2 Apr 2024 09:36:52 -0700
Subject: [PATCH 025/122] chore: fix TRT version

---
 dev_dep_versions.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/dev_dep_versions.yml b/dev_dep_versions.yml
index b07db5533f..e2434d0c45 100644
--- a/dev_dep_versions.yml
+++ b/dev_dep_versions.yml
@@ -1,4 +1,4 @@
 __version__: "2.3.0"
 __cuda_version__: "12.1"
 __cudnn_version__: "8.9"
-__tensorrt_version__: "10.0.0b6"
+__tensorrt_version__: "10.0"

From 092feb225e8844d94c5e7b11d65b5e413cf88c48 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 2 Apr 2024 09:50:03 -0700
Subject: [PATCH 026/122] chore: more updates

---
 dev_dep_versions.yml          | 2 +-
 packaging/pre_build_script.sh | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/dev_dep_versions.yml b/dev_dep_versions.yml
index e2434d0c45..b07db5533f 100644
--- a/dev_dep_versions.yml
+++ b/dev_dep_versions.yml
@@ -1,4 +1,4 @@
 __version__: "2.3.0"
 __cuda_version__: "12.1"
 __cudnn_version__: "8.9"
-__tensorrt_version__: "10.0"
+__tensorrt_version__: "10.0.0b6"
diff --git a/packaging/pre_build_script.sh b/packaging/pre_build_script.sh
index 18cd5d9fe2..9bab9a58c3 100755
--- a/packaging/pre_build_script.sh
+++ b/packaging/pre_build_script.sh
@@ -5,7 +5,7 @@ python3 -m pip install pyyaml
 TRT_VERSION=$(python3 -c "import versions; versions.tensorrt_version()")
 yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo
 yum check-update
-yum install -y ninja-build gettext tensorrt-${TRT_VERSION}.*
+yum install -y ninja-build gettext tensorrt-${TRT_VERSION}
 wget https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-linux-amd64 \
     && mv bazelisk-linux-amd64 /usr/bin/bazel \
     && chmod +x /usr/bin/bazel

From 09ecf263741fb0e945033f602c424a2e5aabb4ad Mon Sep 17 00:00:00 2001
From: Evan Li <zewenl@nvidia.com>
Date: Wed, 3 Apr 2024 00:32:54 +0000
Subject: [PATCH 027/122] fix shape bug in bitwise ops

---
 .../conversion/impl/elementwise/base.py       | 42 ++++++++++++++++---
 1 file changed, 36 insertions(+), 6 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py b/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
index 615cd0bd62..f93ec52504 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
@@ -7,12 +7,13 @@
 import torch
 from torch.fx.node import Target
 from torch_tensorrt.dynamo._SourceIR import SourceIR
+from torch_tensorrt.dynamo.conversion import impl
 from torch_tensorrt.dynamo.conversion._ConversionContext import ConversionContext
 from torch_tensorrt.dynamo.conversion.converter_utils import (
     cast_trt_tensor,
     get_trt_tensor,
 )
-from torch_tensorrt.fx.converters.converter_utils import broadcast, set_layer_name
+from torch_tensorrt.fx.converters.converter_utils import set_layer_name
 from torch_tensorrt.fx.types import TRTElementWiseOp, TRTTensor
 from torch_tensorrt.fx.utils import Frameworks, unified_dtype_converter
 
@@ -140,16 +141,45 @@ def convert_binary_elementwise(
 
     if trt_promoted_type != lhs_val.dtype:
         lhs_val = cast_trt_tensor(
-            ctx, lhs_val, trt_promoted_type, name, target, source_ir
+            ctx, lhs_val, trt_promoted_type, f"{name}_cast_lhs_val", target, source_ir
         )
     if trt_promoted_type != rhs_val.dtype:
         rhs_val = cast_trt_tensor(
-            ctx, rhs_val, trt_promoted_type, name, target, source_ir
+            ctx, rhs_val, trt_promoted_type, f"{name}_cast_rhs_val", target, source_ir
         )
 
-    lhs_val, rhs_val = broadcast(
-        ctx.net, lhs_val, rhs_val, f"{name}_lhs", f"{name}_rhs"
-    )
+    lhs_val_shape = lhs_val.shape
+    rhs_val_shape = rhs_val.shape
+    rank_diff = len(lhs_val_shape) - len(rhs_val_shape)
+    if rank_diff > 0:
+        rhs_val = impl.slice.expand(
+            ctx, target, source_ir, f"{name}_expand_rhs_val", rhs_val, lhs_val_shape
+        )
+    elif rank_diff < 0:
+        lhs_val = impl.slice.expand(
+            ctx, target, source_ir, f"{name}_expand_lhs_val", lhs_val, rhs_val_shape
+        )
+    else:
+        if tuple(lhs_val_shape) != tuple(rhs_val_shape):
+            sum_diff = sum(lhs_val_shape) - sum(rhs_val_shape)
+            if sum_diff > 0:
+                rhs_val = impl.slice.expand(
+                    ctx,
+                    target,
+                    source_ir,
+                    f"{name}_expand_rhs_val",
+                    rhs_val,
+                    lhs_val_shape,
+                )
+            elif sum_diff < 0:
+                lhs_val = impl.slice.expand(
+                    ctx,
+                    target,
+                    source_ir,
+                    f"{name}_expand_lhs_val",
+                    lhs_val,
+                    rhs_val_shape,
+                )
 
     layer = ctx.net.add_elementwise(lhs_val, rhs_val, op_type)
     set_layer_name(layer, target, name, source_ir)

From 85e04c5d5697e60395b79829cf80322da1de41f9 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 2 Apr 2024 19:07:46 -0700
Subject: [PATCH 028/122] chore: update to rhel9

---
 packaging/pre_build_script.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/packaging/pre_build_script.sh b/packaging/pre_build_script.sh
index 9bab9a58c3..ae73d2b773 100755
--- a/packaging/pre_build_script.sh
+++ b/packaging/pre_build_script.sh
@@ -3,7 +3,7 @@
 # Install dependencies
 python3 -m pip install pyyaml
 TRT_VERSION=$(python3 -c "import versions; versions.tensorrt_version()")
-yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo
+yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel9/x86_64/cuda-rhel9.repo
 yum check-update
 yum install -y ninja-build gettext tensorrt-${TRT_VERSION}
 wget https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-linux-amd64 \

From 41229d63ae3465304f451a0b43703ea9754e0d97 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 2 Apr 2024 19:26:52 -0700
Subject: [PATCH 029/122] chore: change trt version

---
 dev_dep_versions.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/dev_dep_versions.yml b/dev_dep_versions.yml
index b07db5533f..4bbfe9d188 100644
--- a/dev_dep_versions.yml
+++ b/dev_dep_versions.yml
@@ -1,4 +1,4 @@
 __version__: "2.3.0"
 __cuda_version__: "12.1"
 __cudnn_version__: "8.9"
-__tensorrt_version__: "10.0.0b6"
+__tensorrt_version__: "10.0.0.6"

From 9d7a65618a039802eb568264eccf1be4172a3750 Mon Sep 17 00:00:00 2001
From: Evan Li <zewenl@nvidia.com>
Date: Wed, 3 Apr 2024 18:23:40 +0000
Subject: [PATCH 030/122] fix test bug and add more tests

---
 tests/py/dynamo/conversion/test_arange_aten.py | 8 ++++++--
 1 file changed, 6 insertions(+), 2 deletions(-)

diff --git a/tests/py/dynamo/conversion/test_arange_aten.py b/tests/py/dynamo/conversion/test_arange_aten.py
index 035b957865..e06239eb4e 100644
--- a/tests/py/dynamo/conversion/test_arange_aten.py
+++ b/tests/py/dynamo/conversion/test_arange_aten.py
@@ -15,14 +15,18 @@ class TestArangeConverter(DispatchTestCase):
             (5, 0, -1),
             (5, 1, -2),
             (5, 3, -3),
+            (5, -2, -1),
+            (-5, -2, 2),
+            (-5, -3, 1),
+            (-2, -5, -1),
         ]
     )
     def test_arange(self, start, end, step):
         class Arange(nn.Module):
             def forward(self, x):
-                return torch.ops.aten.arange.start_step(start, x.shape[0], step)
+                return torch.ops.aten.arange.start_step(start, end, step)
 
-        inputs = [torch.randn(end, 1)]
+        inputs = [torch.randn(1, 1)]
         self.run_test(
             Arange(),
             inputs,

From 5e911a9765c4aad015a6075afd4b30bcca1efa79 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 3 Apr 2024 11:35:30 -0700
Subject: [PATCH 031/122] chore: delete mirror of rules_pkg

---
 WORKSPACE                          | 1 -
 third_party/tensorrt/archive/BUILD | 2 --
 2 files changed, 3 deletions(-)

diff --git a/WORKSPACE b/WORKSPACE
index 95abcea2d3..13c07a6008 100644
--- a/WORKSPACE
+++ b/WORKSPACE
@@ -17,7 +17,6 @@ http_archive(
     name = "rules_pkg",
     sha256 = "8f9ee2dc10c1ae514ee599a8b42ed99fa262b757058f65ad3c384289ff70c4b8",
     urls = [
-        "https://mirror.bazel.build/github.com/bazelbuild/rules_pkg/releases/download/0.9.1/rules_pkg-0.9.1.tar.gz",
         "https://github.com/bazelbuild/rules_pkg/releases/download/0.9.1/rules_pkg-0.9.1.tar.gz",
     ],
 )
diff --git a/third_party/tensorrt/archive/BUILD b/third_party/tensorrt/archive/BUILD
index 221f2ce4b3..5c07794a20 100644
--- a/third_party/tensorrt/archive/BUILD
+++ b/third_party/tensorrt/archive/BUILD
@@ -45,7 +45,6 @@ cc_library(
         "nvinfer_headers",
         "nvinfer_lib",
         "@cuda//:cudart",
-        "@cudnn",
     ],
 )
 
@@ -182,6 +181,5 @@ cc_library(
         "nvinferplugin_headers",
         "nvinferplugin_lib",
         "@cuda//:cudart",
-        "@cudnn",
     ],
 )

From dae0eb2321418e575c826231ce2d2e5194837f06 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 3 Apr 2024 16:10:12 -0700
Subject: [PATCH 032/122] chore: fix conv test

---
 tests/core/conversion/converters/test_conv_deconv.cpp | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/core/conversion/converters/test_conv_deconv.cpp b/tests/core/conversion/converters/test_conv_deconv.cpp
index 27baa1df5e..faaf7f2474 100644
--- a/tests/core/conversion/converters/test_conv_deconv.cpp
+++ b/tests/core/conversion/converters/test_conv_deconv.cpp
@@ -126,13 +126,13 @@ TEST(Converters, ATenConv1dWithWeightTensorsConvertsCorrectly) {
         %5 : int = prim::Constant[value=127]()
         %quant_input : Tensor = aten::fake_quantize_per_tensor_affine(%0, %3, %4, %2, %5)
         %6 : int = prim::Constant[value=6]()
-        %7 : int = prim::Constant[value=5]()
+        %7 : int = prim::Constant[value=4]()
         %8 : Device = prim::Constant[value="cuda:0"]()
         %9 : None = prim::Constant()
         %10 : int[] = prim::ListConstruct(%7)
         %11 : Tensor = aten::full(%10, %3, %6, %9, %8, %9)
         %12 : int[] = prim::ListConstruct(%7)
-        %13 : int = prim::Constant[value=1]()
+        %13 : int = prim::Constant[value=0]()
         %14 : Tensor = aten::full(%12, %13, %6, %9, %8, %9)
         %quant_wts : Tensor = aten::fake_quantize_per_channel_affine(%1, %11, %14, %13, %2, %5)
         %15 : None = prim::Constant()

From 4676cd2d289f23870aa0b1e6829ad498e6855146 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 3 Apr 2024 17:06:25 -0700
Subject: [PATCH 033/122] chore: fix trt version range

---
 py/requirements.txt | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/py/requirements.txt b/py/requirements.txt
index 565395b59b..19c39c8647 100644
--- a/py/requirements.txt
+++ b/py/requirements.txt
@@ -5,5 +5,5 @@ pybind11==2.6.2
 torch==2.3.0
 torchvision==0.18.0
 --extra-index-url https://pypi.ngc.nvidia.com
-tensorrt==10.0.0b6
+tensorrt>=10.0
 pyyaml

From 88efe8e7258c4af254299c7ba37f4af4176cba5b Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 3 Apr 2024 17:10:04 -0700
Subject: [PATCH 034/122] chore: fix trt rangfe

---
 pyproject.toml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 7468484f48..05404f87b7 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,7 +8,7 @@ requires = [
     "cffi>=1.15.1",
     "typing-extensions>=4.7.0",
     "future>=0.18.3",
-    "tensorrt==10.0.0b6",
+    "tensorrt>=10.0",
     "torch >=2.3.0.dev,<2.4.0",
     "pybind11==2.6.2",
     "numpy",

From f9b40e672da686591830b7a1bef1280231af6a2b Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 3 Apr 2024 17:18:01 -0700
Subject: [PATCH 035/122] chore: minor fix

---
 pyproject.toml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 05404f87b7..7a78047be7 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -9,7 +9,7 @@ requires = [
     "typing-extensions>=4.7.0",
     "future>=0.18.3",
     "tensorrt>=10.0",
-    "torch >=2.3.0.dev,<2.4.0",
+    "torch>=2.3.0.dev,<2.4.0",
     "pybind11==2.6.2",
     "numpy",
 ]
@@ -42,7 +42,7 @@ requires-python = ">=3.8"
 keywords = ["pytorch", "torch", "tensorrt", "trt", "ai", "artificial intelligence", "ml", "machine learning", "dl", "deep learning", "compiler", "dynamo", "torchscript", "inference"]
 dependencies = [
     "torch >=2.3.0.dev,<2.4.0",
-    "tensorrt==10.0.0b6",
+    "tensorrt>=10.0",
     "packaging>=23",
     "numpy",
     "typing-extensions>=4.7.0",

From b86aec27a3c8932d94222ca970d0f4178f742841 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 4 Apr 2024 10:26:46 -0700
Subject: [PATCH 036/122] chore: update rules_pkg

---
 WORKSPACE | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/WORKSPACE b/WORKSPACE
index 13c07a6008..4a7a1556d3 100644
--- a/WORKSPACE
+++ b/WORKSPACE
@@ -15,9 +15,9 @@ py_repositories()
 
 http_archive(
     name = "rules_pkg",
-    sha256 = "8f9ee2dc10c1ae514ee599a8b42ed99fa262b757058f65ad3c384289ff70c4b8",
+    sha256 = "d250924a2ecc5176808fc4c25d5cf5e9e79e6346d79d5ab1c493e289e722d1d0",
     urls = [
-        "https://github.com/bazelbuild/rules_pkg/releases/download/0.9.1/rules_pkg-0.9.1.tar.gz",
+        "https://github.com/bazelbuild/rules_pkg/releases/download/0.10.1/rules_pkg-0.10.1.tar.gz",
     ],
 )
 

From 6630281671d52adb765e4d816a8d5315bfbbc6ce Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 4 Apr 2024 13:16:53 -0700
Subject: [PATCH 037/122] chore: minor fixes

---
 WORKSPACE                                              | 4 ++--
 py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py | 1 +
 2 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/WORKSPACE b/WORKSPACE
index 4a7a1556d3..13c07a6008 100644
--- a/WORKSPACE
+++ b/WORKSPACE
@@ -15,9 +15,9 @@ py_repositories()
 
 http_archive(
     name = "rules_pkg",
-    sha256 = "d250924a2ecc5176808fc4c25d5cf5e9e79e6346d79d5ab1c493e289e722d1d0",
+    sha256 = "8f9ee2dc10c1ae514ee599a8b42ed99fa262b757058f65ad3c384289ff70c4b8",
     urls = [
-        "https://github.com/bazelbuild/rules_pkg/releases/download/0.10.1/rules_pkg-0.10.1.tar.gz",
+        "https://github.com/bazelbuild/rules_pkg/releases/download/0.9.1/rules_pkg-0.9.1.tar.gz",
     ],
 )
 
diff --git a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
index ffcc9c195e..a1f6614c85 100644
--- a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
+++ b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
@@ -188,6 +188,7 @@ def run(
             if self.compilation_settings.version_compatible:
                 _LOGGER.info("Using version compatible")
                 builder_config.set_flag(trt.BuilderFlag.VERSION_COMPATIBLE)
+                builder_config.set_flag(trt.BuilderFlag.EXCLUDE_LEAN_RUNTIME)
             if self.compilation_settings.hardware_compatible:
                 _LOGGER.info("Using hardware compatible")
                 builder_config.hardware_compatibility_level = (

From fca55fe06bcba9d9282f275a2aa713f94a73b500 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 4 Apr 2024 14:22:06 -0700
Subject: [PATCH 038/122] chore: expt

---
 WORKSPACE                          | 17 +++++++++++++---
 third_party/tensorrt/archive/BUILD |  2 ++
 third_party/tensorrt/local/BUILD   | 32 ++++++++++++++++++++----------
 3 files changed, 37 insertions(+), 14 deletions(-)

diff --git a/WORKSPACE b/WORKSPACE
index 13c07a6008..edc5c9a050 100644
--- a/WORKSPACE
+++ b/WORKSPACE
@@ -17,6 +17,7 @@ http_archive(
     name = "rules_pkg",
     sha256 = "8f9ee2dc10c1ae514ee599a8b42ed99fa262b757058f65ad3c384289ff70c4b8",
     urls = [
+        "https://mirror.bazel.build/github.com/bazelbuild/rules_pkg/releases/download/0.9.1/rules_pkg-0.9.1.tar.gz",
         "https://github.com/bazelbuild/rules_pkg/releases/download/0.9.1/rules_pkg-0.9.1.tar.gz",
     ],
 )
@@ -67,13 +68,23 @@ http_archive(
 # Either place them in the distdir directory in third_party and use the --distdir flag
 # or modify the urls to "file:///<PATH TO TARBALL>/<TARBALL NAME>.tar.gz
 
+http_archive(
+    name = "cudnn",
+    build_file = "@//third_party/cudnn/archive:BUILD",
+    sha256 = "2a2eb89a2ab51071151c6082f1e816c702167a711a9372f9f73a7b5c4b06e01a",
+    strip_prefix = "cudnn-linux-x86_64-8.9.5.30_cuda12-archive",
+    urls = [
+        "https://developer.nvidia.com/downloads/compute/cudnn/secure/8.9.5/local_installers/12.x/cudnn-linux-x86_64-8.9.5.30_cuda12-archive.tar.xz",
+    ],
+)
+
 http_archive(
     name = "tensorrt",
     build_file = "@//third_party/tensorrt/archive:BUILD",
-    sha256 = "7ad5c8eab8fe8803bef5d8cee54ec1f407797ac8edb8ea3186cb9f24af726486",
-    strip_prefix = "TensorRT-10.0.0.6",
+    sha256 = "0f8157a5fc5329943b338b893591373350afa90ca81239cdadd7580cd1eba254",
+    strip_prefix = "TensorRT-8.6.1.6",
     urls = [
-        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.0/tars/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz",
+        "https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/secure/8.6.1/tars/TensorRT-8.6.1.6.Linux.x86_64-gnu.cuda-12.0.tar.gz",
     ],
 )
 
diff --git a/third_party/tensorrt/archive/BUILD b/third_party/tensorrt/archive/BUILD
index 5c07794a20..221f2ce4b3 100644
--- a/third_party/tensorrt/archive/BUILD
+++ b/third_party/tensorrt/archive/BUILD
@@ -45,6 +45,7 @@ cc_library(
         "nvinfer_headers",
         "nvinfer_lib",
         "@cuda//:cudart",
+        "@cudnn",
     ],
 )
 
@@ -181,5 +182,6 @@ cc_library(
         "nvinferplugin_headers",
         "nvinferplugin_lib",
         "@cuda//:cudart",
+        "@cudnn",
     ],
 )
diff --git a/third_party/tensorrt/local/BUILD b/third_party/tensorrt/local/BUILD
index 31aa906ba4..9cbe98a41e 100644
--- a/third_party/tensorrt/local/BUILD
+++ b/third_party/tensorrt/local/BUILD
@@ -29,7 +29,9 @@ config_setting(
 cc_library(
     name = "nvinfer_headers",
     hdrs = select({
-        ":aarch64_linux": glob(
+        ":aarch64_linux": [
+            "include/aarch64-linux-gnu/NvUtils.h",
+        ] + glob(
             [
                 "include/aarch64-linux-gnu/NvInfer*.h",
             ],
@@ -38,7 +40,9 @@ cc_library(
                 "include/aarch64-linux-gnu/NvInferPluginUtils.h",
             ],
         ),
-        ":ci_rhel_x86_64_linux": glob(
+        ":ci_rhel_x86_64_linux": [
+            "include/NvUtils.h",
+        ] + glob(
             [
                 "include/NvInfer*.h",
             ],
@@ -47,7 +51,9 @@ cc_library(
                 "include/NvInferPluginUtils.h",
             ],
         ),
-        ":windows": glob(
+        ":windows": [
+            "include/NvUtils.h",
+        ] + glob(
             [
                 "include/NvInfer*.h",
             ],
@@ -56,7 +62,9 @@ cc_library(
                 "include/NvInferPluginUtils.h",
             ],
         ),
-        "//conditions:default": glob(
+        "//conditions:default": [
+            "include/x86_64-linux-gnu/NvUtils.h",
+        ] + glob(
             [
                 "include/x86_64-linux-gnu/NvInfer*.h",
             ],
@@ -79,7 +87,7 @@ cc_import(
     name = "nvinfer_static_lib",
     static_library = select({
         ":aarch64_linux": "lib/aarch64-linux-gnu/libnvinfer_static.a",
-        ":ci_rhel_x86_64_linux": "lib/libnvinfer_static.a",
+        ":ci_rhel_x86_64_linux": "lib64/libnvinfer_static.a",
         ":windows": "lib/nvinfer.lib",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvinfer_static.a",
     }),
@@ -90,7 +98,7 @@ cc_import(
     name = "nvinfer_lib",
     shared_library = select({
         ":aarch64_linux": "lib/aarch64-linux-gnu/libnvinfer.so",
-        ":ci_rhel_x86_64_linux": "lib/libnvinfer.so",
+        ":ci_rhel_x86_64_linux": "lib64/libnvinfer.so",
         ":windows": "lib/nvinfer.dll",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvinfer.so",
     }),
@@ -104,6 +112,7 @@ cc_library(
         "nvinfer_headers",
         "nvinfer_lib",
         "@cuda//:cudart",
+        "@cudnn",
     ],
 )
 
@@ -113,7 +122,7 @@ cc_import(
     name = "nvparsers_lib",
     shared_library = select({
         ":aarch64_linux": "lib/aarch64-linux-gnu/libnvparsers.so",
-        ":ci_rhel_x86_64_linux": "lib/libnvparsers.so",
+        ":ci_rhel_x86_64_linux": "lib64/libnvparsers.so",
         ":windows": "lib/nvparsers.dll",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvparsers.so",
     }),
@@ -177,7 +186,7 @@ cc_import(
     name = "nvonnxparser_lib",
     shared_library = select({
         ":aarch64_linux": "lib/aarch64-linux-gnu/libnvonnxparser.so",
-        ":ci_rhel_x86_64_linux": "lib/libnvonnxparser.so",
+        ":ci_rhel_x86_64_linux": "lib64/libnvonnxparser.so",
         ":windows": "lib/nvonnxparser.dll",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvonnxparser.so",
     }),
@@ -233,7 +242,7 @@ cc_import(
     name = "nvonnxparser_runtime_lib",
     shared_library = select({
         ":aarch64_linux": "lib/x86_64-linux-gnu/libnvonnxparser_runtime.so",
-        ":ci_rhel_x86_64_linux": "lib/libnvonnxparser_runtime.so",
+        ":ci_rhel_x86_64_linux": "lib64/libnvonnxparser_runtime.so",
         ":windows": "lib/nvonnxparser_runtime.dll",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvonnxparser_runtime.so",
     }),
@@ -281,7 +290,7 @@ cc_import(
     name = "nvcaffeparser_lib",
     shared_library = select({
         ":aarch64_linux": "lib/aarch64-linux-gnu/libnvcaffe_parsers.so",
-        ":ci_rhel_x86_64_linux": "lib/libnvcaffe_parsers.so",
+        ":ci_rhel_x86_64_linux": "lib64/libnvcaffe_parsers.so",
         ":windows": "lib/nvcaffe_parsers.dll",
         "//conditions:default": "lib/x86_64-linux-gnu/libnvcaffe_parsers.so",
     }),
@@ -329,7 +338,7 @@ cc_library(
     name = "nvinferplugin",
     srcs = select({
         ":aarch64_linux": ["lib/aarch64-linux-gnu/libnvinfer_plugin.so"],
-        ":ci_rhel_x86_64_linux": ["lib/libnvinfer_plugin.so"],
+        ":ci_rhel_x86_64_linux": ["lib64/libnvinfer_plugin.so"],
         ":windows": ["lib/nvinfer_plugin.dll"],
         "//conditions:default": ["lib/x86_64-linux-gnu/libnvinfer_plugin.so"],
     }),
@@ -357,6 +366,7 @@ cc_library(
     deps = [
         "nvinfer",
         "@cuda//:cudart",
+        "@cudnn",
     ],
     alwayslink = True,
 )

From 1ca01e782915a8073f546e53b9f171e9675e4731 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 4 Apr 2024 18:19:23 -0700
Subject: [PATCH 039/122] chore: update WORKSPACE tmpl

---
 toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl | 1 -
 1 file changed, 1 deletion(-)

diff --git a/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl b/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl
index 8ff4f74aaf..4a37bb6091 100644
--- a/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl
+++ b/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl
@@ -17,7 +17,6 @@ http_archive(
     name = "rules_pkg",
     sha256 = "8f9ee2dc10c1ae514ee599a8b42ed99fa262b757058f65ad3c384289ff70c4b8",
     urls = [
-        "https://mirror.bazel.build/github.com/bazelbuild/rules_pkg/releases/download/0.9.1/rules_pkg-0.9.1.tar.gz",
         "https://github.com/bazelbuild/rules_pkg/releases/download/0.9.1/rules_pkg-0.9.1.tar.gz",
     ],
 )

From 6ffb85ee051604aa5c57d8c8802bc47525fcc22d Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 5 Apr 2024 16:50:34 -0700
Subject: [PATCH 040/122] chore: fix

---
 packaging/pre_build_script.sh | 3 ++-
 pyproject.toml                | 4 ++--
 2 files changed, 4 insertions(+), 3 deletions(-)

diff --git a/packaging/pre_build_script.sh b/packaging/pre_build_script.sh
index ae73d2b773..41fb47ff79 100755
--- a/packaging/pre_build_script.sh
+++ b/packaging/pre_build_script.sh
@@ -2,10 +2,11 @@
 
 # Install dependencies
 python3 -m pip install pyyaml
+yum install -y ninja-build gettext
 TRT_VERSION=$(python3 -c "import versions; versions.tensorrt_version()")
 yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel9/x86_64/cuda-rhel9.repo
 yum check-update
-yum install -y ninja-build gettext tensorrt-${TRT_VERSION}
+yum install tensorrt-${TRT_VERSION}
 wget https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-linux-amd64 \
     && mv bazelisk-linux-amd64 /usr/bin/bazel \
     && chmod +x /usr/bin/bazel
diff --git a/pyproject.toml b/pyproject.toml
index 1e29a43565..dd4cada7f2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,7 +8,7 @@ requires = [
     "cffi>=1.15.1",
     "typing-extensions>=4.7.0",
     "future>=0.18.3",
-    "tensorrt>=8.6,<8.7",
+    "tensorrt==10.0.0b6",
     "torch==2.3.0",
     "pybind11==2.6.2",
     "numpy",
@@ -42,7 +42,7 @@ requires-python = ">=3.8"
 keywords = ["pytorch", "torch", "tensorrt", "trt", "ai", "artificial intelligence", "ml", "machine learning", "dl", "deep learning", "compiler", "dynamo", "torchscript", "inference"]
 dependencies = [
     "torch==2.3.0",
-    "tensorrt>=8.6,<8.7",
+    "tensorrt==10.0.0b6",
     "packaging>=23",
     "numpy",
     "typing-extensions>=4.7.0",

From 76af510ebb7129460d70b759677673878d767c01 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 5 Apr 2024 17:05:18 -0700
Subject: [PATCH 041/122] chore: remove cudnn dep

---
 third_party/tensorrt/archive/BUILD | 2 --
 third_party/tensorrt/local/BUILD   | 2 --
 2 files changed, 4 deletions(-)

diff --git a/third_party/tensorrt/archive/BUILD b/third_party/tensorrt/archive/BUILD
index 221f2ce4b3..5c07794a20 100644
--- a/third_party/tensorrt/archive/BUILD
+++ b/third_party/tensorrt/archive/BUILD
@@ -45,7 +45,6 @@ cc_library(
         "nvinfer_headers",
         "nvinfer_lib",
         "@cuda//:cudart",
-        "@cudnn",
     ],
 )
 
@@ -182,6 +181,5 @@ cc_library(
         "nvinferplugin_headers",
         "nvinferplugin_lib",
         "@cuda//:cudart",
-        "@cudnn",
     ],
 )
diff --git a/third_party/tensorrt/local/BUILD b/third_party/tensorrt/local/BUILD
index 9cbe98a41e..5136563521 100644
--- a/third_party/tensorrt/local/BUILD
+++ b/third_party/tensorrt/local/BUILD
@@ -112,7 +112,6 @@ cc_library(
         "nvinfer_headers",
         "nvinfer_lib",
         "@cuda//:cudart",
-        "@cudnn",
     ],
 )
 
@@ -366,7 +365,6 @@ cc_library(
     deps = [
         "nvinfer",
         "@cuda//:cudart",
-        "@cudnn",
     ],
     alwayslink = True,
 )

From f9cf75ae8b7c91d88195b182fda784fb6fcce792 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 5 Apr 2024 17:20:35 -0700
Subject: [PATCH 042/122] chore: fix

---
 third_party/tensorrt/local/BUILD | 16 ++++------------
 1 file changed, 4 insertions(+), 12 deletions(-)

diff --git a/third_party/tensorrt/local/BUILD b/third_party/tensorrt/local/BUILD
index 5136563521..c317e16688 100644
--- a/third_party/tensorrt/local/BUILD
+++ b/third_party/tensorrt/local/BUILD
@@ -29,9 +29,7 @@ config_setting(
 cc_library(
     name = "nvinfer_headers",
     hdrs = select({
-        ":aarch64_linux": [
-            "include/aarch64-linux-gnu/NvUtils.h",
-        ] + glob(
+        ":aarch64_linux": glob(
             [
                 "include/aarch64-linux-gnu/NvInfer*.h",
             ],
@@ -40,9 +38,7 @@ cc_library(
                 "include/aarch64-linux-gnu/NvInferPluginUtils.h",
             ],
         ),
-        ":ci_rhel_x86_64_linux": [
-            "include/NvUtils.h",
-        ] + glob(
+        ":ci_rhel_x86_64_linux": glob(
             [
                 "include/NvInfer*.h",
             ],
@@ -51,9 +47,7 @@ cc_library(
                 "include/NvInferPluginUtils.h",
             ],
         ),
-        ":windows": [
-            "include/NvUtils.h",
-        ] + glob(
+        ":windows": glob(
             [
                 "include/NvInfer*.h",
             ],
@@ -62,9 +56,7 @@ cc_library(
                 "include/NvInferPluginUtils.h",
             ],
         ),
-        "//conditions:default": [
-            "include/x86_64-linux-gnu/NvUtils.h",
-        ] + glob(
+        "//conditions:default": glob(
             [
                 "include/x86_64-linux-gnu/NvInfer*.h",
             ],

From 33ba8b2c619b57f151d6eba74dfc885f8af03d2a Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 8 Apr 2024 14:27:27 -0700
Subject: [PATCH 043/122] chore: updates

---
 packaging/pre_build_script.sh                       |  6 +++---
 .../WORKSPACE.x86_64.release.rhel.tmpl              | 13 +++++--------
 2 files changed, 8 insertions(+), 11 deletions(-)

diff --git a/packaging/pre_build_script.sh b/packaging/pre_build_script.sh
index 41fb47ff79..5905e44d2e 100755
--- a/packaging/pre_build_script.sh
+++ b/packaging/pre_build_script.sh
@@ -4,9 +4,9 @@
 python3 -m pip install pyyaml
 yum install -y ninja-build gettext
 TRT_VERSION=$(python3 -c "import versions; versions.tensorrt_version()")
-yum-config-manager --add-repo https://developer.download.nvidia.com/compute/cuda/repos/rhel9/x86_64/cuda-rhel9.repo
-yum check-update
-yum install tensorrt-${TRT_VERSION}
+wget -P /opt/torch-tensorrt-builds/ https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.0/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz
+tar -xvzf /opt/torch-tensorrt-builds/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz -C /opt/torch-tensorrt-builds/
+export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
 wget https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-linux-amd64 \
     && mv bazelisk-linux-amd64 /usr/bin/bazel \
     && chmod +x /usr/bin/bazel
diff --git a/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl b/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl
index 4a37bb6091..cad54b1707 100644
--- a/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl
+++ b/toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl
@@ -68,14 +68,11 @@ http_archive(
     urls = ["https://download.pytorch.org/libtorch/test/cu121/libtorch-shared-with-deps-2.3.0%2Bcu121.zip"],
 )
 
-####################################################################################
-# Locally installed dependencies (use in cases of custom dependencies or aarch64)
-####################################################################################
-
-new_local_repository(
-   name = "tensorrt",
-   path = "/usr/",
-   build_file = "@//third_party/tensorrt/local:BUILD"
+http_archive(
+    name = "tensorrt",
+    urls = ["file:////opt/torch-tensorrt-builds/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz",],
+    build_file = "@//third_party/tensorrt/archive:BUILD",
+    strip_prefix = "TensorRT-10.0.0.6"
 )
 
 # #########################################################################

From 923377c86e5a664ac13c992188c91748fcc44b07 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 8 Apr 2024 21:44:50 -0700
Subject: [PATCH 044/122] chore: update post-build script

---
 .github/workflows/build-test.yml | 8 +++++++-
 packaging/post_build_script.sh   | 1 +
 2 files changed, 8 insertions(+), 1 deletion(-)

diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml
index 5573bb8d28..febc475c09 100644
--- a/.github/workflows/build-test.yml
+++ b/.github/workflows/build-test.yml
@@ -36,7 +36,7 @@ jobs:
           - repository: pytorch/tensorrt
             pre-script: packaging/pre_build_script.sh
             env-var-script: packaging/env_vars.txt
-            post-script: ""
+            post-script: packaging/post_build_script.sh
             smoke-test-script: ""
             package-name: torch_tensorrt
     name: Build torch-tensorrt whl package
@@ -64,6 +64,7 @@ jobs:
           - repository: pytorch/tensorrt
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
+            post-script: packaging/post_build_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
     with:
       job-name: tests-py-torchscript-fe
@@ -99,6 +100,7 @@ jobs:
           - repository: pytorch/tensorrt
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
+            post-script: packaging/post_build_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
     with:
       job-name: tests-py-dynamo-converters
@@ -126,6 +128,7 @@ jobs:
           - repository: pytorch/tensorrt
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
+            post-script: packaging/post_build_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
     with:
       job-name: tests-py-dynamo-fe
@@ -154,6 +157,7 @@ jobs:
           - repository: pytorch/tensorrt
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
+            post-script: packaging/post_build_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
     with:
       job-name: tests-py-dynamo-serde
@@ -181,6 +185,7 @@ jobs:
           - repository: pytorch/tensorrt
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
+            post-script: packaging/post_build_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
     with:
       job-name: tests-py-torch-compile-be
@@ -209,6 +214,7 @@ jobs:
           - repository: pytorch/tensorrt
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
+            post-script: packaging/post_build_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
     with:
       job-name: tests-py-dynamo-core
diff --git a/packaging/post_build_script.sh b/packaging/post_build_script.sh
index e69de29bb2..c42774070a 100644
--- a/packaging/post_build_script.sh
+++ b/packaging/post_build_script.sh
@@ -0,0 +1 @@
+python -m pip install /opt/torch-tensorrt-builds/TensorRT-10.0.0.6/python/tensorrt-10.0.0b6-cp38-none-linux_x86_64.whl
\ No newline at end of file

From 89f04dbbaf50075e7f4c0e5f4fe86f04ada43f2c Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 8 Apr 2024 22:07:54 -0700
Subject: [PATCH 045/122] chore: remove trt dep

---
 pyproject.toml | 2 --
 1 file changed, 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index dd4cada7f2..acad8561c6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,7 +8,6 @@ requires = [
     "cffi>=1.15.1",
     "typing-extensions>=4.7.0",
     "future>=0.18.3",
-    "tensorrt==10.0.0b6",
     "torch==2.3.0",
     "pybind11==2.6.2",
     "numpy",
@@ -42,7 +41,6 @@ requires-python = ">=3.8"
 keywords = ["pytorch", "torch", "tensorrt", "trt", "ai", "artificial intelligence", "ml", "machine learning", "dl", "deep learning", "compiler", "dynamo", "torchscript", "inference"]
 dependencies = [
     "torch==2.3.0",
-    "tensorrt==10.0.0b6",
     "packaging>=23",
     "numpy",
     "typing-extensions>=4.7.0",

From 7620acca4d2d73e01d3edf9af9bf51dc29075d5b Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 8 Apr 2024 22:20:14 -0700
Subject: [PATCH 046/122] chore: updates

---
 packaging/pre_build_script.sh | 2 +-
 py/requirements.txt           | 7 ++++++-
 2 files changed, 7 insertions(+), 2 deletions(-)

diff --git a/packaging/pre_build_script.sh b/packaging/pre_build_script.sh
index 5905e44d2e..3243afd69f 100755
--- a/packaging/pre_build_script.sh
+++ b/packaging/pre_build_script.sh
@@ -10,7 +10,7 @@ export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBR
 wget https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-linux-amd64 \
     && mv bazelisk-linux-amd64 /usr/bin/bazel \
     && chmod +x /usr/bin/bazel
-
+python -m pip install -r py/requirements.txt
 export TORCH_BUILD_NUMBER=$(python -c "import torch, urllib.parse as ul; print(ul.quote_plus(torch.__version__))")
 
 cat toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl | envsubst > WORKSPACE
diff --git a/py/requirements.txt b/py/requirements.txt
index 19c39c8647..360fdbb01d 100644
--- a/py/requirements.txt
+++ b/py/requirements.txt
@@ -5,5 +5,10 @@ pybind11==2.6.2
 torch==2.3.0
 torchvision==0.18.0
 --extra-index-url https://pypi.ngc.nvidia.com
-tensorrt>=10.0
 pyyaml
+# Extras
+ninja>=1.11.0
+cffi>=1.15.1
+pybind11==2.6.2
+wheel>=0.40.0
+future>=0.18.3

From 62332fb4236442ca8e08f8323cdad10c3bfec9c0 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 9 Apr 2024 00:17:52 -0700
Subject: [PATCH 047/122] chore: set ld_library path in post script

---
 packaging/post_build_script.sh | 1 +
 1 file changed, 1 insertion(+)

diff --git a/packaging/post_build_script.sh b/packaging/post_build_script.sh
index c42774070a..1ee8f77467 100644
--- a/packaging/post_build_script.sh
+++ b/packaging/post_build_script.sh
@@ -1 +1,2 @@
+export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
 python -m pip install /opt/torch-tensorrt-builds/TensorRT-10.0.0.6/python/tensorrt-10.0.0b6-cp38-none-linux_x86_64.whl
\ No newline at end of file

From 96a8bf61e4027634d8bd85f3e6a4411816912c81 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 9 Apr 2024 13:20:29 -0700
Subject: [PATCH 048/122] chore: updates

---
 packaging/pre_build_script.sh | 2 +-
 py/torch_tensorrt/__init__.py | 5 ++---
 2 files changed, 3 insertions(+), 4 deletions(-)

diff --git a/packaging/pre_build_script.sh b/packaging/pre_build_script.sh
index 3243afd69f..c518992ab6 100755
--- a/packaging/pre_build_script.sh
+++ b/packaging/pre_build_script.sh
@@ -3,7 +3,7 @@
 # Install dependencies
 python3 -m pip install pyyaml
 yum install -y ninja-build gettext
-TRT_VERSION=$(python3 -c "import versions; versions.tensorrt_version()")
+TRT_VERSION=10.0.0.6 #$(python3 -c "import versions; versions.tensorrt_version()")
 wget -P /opt/torch-tensorrt-builds/ https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.0/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz
 tar -xvzf /opt/torch-tensorrt-builds/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz -C /opt/torch-tensorrt-builds/
 export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
diff --git a/py/torch_tensorrt/__init__.py b/py/torch_tensorrt/__init__.py
index b9d2af39c5..f97de95d52 100644
--- a/py/torch_tensorrt/__init__.py
+++ b/py/torch_tensorrt/__init__.py
@@ -60,7 +60,7 @@ def _find_lib(name: str, paths: List[str]) -> str:
 
     elif sys.platform.startswith("linux"):
         LINUX_PATHS = ["/usr/local/cuda-12.1/lib64", "/usr/lib", "/usr/lib64"]
-
+        print("==== BOOL CHECK", "LD_LIBRARY_PATH" in os.environ)
         if "LD_LIBRARY_PATH" in os.environ:
             LINUX_PATHS += os.environ["LD_LIBRARY_PATH"].split(os.path.pathsep)
 
@@ -92,9 +92,8 @@ def _find_lib(name: str, paths: List[str]) -> str:
 from torch_tensorrt.runtime import *  # noqa: F403
 
 if version.parse(sanitized_torch_version()) >= version.parse("2.1.dev"):
-    from torch_tensorrt.dynamo import backend  # noqa: F401
-
     from torch_tensorrt import dynamo  # noqa: F401
+    from torch_tensorrt.dynamo import backend  # noqa: F401
 
 
 def _register_with_torch() -> None:

From 041f6a38e834bb94004c0a4910f08794a3024992 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 9 Apr 2024 13:48:58 -0700
Subject: [PATCH 049/122] chore: updates

---
 packaging/post_build_script.sh | 1 +
 py/torch_tensorrt/__init__.py  | 7 ++++++-
 2 files changed, 7 insertions(+), 1 deletion(-)

diff --git a/packaging/post_build_script.sh b/packaging/post_build_script.sh
index 1ee8f77467..0d5d045cd0 100644
--- a/packaging/post_build_script.sh
+++ b/packaging/post_build_script.sh
@@ -1,2 +1,3 @@
 export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
+echo $LD_LIBRARY_PATH
 python -m pip install /opt/torch-tensorrt-builds/TensorRT-10.0.0.6/python/tensorrt-10.0.0b6-cp38-none-linux_x86_64.whl
\ No newline at end of file
diff --git a/py/torch_tensorrt/__init__.py b/py/torch_tensorrt/__init__.py
index f97de95d52..01f310637b 100644
--- a/py/torch_tensorrt/__init__.py
+++ b/py/torch_tensorrt/__init__.py
@@ -60,7 +60,12 @@ def _find_lib(name: str, paths: List[str]) -> str:
 
     elif sys.platform.startswith("linux"):
         LINUX_PATHS = ["/usr/local/cuda-12.1/lib64", "/usr/lib", "/usr/lib64"]
-        print("==== BOOL CHECK", "LD_LIBRARY_PATH" in os.environ)
+        print(
+            "==== BOOL CHECK",
+            "LD_LIBRARY_PATH" in os.environ,
+            " path: ",
+            os.environ["LD_LIBRARY_PATH"],
+        )
         if "LD_LIBRARY_PATH" in os.environ:
             LINUX_PATHS += os.environ["LD_LIBRARY_PATH"].split(os.path.pathsep)
 

From 83e9a0bc4f7e4281da00ea56df03f965883e285a Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 9 Apr 2024 15:31:31 -0700
Subject: [PATCH 050/122] chore: disable smoke test

---
 .github/workflows/build-test.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml
index febc475c09..b05cb1e276 100644
--- a/.github/workflows/build-test.yml
+++ b/.github/workflows/build-test.yml
@@ -37,7 +37,7 @@ jobs:
             pre-script: packaging/pre_build_script.sh
             env-var-script: packaging/env_vars.txt
             post-script: packaging/post_build_script.sh
-            smoke-test-script: ""
+            smoke-test-script: packaging/smoke_test_script.sh
             package-name: torch_tensorrt
     name: Build torch-tensorrt whl package
     uses: pytorch/test-infra/.github/workflows/build_wheels_linux.yml@main

From e8529b057e7658654114e31a2e5fecca7ec0faf9 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 9 Apr 2024 15:51:56 -0700
Subject: [PATCH 051/122] chore: updates

---
 .github/workflows/build-test.yml | 16 ++++++++--------
 1 file changed, 8 insertions(+), 8 deletions(-)

diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml
index b05cb1e276..330006f76e 100644
--- a/.github/workflows/build-test.yml
+++ b/.github/workflows/build-test.yml
@@ -15,7 +15,7 @@ on:
 
 jobs:
   generate-matrix:
-    uses: pytorch/test-infra/.github/workflows/generate_binary_build_matrix.yml@main
+    uses: pytorch/test-infra/.github/workflows/generate_binary_build_matrix.yml@release/2.3
     with:
       package-type: wheel
       os: linux
@@ -40,7 +40,7 @@ jobs:
             smoke-test-script: packaging/smoke_test_script.sh
             package-name: torch_tensorrt
     name: Build torch-tensorrt whl package
-    uses: pytorch/test-infra/.github/workflows/build_wheels_linux.yml@main
+    uses: pytorch/test-infra/.github/workflows/build_wheels_linux.yml@release/2.3
     with:
       repository: ${{ matrix.repository }}
       ref: ""
@@ -65,7 +65,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
-    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
+    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-torchscript-fe
       repository: "pytorch/tensorrt"
@@ -101,7 +101,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
-    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
+    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-dynamo-converters
       repository: "pytorch/tensorrt"
@@ -129,7 +129,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
-    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
+    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-dynamo-fe
       repository: "pytorch/tensorrt"
@@ -158,7 +158,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
-    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
+    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-dynamo-serde
       repository: "pytorch/tensorrt"
@@ -186,7 +186,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
-    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
+    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-torch-compile-be
       repository: "pytorch/tensorrt"
@@ -215,7 +215,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
-    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
+    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-dynamo-core
       repository: "pytorch/tensorrt"

From 1357112a12995d25f9c6865544e8a71434d8a945 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 9 Apr 2024 16:41:16 -0700
Subject: [PATCH 052/122] chore: updates

---
 packaging/smoke_test_script.sh | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 packaging/smoke_test_script.sh

diff --git a/packaging/smoke_test_script.sh b/packaging/smoke_test_script.sh
new file mode 100644
index 0000000000..e69de29bb2

From 608a6d274abea87d0939bb0917ae7e42c9efb605 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 10 Apr 2024 08:20:39 -0700
Subject: [PATCH 053/122] chore: updates

---
 .github/scripts/install-torch-tensorrt.sh | 12 +++++++++++-
 .github/workflows/build-test.yml          |  3 ++-
 packaging/post_build_script.sh            |  3 ---
 packaging/smoke_test_script.sh            |  6 ++++++
 py/requirements.txt                       |  8 +-------
 5 files changed, 20 insertions(+), 12 deletions(-)

diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index 48c6c90cbf..10d5023557 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -5,6 +5,16 @@ source ${BUILD_ENV_FILE}
 ${CONDA_RUN} ${PIP_INSTALL_TORCH} torchvision
 ${CONDA_RUN} python -m pip install pyyaml mpmath==1.3.0
 export TRT_VERSION=$(${CONDA_RUN} python -c "import versions; versions.tensorrt_version()")
-${CONDA_RUN} python -m pip install /opt/torch-tensorrt-builds/torch_tensorrt*+${CU_VERSION}*.whl tensorrt~=${TRT_VERSION} tensorrt-bindings~=${TRT_VERSION} --extra-index-url=https://pypi.ngc.nvidia.com
+
+# Print PYTHON_VERSION
+printf "PYTHON_VERSION is equal to %s" ${PYTHON_VERSION//./}
+
+# Install TensorRT manually
+wget -P /opt/torch-tensorrt-builds/ https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.0/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz
+tar -xvzf /opt/torch-tensorrt-builds/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz -C /opt/torch-tensorrt-builds/
+python -m pip install /opt/torch-tensorrt-builds/TensorRT-10.0.0.6/python/tensorrt-10.0.0b6-cp${PYTHON_VERSION//./}-none-linux_x86_64.whl
+
+# Install Torch-TensorRT
+${CONDA_RUN} python -m pip install /opt/torch-tensorrt-builds/torch_tensorrt*+${CU_VERSION}*.whl
 
 echo -e "Running test script";
diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml
index 330006f76e..89b41df3a3 100644
--- a/.github/workflows/build-test.yml
+++ b/.github/workflows/build-test.yml
@@ -79,7 +79,8 @@ jobs:
         export LD_LIBRARY_PATH=/usr/lib64:$LD_LIBRARY_PATH
         pushd .
         cd tests/modules
-        ${CONDA_RUN} python -m pip install --pre -r requirements.txt --use-deprecated=legacy-resolver
+        # Don't use requirements.txt here as it contains tensorrt and torch which should have been installed by now.
+        ${CONDA_RUN} python -m pip install numpy packaging pyyaml pybind11==2.6.2
         ${CONDA_RUN} python hub.py
         popd
         pushd .
diff --git a/packaging/post_build_script.sh b/packaging/post_build_script.sh
index 0d5d045cd0..e69de29bb2 100644
--- a/packaging/post_build_script.sh
+++ b/packaging/post_build_script.sh
@@ -1,3 +0,0 @@
-export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
-echo $LD_LIBRARY_PATH
-python -m pip install /opt/torch-tensorrt-builds/TensorRT-10.0.0.6/python/tensorrt-10.0.0b6-cp38-none-linux_x86_64.whl
\ No newline at end of file
diff --git a/packaging/smoke_test_script.sh b/packaging/smoke_test_script.sh
index e69de29bb2..d3bed3249e 100644
--- a/packaging/smoke_test_script.sh
+++ b/packaging/smoke_test_script.sh
@@ -0,0 +1,6 @@
+# Smoke test is intentionally disabled.
+# The issue was smoke test installs the built torch_tensorrt wheel file and checks `import torch_tensorrt; print(torch_tensorrt.__version__)`
+# Since tensorrt cannot be pip installable in CI, the smoke test will fail.
+# One way we tried to handle it is manually install tensorrt wheel while by extracting from the tarball.
+# However, the TensorRT-10.0.0.6/lib path doesn't seem to show up in LD_LIBRARY_PATH even if we explicitly set it.
+# TODO: Implement a custom smoke_test script to verify torch_tensorrt installation.
\ No newline at end of file
diff --git a/py/requirements.txt b/py/requirements.txt
index 360fdbb01d..e3356a8c59 100644
--- a/py/requirements.txt
+++ b/py/requirements.txt
@@ -5,10 +5,4 @@ pybind11==2.6.2
 torch==2.3.0
 torchvision==0.18.0
 --extra-index-url https://pypi.ngc.nvidia.com
-pyyaml
-# Extras
-ninja>=1.11.0
-cffi>=1.15.1
-pybind11==2.6.2
-wheel>=0.40.0
-future>=0.18.3
+pyyaml
\ No newline at end of file

From 1b34b3246da47b4a621b8d818b8e57d86a9679d0 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 10 Apr 2024 08:56:19 -0700
Subject: [PATCH 054/122] chore: updates

---
 .github/workflows/build-test.yml | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml
index 89b41df3a3..278a4aecf3 100644
--- a/.github/workflows/build-test.yml
+++ b/.github/workflows/build-test.yml
@@ -77,6 +77,7 @@ jobs:
       script: |
         export USE_HOST_DEPS=1
         export LD_LIBRARY_PATH=/usr/lib64:$LD_LIBRARY_PATH
+        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/modules
         # Don't use requirements.txt here as it contains tensorrt and torch which should have been installed by now.
@@ -113,6 +114,7 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
+        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/dynamo
         ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
@@ -141,6 +143,7 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
+        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/dynamo
         ${CONDA_RUN} python -m pip install --pre pytest timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
@@ -170,6 +173,7 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
+        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/dynamo
         ${CONDA_RUN} python -m pip install --pre pytest timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
@@ -198,6 +202,7 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
+        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/dynamo
         ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
@@ -227,6 +232,7 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
+        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/dynamo
         ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver

From 89cb55a6af0aeacf4063ea5510c3049a5763e401 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 10 Apr 2024 11:45:13 -0700
Subject: [PATCH 055/122] chore: updates

---
 .github/workflows/build-test.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml
index 278a4aecf3..c32d42c78e 100644
--- a/.github/workflows/build-test.yml
+++ b/.github/workflows/build-test.yml
@@ -81,7 +81,7 @@ jobs:
         pushd .
         cd tests/modules
         # Don't use requirements.txt here as it contains tensorrt and torch which should have been installed by now.
-        ${CONDA_RUN} python -m pip install numpy packaging pyyaml pybind11==2.6.2
+        ${CONDA_RUN} python -m pip install numpy packaging pyyaml transformers pybind11==2.6.2
         ${CONDA_RUN} python hub.py
         popd
         pushd .

From 4323e36461b4caeb90c9eca47e7f6887e92bed15 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 10 Apr 2024 12:41:49 -0700
Subject: [PATCH 056/122] chore: updates

---
 .github/workflows/build-test.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml
index c32d42c78e..1b1fa72f2f 100644
--- a/.github/workflows/build-test.yml
+++ b/.github/workflows/build-test.yml
@@ -81,7 +81,7 @@ jobs:
         pushd .
         cd tests/modules
         # Don't use requirements.txt here as it contains tensorrt and torch which should have been installed by now.
-        ${CONDA_RUN} python -m pip install numpy packaging pyyaml transformers pybind11==2.6.2
+        ${CONDA_RUN} python -m pip install numpy packaging pyyaml transformers timm pybind11==2.6.2
         ${CONDA_RUN} python hub.py
         popd
         pushd .

From 60b3e51bcc4e6fc93bc84909fe8cfb27617d54af Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 10 Apr 2024 15:07:23 -0700
Subject: [PATCH 057/122] chore: update hw_compat

---
 tests/py/dynamo/runtime/gen_hw_compat.py  |  33 ++++++++++++++++++++++
 tests/py/dynamo/runtime/test_hw_compat.py |   6 ++--
 tests/py/ts/models/hw_compat.ts           | Bin 386982 -> 110354 bytes
 3 files changed, 35 insertions(+), 4 deletions(-)
 create mode 100644 tests/py/dynamo/runtime/gen_hw_compat.py

diff --git a/tests/py/dynamo/runtime/gen_hw_compat.py b/tests/py/dynamo/runtime/gen_hw_compat.py
new file mode 100644
index 0000000000..e279015aa2
--- /dev/null
+++ b/tests/py/dynamo/runtime/gen_hw_compat.py
@@ -0,0 +1,33 @@
+# This script is used to generate hw_compat.ts file that's used in test_hw_compat.py
+# Generate the model on a different hardware compared to the one you're testing on to
+# verify HW compatibility feature.
+
+import torch
+import torch_tensorrt
+
+
+class MyModule(torch.nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.conv = torch.nn.Conv2d(3, 16, 3, stride=1, bias=True)
+        self.relu = torch.nn.ReLU()
+
+    def forward(self, x):
+        out = self.conv(x)
+        out = self.relu(out)
+        return out
+
+
+model = MyModule().eval().cuda()
+inputs = torch.randn((1, 3, 224, 224)).to("cuda")
+
+trt_gm = torch_tensorrt.compile(
+    model,
+    ir="dynamo",
+    inputs=inputs,
+    min_block_size=1,
+    hardware_compatible=True,
+    version_compatible=True,
+)
+trt_script_model = torch.jit.trace(trt_gm, inputs)
+torch.jit.save(trt_script_model, "hw_compat.ts")
diff --git a/tests/py/dynamo/runtime/test_hw_compat.py b/tests/py/dynamo/runtime/test_hw_compat.py
index 4218cc7de0..aa238c7a4a 100644
--- a/tests/py/dynamo/runtime/test_hw_compat.py
+++ b/tests/py/dynamo/runtime/test_hw_compat.py
@@ -59,16 +59,14 @@ def forward(self, x):
         "Detected incorrect ABI version, please update this test case",
     )
     def test_hw_compat_3080_build(self):
-        inputs = [torch.randn(5, 7).cuda()]
+        inputs = [torch.randn(1, 3, 224, 224).cuda()]
 
         cwd = os.getcwd()
         os.chdir(os.path.dirname(os.path.realpath(__file__)))
         model = torch.jit.load("../../ts/models/hw_compat.ts").cuda()
         out = model(*inputs)
         self.assertTrue(
-            isinstance(out, tuple)
-            and len(out) == 1
-            and isinstance(out[0], torch.Tensor),
+            len(out) == 1 and isinstance(out, torch.Tensor),
             "Invalid output detected",
         )
         os.chdir(cwd)
diff --git a/tests/py/ts/models/hw_compat.ts b/tests/py/ts/models/hw_compat.ts
index ab43e5e040ef3850c8e0b879a973dc759565830e..27726233f28119dc4c1b52793e03efc7da7fc3da 100644
GIT binary patch
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From 05627cd8aa329739e8655eed5637fecb5130c673 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 12 Apr 2024 14:45:50 -0700
Subject: [PATCH 058/122] chore: updates

---
 .../conversion/impl/normalization/ops.py      | 14 +++++-
 .../dynamo/conversion/test_layer_norm_aten.py | 49 -------------------
 2 files changed, 13 insertions(+), 50 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/conversion/impl/normalization/ops.py b/py/torch_tensorrt/dynamo/conversion/impl/normalization/ops.py
index f45d067349..bbe566d0b7 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/normalization/ops.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/normalization/ops.py
@@ -452,6 +452,7 @@ def pdist(
     p: float = 2,
 ) -> Union[TRTTensor, Sequence[TRTTensor]]:
     shape = input.shape
+    # Extend input from shape [N, D] to [N, 1, D]
     extend_input = impl.shuffle.reshape(
         ctx,
         target,
@@ -460,7 +461,18 @@ def pdist(
         input,
         shape=shape[0:1] + (1,) + shape[1:],
     )
-    x = impl.elementwise.sub(ctx, target, source_ir, f"{name}_sub", extend_input, input)
+    # Expand the input from [N, 1, D] to [N, N, D]
+    x = impl.slice.expand(
+        ctx,
+        target,
+        source_ir,
+        f"{name}_sub",
+        extend_input,
+        (shape[0], shape[0]) + shape[1:],
+    )
+    # Subtract the expanded input from original input. Result shape = [N, N, D]
+    # This matrix has the distance of each sample to every other sample and hence the shape is [N, N, D]
+    x = impl.elementwise.sub(ctx, target, source_ir, f"{name}_sub", x, input)
 
     if p == 0:
         # norm = torch.sum(x!=0, dim=2)
diff --git a/tests/py/dynamo/conversion/test_layer_norm_aten.py b/tests/py/dynamo/conversion/test_layer_norm_aten.py
index 8013768214..7f43234211 100644
--- a/tests/py/dynamo/conversion/test_layer_norm_aten.py
+++ b/tests/py/dynamo/conversion/test_layer_norm_aten.py
@@ -24,31 +24,6 @@ def forward(self, x):
             inputs,
         )
 
-    def test_layernorm_with_dynamic_shape(self):
-        class LayerNorm(torch.nn.Module):
-            def forward(self, x):
-                return torch.ops.aten.layer_norm.default(
-                    x,
-                    torch.tensor([3, 224, 224]),
-                    torch.ones((3, 224, 224)),
-                    torch.zeros((3, 224, 224)),
-                    1e-05,
-                    True,
-                )
-
-        input_specs = [
-            Input(
-                shape=(-1, 3, 224, 224),
-                dtype=torch.float32,
-                shape_ranges=[((1, 3, 224, 224), (1, 3, 224, 224), (2, 3, 224, 224))],
-            ),
-        ]
-
-        self.run_test_with_dynamic_shape(
-            LayerNorm(),
-            input_specs,
-        )
-
 
 class TestNativeLayerNormConverter(DispatchTestCase):
     def test_layer_norm(self):
@@ -68,30 +43,6 @@ def forward(self, x):
             inputs,
         )
 
-    def test_layernorm_with_dynamic_shape(self):
-        class LayerNorm(torch.nn.Module):
-            def forward(self, x):
-                return torch.ops.aten.native_layer_norm.default(
-                    x,
-                    torch.tensor([3, 224, 224]),
-                    torch.ones((3, 224, 224)),
-                    torch.zeros((3, 224, 224)),
-                    1e-05,
-                )[0]
-
-        input_specs = [
-            Input(
-                shape=(-1, 3, 224, 224),
-                dtype=torch.float32,
-                shape_ranges=[((1, 3, 224, 224), (1, 3, 224, 224), (2, 3, 224, 224))],
-            ),
-        ]
-
-        self.run_test_with_dynamic_shape(
-            LayerNorm(),
-            input_specs,
-        )
-
 
 if __name__ == "__main__":
     run_tests()

From d16585f0be1c5085739d7c09b29acb81d359e921 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 12 Apr 2024 16:26:37 -0700
Subject: [PATCH 059/122] chore: update streams

---
 core/runtime/execute_engine.cpp                               | 3 +--
 .../dynamo/runtime/_PythonTorchTensorRTModule.py              | 4 ++--
 2 files changed, 3 insertions(+), 4 deletions(-)

diff --git a/core/runtime/execute_engine.cpp b/core/runtime/execute_engine.cpp
index 5ff163fbfb..165328f16c 100644
--- a/core/runtime/execute_engine.cpp
+++ b/core/runtime/execute_engine.cpp
@@ -178,8 +178,7 @@ std::vector<at::Tensor> execute_engine(std::vector<at::Tensor> inputs, c10::intr
       enqueue_profiler_guard =
           std::make_unique<torch::autograd::profiler::RecordProfile>(compiled_engine->enqueue_profile_path);
     }
-    c10::cuda::CUDAStream stream = c10::cuda::getCurrentCUDAStream(inputs[0].device().index());
-
+    c10::cuda::CUDAStream stream = c10::cuda::getStreamFromPool(/*isHighPriority=*/true, inputs[0].device().index());
     // nvinfer1::IExecutionContext::enqueue is not thread safe and we need a mutex for it.
     std::unique_lock<std::mutex> lock(compiled_engine->mu);
     compiled_engine->exec_ctx->enqueueV3(stream);
diff --git a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
index 82f5817b01..a296deaba9 100644
--- a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
+++ b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
@@ -59,7 +59,7 @@ def _initialize(self) -> None:
         runtime = trt.Runtime(logger)
         self.engine = runtime.deserialize_cuda_engine(self.engine)
         self.context = self.engine.create_execution_context()
-
+        self.stream = torch.cuda.Stream(torch.cuda.current_device())
         # Indices of inputs/outputs in the trt engine bindings, in the order
         # as they are in the original PyTorch model.
 
@@ -286,7 +286,7 @@ def forward(self, *inputs: torch.Tensor) -> torch.Tensor | Tuple[torch.Tensor, .
                 if self.profiling_enabled
                 else nullcontext()
             ):
-                self.context.execute_async_v3(torch.cuda.current_stream().cuda_stream)
+                self.context.execute_async_v3(self.stream.cuda_stream)
 
             if len(outputs) == 1:
                 return outputs[0]

From 3d149ef78a4e39c9a249b66790721d0e02a92e7d Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 12 Apr 2024 21:30:42 -0700
Subject: [PATCH 060/122] chore: updates

---
 py/torch_tensorrt/dynamo/conversion/impl/shape.py | 13 +++++++++++++
 1 file changed, 13 insertions(+)

diff --git a/py/torch_tensorrt/dynamo/conversion/impl/shape.py b/py/torch_tensorrt/dynamo/conversion/impl/shape.py
index 0727eecef7..e19f44ab3a 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/shape.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/shape.py
@@ -9,6 +9,7 @@
 from torch_tensorrt.dynamo._SourceIR import SourceIR
 from torch_tensorrt.dynamo.conversion._ConversionContext import ConversionContext
 from torch_tensorrt.dynamo.conversion.converter_utils import (
+    cast_trt_tensor,
     get_positive_dim,
     get_trt_tensor,
 )
@@ -38,6 +39,12 @@ def shape(
     """
     shape_layer = ctx.net.add_shape(input_val)
     input_shape = shape_layer.get_output(0)
+    input_shape = cast_trt_tensor(
+        ctx,
+        input_shape,
+        trt.int32,
+        name + "_shape_casted",
+    )
     set_layer_name(shape_layer, target, name + "_shape", source_ir)
 
     n_dims = len(input_val.shape)
@@ -82,6 +89,12 @@ def get_shape_with_dynamic_shape(
     """
     # Ger real shape info for input_val
     input_shape = ctx.net.add_shape(input_val).get_output(0)
+    input_shape = cast_trt_tensor(
+        ctx,
+        input_shape,
+        trt.int32,
+        name + "_int32_casted",
+    )
     # input_shape.dtype is int64 in TRT 10.0
     input_np_dtype = unified_dtype_converter(input_shape.dtype, Frameworks.NUMPY)
     scale_layer = ctx.net.add_constant(

From 3addcae373f550603c904dd110c4d906dbf4bfb9 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Sat, 13 Apr 2024 01:07:35 -0700
Subject: [PATCH 061/122] chore: updates

---
 .github/scripts/install-torch-tensorrt.sh | 7 ++-----
 core/runtime/execute_engine.cpp           | 2 +-
 packaging/pre_build_script.sh             | 6 +++---
 3 files changed, 6 insertions(+), 9 deletions(-)

diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index 10d5023557..b2b19b139d 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -6,12 +6,9 @@ ${CONDA_RUN} ${PIP_INSTALL_TORCH} torchvision
 ${CONDA_RUN} python -m pip install pyyaml mpmath==1.3.0
 export TRT_VERSION=$(${CONDA_RUN} python -c "import versions; versions.tensorrt_version()")
 
-# Print PYTHON_VERSION
-printf "PYTHON_VERSION is equal to %s" ${PYTHON_VERSION//./}
-
 # Install TensorRT manually
-wget -P /opt/torch-tensorrt-builds/ https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.0/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz
-tar -xvzf /opt/torch-tensorrt-builds/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz -C /opt/torch-tensorrt-builds/
+wget -q -P /opt/torch-tensorrt-builds/ https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.0/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz
+tar -xzf /opt/torch-tensorrt-builds/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz -C /opt/torch-tensorrt-builds/
 python -m pip install /opt/torch-tensorrt-builds/TensorRT-10.0.0.6/python/tensorrt-10.0.0b6-cp${PYTHON_VERSION//./}-none-linux_x86_64.whl
 
 # Install Torch-TensorRT
diff --git a/core/runtime/execute_engine.cpp b/core/runtime/execute_engine.cpp
index 165328f16c..a1ee30e994 100644
--- a/core/runtime/execute_engine.cpp
+++ b/core/runtime/execute_engine.cpp
@@ -178,7 +178,7 @@ std::vector<at::Tensor> execute_engine(std::vector<at::Tensor> inputs, c10::intr
       enqueue_profiler_guard =
           std::make_unique<torch::autograd::profiler::RecordProfile>(compiled_engine->enqueue_profile_path);
     }
-    c10::cuda::CUDAStream stream = c10::cuda::getStreamFromPool(/*isHighPriority=*/true, inputs[0].device().index());
+    c10::cuda::CUDAStream stream = c10::cuda::getCurrentCUDAStream(inputs[0].device().index());
     // nvinfer1::IExecutionContext::enqueue is not thread safe and we need a mutex for it.
     std::unique_lock<std::mutex> lock(compiled_engine->mu);
     compiled_engine->exec_ctx->enqueueV3(stream);
diff --git a/packaging/pre_build_script.sh b/packaging/pre_build_script.sh
index c518992ab6..befb6e38d9 100755
--- a/packaging/pre_build_script.sh
+++ b/packaging/pre_build_script.sh
@@ -3,9 +3,9 @@
 # Install dependencies
 python3 -m pip install pyyaml
 yum install -y ninja-build gettext
-TRT_VERSION=10.0.0.6 #$(python3 -c "import versions; versions.tensorrt_version()")
-wget -P /opt/torch-tensorrt-builds/ https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.0/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz
-tar -xvzf /opt/torch-tensorrt-builds/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz -C /opt/torch-tensorrt-builds/
+TRT_VERSION=$(python3 -c "import versions; versions.tensorrt_version()")
+wget -q -P /opt/torch-tensorrt-builds/ https://developer.nvidia.com/downloads/compute/machine-learning/tensorrt/10.0.0/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz
+tar -xzf /opt/torch-tensorrt-builds/TensorRT-10.0.0.6.Linux.x86_64-gnu.cuda-12.4.tar.gz -C /opt/torch-tensorrt-builds/
 export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
 wget https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-linux-amd64 \
     && mv bazelisk-linux-amd64 /usr/bin/bazel \

From b0e92d87979bf10d5a7b7ac356868c8f006f7787 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 15 Apr 2024 12:49:39 -0700
Subject: [PATCH 062/122] chore: update hw_compat.ts

---
 tests/py/ts/models/hw_compat.ts | Bin 110354 -> 110418 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)

diff --git a/tests/py/ts/models/hw_compat.ts b/tests/py/ts/models/hw_compat.ts
index 27726233f28119dc4c1b52793e03efc7da7fc3da..ed71663c0c77a406307a3e7c23d331c1b44b7243 100644
GIT binary patch
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From d285d27d6384fa8101fcebe74136400d42effca8 Mon Sep 17 00:00:00 2001
From: Evan Li <zewenl@nvidia.com>
Date: Mon, 15 Apr 2024 14:06:20 -0700
Subject: [PATCH 063/122] fix dynamic shape bugs for test_binary_ops_aten

---
 .../conversion/impl/elementwise/base.py       | 71 +++++++++++--------
 1 file changed, 40 insertions(+), 31 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py b/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
index f93ec52504..d835110159 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/elementwise/base.py
@@ -13,7 +13,11 @@
     cast_trt_tensor,
     get_trt_tensor,
 )
-from torch_tensorrt.fx.converters.converter_utils import set_layer_name
+from torch_tensorrt.fx.converters.converter_utils import (
+    broadcast,
+    has_dynamic_shape,
+    set_layer_name,
+)
 from torch_tensorrt.fx.types import TRTElementWiseOp, TRTTensor
 from torch_tensorrt.fx.utils import Frameworks, unified_dtype_converter
 
@@ -148,38 +152,43 @@ def convert_binary_elementwise(
             ctx, rhs_val, trt_promoted_type, f"{name}_cast_rhs_val", target, source_ir
         )
 
-    lhs_val_shape = lhs_val.shape
-    rhs_val_shape = rhs_val.shape
-    rank_diff = len(lhs_val_shape) - len(rhs_val_shape)
-    if rank_diff > 0:
-        rhs_val = impl.slice.expand(
-            ctx, target, source_ir, f"{name}_expand_rhs_val", rhs_val, lhs_val_shape
-        )
-    elif rank_diff < 0:
-        lhs_val = impl.slice.expand(
-            ctx, target, source_ir, f"{name}_expand_lhs_val", lhs_val, rhs_val_shape
+    if has_dynamic_shape(lhs_val.shape) or has_dynamic_shape(rhs_val.shape):
+        lhs_val, rhs_val = broadcast(
+            ctx.net, lhs_val, rhs_val, f"{name}_lhs", f"{name}_rhs"
         )
     else:
-        if tuple(lhs_val_shape) != tuple(rhs_val_shape):
-            sum_diff = sum(lhs_val_shape) - sum(rhs_val_shape)
-            if sum_diff > 0:
-                rhs_val = impl.slice.expand(
-                    ctx,
-                    target,
-                    source_ir,
-                    f"{name}_expand_rhs_val",
-                    rhs_val,
-                    lhs_val_shape,
-                )
-            elif sum_diff < 0:
-                lhs_val = impl.slice.expand(
-                    ctx,
-                    target,
-                    source_ir,
-                    f"{name}_expand_lhs_val",
-                    lhs_val,
-                    rhs_val_shape,
-                )
+        lhs_val_shape = lhs_val.shape
+        rhs_val_shape = rhs_val.shape
+        rank_diff = len(lhs_val_shape) - len(rhs_val_shape)
+        if rank_diff > 0:
+            rhs_val = impl.slice.expand(
+                ctx, target, source_ir, f"{name}_expand_rhs_val", rhs_val, lhs_val_shape
+            )
+        elif rank_diff < 0:
+            lhs_val = impl.slice.expand(
+                ctx, target, source_ir, f"{name}_expand_lhs_val", lhs_val, rhs_val_shape
+            )
+        else:
+            if tuple(lhs_val_shape) != tuple(rhs_val_shape):
+                sum_diff = sum(lhs_val_shape) - sum(rhs_val_shape)
+                if sum_diff > 0:
+                    rhs_val = impl.slice.expand(
+                        ctx,
+                        target,
+                        source_ir,
+                        f"{name}_expand_rhs_val",
+                        rhs_val,
+                        lhs_val_shape,
+                    )
+                elif sum_diff < 0:
+                    lhs_val = impl.slice.expand(
+                        ctx,
+                        target,
+                        source_ir,
+                        f"{name}_expand_lhs_val",
+                        lhs_val,
+                        rhs_val_shape,
+                    )
 
     layer = ctx.net.add_elementwise(lhs_val, rhs_val, op_type)
     set_layer_name(layer, target, name, source_ir)

From d78a8466c961ae11e061ea4d253a0bcb4809cbcd Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 15 Apr 2024 18:40:05 -0700
Subject: [PATCH 064/122] chore: revert layer_norm test

---
 .../dynamo/conversion/test_layer_norm_aten.py | 49 +++++++++++++++++++
 1 file changed, 49 insertions(+)

diff --git a/tests/py/dynamo/conversion/test_layer_norm_aten.py b/tests/py/dynamo/conversion/test_layer_norm_aten.py
index 7f43234211..8013768214 100644
--- a/tests/py/dynamo/conversion/test_layer_norm_aten.py
+++ b/tests/py/dynamo/conversion/test_layer_norm_aten.py
@@ -24,6 +24,31 @@ def forward(self, x):
             inputs,
         )
 
+    def test_layernorm_with_dynamic_shape(self):
+        class LayerNorm(torch.nn.Module):
+            def forward(self, x):
+                return torch.ops.aten.layer_norm.default(
+                    x,
+                    torch.tensor([3, 224, 224]),
+                    torch.ones((3, 224, 224)),
+                    torch.zeros((3, 224, 224)),
+                    1e-05,
+                    True,
+                )
+
+        input_specs = [
+            Input(
+                shape=(-1, 3, 224, 224),
+                dtype=torch.float32,
+                shape_ranges=[((1, 3, 224, 224), (1, 3, 224, 224), (2, 3, 224, 224))],
+            ),
+        ]
+
+        self.run_test_with_dynamic_shape(
+            LayerNorm(),
+            input_specs,
+        )
+
 
 class TestNativeLayerNormConverter(DispatchTestCase):
     def test_layer_norm(self):
@@ -43,6 +68,30 @@ def forward(self, x):
             inputs,
         )
 
+    def test_layernorm_with_dynamic_shape(self):
+        class LayerNorm(torch.nn.Module):
+            def forward(self, x):
+                return torch.ops.aten.native_layer_norm.default(
+                    x,
+                    torch.tensor([3, 224, 224]),
+                    torch.ones((3, 224, 224)),
+                    torch.zeros((3, 224, 224)),
+                    1e-05,
+                )[0]
+
+        input_specs = [
+            Input(
+                shape=(-1, 3, 224, 224),
+                dtype=torch.float32,
+                shape_ranges=[((1, 3, 224, 224), (1, 3, 224, 224), (2, 3, 224, 224))],
+            ),
+        ]
+
+        self.run_test_with_dynamic_shape(
+            LayerNorm(),
+            input_specs,
+        )
+
 
 if __name__ == "__main__":
     run_tests()

From 68aab70d633a9d35a08f32209fbdbbde4ad2000d Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 17 Apr 2024 16:18:45 -0700
Subject: [PATCH 065/122] chore: updates

---
 docker/Dockerfile | 65 ++++++++++++++++++++++-------------------------
 docker/README.md  |  6 ++---
 2 files changed, 34 insertions(+), 37 deletions(-)

diff --git a/docker/Dockerfile b/docker/Dockerfile
index 60b213b110..8e9918d0ba 100644
--- a/docker/Dockerfile
+++ b/docker/Dockerfile
@@ -8,9 +8,6 @@ ENV BASE_IMG=nvidia/cuda:12.1.1-devel-ubuntu22.04
 ARG TENSORRT_VERSION
 ENV TENSORRT_VERSION=${TENSORRT_VERSION}
 RUN test -n "$TENSORRT_VERSION" || (echo "No tensorrt version specified, please use --build-arg TENSORRT_VERSION=x.y to specify a version." && exit 1)
-ARG CUDNN_VERSION
-ENV CUDNN_VERSION=${CUDNN_VERSION}
-RUN test -n "$CUDNN_VERSION" || (echo "No cudnn version specified, please use --build-arg CUDNN_VERSION=x.y to specify a version." && exit 1)
 
 ARG PYTHON_VERSION=3.10
 ENV PYTHON_VERSION=${PYTHON_VERSION}
@@ -36,18 +33,18 @@ RUN pyenv install -v ${PYTHON_VERSION}
 RUN pyenv global ${PYTHON_VERSION}
 
 # Install CUDNN + TensorRT + dependencies
-RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin
-RUN mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600
-RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/7fa2af80.pub
-RUN add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /"
-RUN apt-get update
-RUN apt-get install -y libcudnn8=${CUDNN_VERSION}* libcudnn8-dev=${CUDNN_VERSION}*
+# RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin
+# RUN mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600
+# RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/7fa2af80.pub
+# RUN add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /"
+# RUN apt-get update
+# RUN apt-get install -y libcudnn8=${CUDNN_VERSION}* libcudnn8-dev=${CUDNN_VERSION}*
 
 RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub
 RUN add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /"
 RUN apt-get update
 
-RUN apt-get install -y libnvinfer8=${TENSORRT_VERSION}.* libnvinfer-plugin8=${TENSORRT_VERSION}.* libnvinfer-dev=${TENSORRT_VERSION}.* libnvinfer-plugin-dev=${TENSORRT_VERSION}.* libnvonnxparsers8=${TENSORRT_VERSION}.* libnvonnxparsers-dev=${TENSORRT_VERSION}.* libnvparsers8=${TENSORRT_VERSION}.*  libnvparsers-dev=${TENSORRT_VERSION}.*
+RUN apt-get install -y libnvinfer10=${TENSORRT_VERSION}.* libnvinfer-plugin10=${TENSORRT_VERSION}.* libnvinfer-dev=${TENSORRT_VERSION}.* libnvinfer-plugin-dev=${TENSORRT_VERSION}.* libnvonnxparsers10=${TENSORRT_VERSION}.* libnvonnxparsers-dev=${TENSORRT_VERSION}.*
 
 # Setup Bazel via Bazelisk
 RUN wget -q https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-linux-amd64 -O /usr/bin/bazel &&\
@@ -88,35 +85,35 @@ RUN CUDA_BASE_IMG_VERSION_INTERMEDIATE=`echo ${BASE_IMG#*:}` &&\
 
 ENV CUDA_HOME=/usr/local/cuda
 
-# This script builds both libtorchtrt bin/lib/include tarball and the Python wheel, in dist/
-RUN bash ./docker/dist-build.sh
+# # This script builds both libtorchtrt bin/lib/include tarball and the Python wheel, in dist/
+# RUN bash ./docker/dist-build.sh
 
-# Copy and install Torch-TRT into the main container
-FROM base as torch-tensorrt
+# # Copy and install Torch-TRT into the main container
+# FROM base as torch-tensorrt
 
-COPY . /opt/torch_tensorrt
+# COPY . /opt/torch_tensorrt
 
-# Symlink the path pyenv is using for python with the /opt directory for package sourcing
-RUN mkdir -p "/opt/python3/" &&\
-    ln -s "`pyenv which python | xargs dirname | xargs dirname`/lib/python$PYTHON_VERSION/site-packages" "/opt/python3/"
+# # Symlink the path pyenv is using for python with the /opt directory for package sourcing
+# RUN mkdir -p "/opt/python3/" &&\
+#     ln -s "`pyenv which python | xargs dirname | xargs dirname`/lib/python$PYTHON_VERSION/site-packages" "/opt/python3/"
 
-COPY --from=torch-tensorrt-builder  /workspace/torch_tensorrt/src/dist/ .
+# COPY --from=torch-tensorrt-builder  /workspace/torch_tensorrt/src/dist/ .
 
-RUN cp /opt/torch_tensorrt/docker/WORKSPACE.docker /opt/torch_tensorrt/WORKSPACE &&\
-    pip install -r /opt/torch_tensorrt/py/requirements.txt &&\
-    # Install all dependency wheel files and user-specified TensorRT
-    pip install *.whl &&\
-    pip install tensorrt==${TENSORRT_VERSION}.* &&\
-    # Add the Torch-TensorRT wheel file to the dist directory and delete all other .whl files
-    rm -fr /workspace/torch_tensorrt/dist/* &&\
-    mkdir -p /opt/torch_tensorrt/dist/ && mv torch_tensorrt*.whl /opt/torch_tensorrt/dist/ &&\
-    rm -fr *.whl &&\
-    # Remove other cache files if present
-    pip cache purge && rm -rf /opt/torch_tensorrt/.mypy_cache
+# RUN cp /opt/torch_tensorrt/docker/WORKSPACE.docker /opt/torch_tensorrt/WORKSPACE &&\
+#     pip install -r /opt/torch_tensorrt/py/requirements.txt &&\
+#     # Install all dependency wheel files and user-specified TensorRT
+#     pip install *.whl &&\
+#     pip install tensorrt==${TENSORRT_VERSION}.* &&\
+#     # Add the Torch-TensorRT wheel file to the dist directory and delete all other .whl files
+#     rm -fr /workspace/torch_tensorrt/dist/* &&\
+#     mkdir -p /opt/torch_tensorrt/dist/ && mv torch_tensorrt*.whl /opt/torch_tensorrt/dist/ &&\
+#     rm -fr *.whl &&\
+#     # Remove other cache files if present
+#     pip cache purge && rm -rf /opt/torch_tensorrt/.mypy_cache
 
-WORKDIR /opt/torch_tensorrt
+# WORKDIR /opt/torch_tensorrt
 
-ENV LD_LIBRARY_PATH /opt/python3/site-packages/torch/lib:/opt/python3/site-packages/torch_tensorrt/lib:/usr/lib/x86_64-linux-gnu:${LD_LIBRARY_PATH}
-ENV PATH /opt/python3/site-packages/torch_tensorrt/bin:${PATH}
+# ENV LD_LIBRARY_PATH /opt/python3/site-packages/torch/lib:/opt/python3/site-packages/torch_tensorrt/lib:/usr/lib/x86_64-linux-gnu:${LD_LIBRARY_PATH}
+# ENV PATH /opt/python3/site-packages/torch_tensorrt/bin:${PATH}
 
-CMD /bin/bash
+# CMD /bin/bash
diff --git a/docker/README.md b/docker/README.md
index 9f83f25134..24a76ea9ec 100644
--- a/docker/README.md
+++ b/docker/README.md
@@ -3,7 +3,7 @@
 * Use `Dockerfile` to build a container which provides the exact development environment that our master branch is usually tested against.
 
 * The `Dockerfile` currently uses <a href="https://github.com/bazelbuild/bazelisk">Bazelisk</a> to select the Bazel version, and uses the exact library versions of Torch and CUDA listed in <a href="https://github.com/pytorch/TensorRT#dependencies">dependencies</a>.
-  * The desired versions of CUDNN and TensorRT must be specified as build-args, with major and minor versions as in: `--build-arg TENSORRT_VERSION=a.b --build-arg CUDNN_VERSION=x.y`
+  * The desired version of TensorRT must be specified as build-args, with major and minor versions as in: `--build-arg TENSORRT_VERSION=a.b`
   * [**Optional**] The desired base image be changed by explicitly setting a base image, as in `--build-arg BASE_IMG=nvidia/cuda:11.8.0-devel-ubuntu22.04`, though this is optional
   * [**Optional**] Additionally, the desired Python version can be changed by explicitly setting a version, as in `--build-arg PYTHON_VERSION=3.10`, though this is optional as well.
 
@@ -17,14 +17,14 @@ Note: By default the container uses the `pre-cxx11-abi` version of Torch + Torch
 
 ### Instructions
 
-- The example below uses CUDNN 8.9 and TensorRT 8.6
+- The example below uses TensorRT 10.0.0.6
 - See <a href="https://github.com/pytorch/TensorRT#dependencies">dependencies</a> for a list of current default dependencies.
 
 > From root of Torch-TensorRT repo
 
 Build:
 ```
-DOCKER_BUILDKIT=1 docker build --build-arg TENSORRT_VERSION=8.6 --build-arg CUDNN_VERSION=8.9 -f docker/Dockerfile -t torch_tensorrt:latest .
+DOCKER_BUILDKIT=1 docker build --build-arg TENSORRT_VERSION=10.0 -f docker/Dockerfile -t torch_tensorrt:latest .
 ```
 
 Run:

From 38642bb9ef8b4da63b25363cde751dc17a3812b9 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 18 Apr 2024 16:07:04 -0700
Subject: [PATCH 066/122] chore: updates

---
 py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
index 05808dd37c..9a75add755 100644
--- a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
+++ b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
@@ -313,7 +313,7 @@ def run(
         )
         timing_cache = self._create_timing_cache(builder_config, existing_cache)
 
-        engine = self.builder.build_engine(self.ctx.net, builder_config)
+        engine = self.builder.build_serialized_network(self.ctx.net, builder_config)
         assert engine
 
         serialized_cache = (

From ba286bdab40c0d0aa418b609ef129306a555b241 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 18 Apr 2024 16:40:24 -0700
Subject: [PATCH 067/122] chore: add fp8 test

---
 tests/py/dynamo/models/test_models_export.py | 42 ++++++++++++++++++++
 1 file changed, 42 insertions(+)

diff --git a/tests/py/dynamo/models/test_models_export.py b/tests/py/dynamo/models/test_models_export.py
index 38889a3df8..fe41cd1406 100644
--- a/tests/py/dynamo/models/test_models_export.py
+++ b/tests/py/dynamo/models/test_models_export.py
@@ -180,3 +180,45 @@ def test_resnet18_half(ir):
 
     # Clean up model env
     torch._dynamo.reset()
+
+
+@pytest.mark.unit
+def test_base_fp8(ir):
+    class SimpleNetwork(nn.Module):
+        def __init__(self):
+            super(SimpleNetwork, self).__init__()
+            self.linear1 = nn.Linear(in_features=10, out_features=5)
+            self.linear2 = nn.Linear(in_features=5, out_features=1)
+
+        def forward(self, x):
+            x = self.linear1(x)
+            x = torch.nn.ReLU()(x)
+            x = self.linear2(x)
+            return x
+
+    import ammo.torch.quantization as atq
+    from ammo.torch.quantization.torch_export import export_torch_mode
+
+    def calibrate_loop(model):
+        """Simple calibration function for testing."""
+        model(input_tensor)
+
+    input_tensor = torch.randn(1, 10).cuda()
+    model = SimpleNetwork().eval().cuda()
+
+    with torch.no_grad():
+        quant_cfg = atq.FP8_DEFAULT_CFG
+        atq.quantize(model, quant_cfg, forward_loop=calibrate_loop)
+        # model has FP8 qdq nodes at this point
+        output_pyt = model(input_tensor)
+
+        with export_torch_mode():
+            exp_program = torch.export.export(model, (input_tensor,))
+            trt_model = torch_tensorrt.dynamo.compile(
+                exp_program,
+                inputs=[input_tensor],
+                enabled_precisions={torch.float8_e4m3fn},
+                min_block_size=1,
+            )
+            outputs_trt = trt_model(input_tensor)
+            assert torch.allclose(output_pyt, outputs_trt, rtol=1e-3, atol=1e-2)

From d15dd72c38e91ddc20f10b5452f76239e16f819a Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 18 Apr 2024 17:21:21 -0700
Subject: [PATCH 068/122] chore: updates

---
 py/torch_tensorrt/_enums.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/py/torch_tensorrt/_enums.py b/py/torch_tensorrt/_enums.py
index 5c16cd03cd..062abb9a87 100644
--- a/py/torch_tensorrt/_enums.py
+++ b/py/torch_tensorrt/_enums.py
@@ -107,7 +107,7 @@ def _from(
                 return dtype.f16
             elif t == trt.float32:
                 return dtype.f32
-            elif trt.__version__ >= "7.0" and t == trt.bool:
+            elif t == trt.bool:
                 return dtype.b
             else:
                 raise TypeError(

From dee9aa02d941be5312f7e3cceef5ad4f887aefe1 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 19 Apr 2024 09:23:09 -0700
Subject: [PATCH 069/122] chore: updates

---
 .github/workflows/build-test.yml            | 1 +
 tests/py/dynamo/conversion/test_erf_aten.py | 2 +-
 tests/py/dynamo/conversion/test_neg_aten.py | 2 +-
 3 files changed, 3 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml
index 97f4ad2ba0..f4d39bd056 100644
--- a/.github/workflows/build-test.yml
+++ b/.github/workflows/build-test.yml
@@ -264,6 +264,7 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
+        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/core
         ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
diff --git a/tests/py/dynamo/conversion/test_erf_aten.py b/tests/py/dynamo/conversion/test_erf_aten.py
index d65788bc85..d9d201b0ae 100644
--- a/tests/py/dynamo/conversion/test_erf_aten.py
+++ b/tests/py/dynamo/conversion/test_erf_aten.py
@@ -22,7 +22,7 @@ def forward(self, input):
                 return torch.ops.aten.erf.default(input)
 
         inputs = [torch.randn(x, dtype=type)]
-        self.run_test(erf(), inputs, precision=type, output_dtypes=[type])
+        self.run_test(erf(), inputs, precision=type)
 
     @parameterized.expand(
         [
diff --git a/tests/py/dynamo/conversion/test_neg_aten.py b/tests/py/dynamo/conversion/test_neg_aten.py
index 818d9c5a83..795a78354f 100644
--- a/tests/py/dynamo/conversion/test_neg_aten.py
+++ b/tests/py/dynamo/conversion/test_neg_aten.py
@@ -22,7 +22,7 @@ def forward(self, input):
                 return torch.ops.aten.neg.default(input)
 
         inputs = [torch.randn(x, dtype=type)]
-        self.run_test(neg(), inputs, precision=type, output_dtypes=[type])
+        self.run_test(neg(), inputs, precision=type)
 
     @parameterized.expand(
         [

From c05d675d5db3a5b12fee6e2505dfdc9a4b51ccaf Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 19 Apr 2024 16:25:01 -0700
Subject: [PATCH 070/122] chore: update stream in python runtime

---
 .../runtime/_PythonTorchTensorRTModule.py      |   3 +--
 tests/py/ts/models/hw_compat.ts                | Bin 110418 -> 0 bytes
 2 files changed, 1 insertion(+), 2 deletions(-)
 delete mode 100644 tests/py/ts/models/hw_compat.ts

diff --git a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
index ef24a57f8e..49ed64a953 100644
--- a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
+++ b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
@@ -59,7 +59,6 @@ def _initialize(self) -> None:
         runtime = trt.Runtime(logger)
         self.engine = runtime.deserialize_cuda_engine(self.engine)
         self.context = self.engine.create_execution_context()
-        self.stream = torch.cuda.Stream(torch.cuda.current_device())
         # Indices of inputs/outputs in the trt engine bindings, in the order
         # as they are in the original PyTorch model.
 
@@ -282,7 +281,7 @@ def forward(self, *inputs: torch.Tensor) -> torch.Tensor | Tuple[torch.Tensor, .
                 if self.profiling_enabled
                 else nullcontext()
             ):
-                self.context.execute_async_v3(self.stream.cuda_stream)
+                self.context.execute_async_v3(torch.cuda.current_stream().cuda_stream)
 
             if len(outputs) == 1:
                 return outputs[0]
diff --git a/tests/py/ts/models/hw_compat.ts b/tests/py/ts/models/hw_compat.ts
deleted file mode 100644
index ed71663c0c77a406307a3e7c23d331c1b44b7243..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

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From 23296573c4eb02b7687f44cd56da0658af6a5980 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 19 Apr 2024 16:42:55 -0700
Subject: [PATCH 071/122] chore: update hw_compat.ts

---
 tests/py/ts/models/hw_compat.ts | Bin 0 -> 110481 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 tests/py/ts/models/hw_compat.ts

diff --git a/tests/py/ts/models/hw_compat.ts b/tests/py/ts/models/hw_compat.ts
new file mode 100644
index 0000000000000000000000000000000000000000..3cf583c78824407d066054b56da3095b37c2615d
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zF_$+}5iFQU=RIkEYE+o%X)fpN&1ECeOha!P%$P7k7O8p%gbk^>W;PoE=LrQ;quDGC
znrOn4wX%^7sWDWZ<EO?_k<XX&doJdu#u=FQIwsqdsy8yt#!<%6#&?bHW}9iOiP?<M
zsO+^qUm_X}__C2iJk!vT_6O1dzbfJbBOX7)lC`9c<4B0|c(Etdu*i~go{T;ssff^c
z;aOCCBrkhXjgTKF(C)nRqub`51Rg<t!#DAXOe?2}2LkB~Dxy*R<QTe9)IbLI&bve1
z7}pH>4PV?z%xq3^-eNY8AfK#J$c~}FA*dCNWV6u#sl(N?KWHK%H~9@;hqIUqIdy3D
zd$Jy0CXkMJqLGq^^h0mNuTeCQxI%oXK-?ykip4S!UnCRH6pDp2`C@UKL?jdmWRf<S
zP$-s)WKvSYk6!-z+h){`{5p-JNMjAkl3Xc&GI>#RRV8~;VS@f_{wn+DN~waHyq{v;
zP|ZKWnZeNNaRt9iYQV?u`5xe_RC4Hda0MK5O+lp<M=R)9rOKgYAK<VjDmD+6e{kiG
zUG~rxKv73zg@aYV!}|M=R*NGs#-Uxw<sP%R;F-Crz7PDvzoarh;_{SJYf54ss4a=Z
zn<~{kQgbxb0I}5o8N!SzU@CRt62xgWU^Wg9raI871C>kaPOJfRE`;*xKr2(zq4nTW
zsgr85-%^u(kU9<pz$GGQ)c~0C5V!mzleSLdxN#SjbDc5zqQU$V%TJYip2z{Xeh--B
cLO!yB!SL3yVe-GzIF`^_W+MJbdN%Dp0BTWb(*OVf

literal 0
HcmV?d00001


From b8a87099015a5180c5faadc66455542c3299fa2e Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 19 Apr 2024 23:22:46 -0700
Subject: [PATCH 072/122] chore: updates

---
 tests/py/dynamo/lowering/test_aten_lowering_passes.py | 2 +-
 tests/py/dynamo/testing_utilities.py                  | 1 -
 2 files changed, 1 insertion(+), 2 deletions(-)

diff --git a/tests/py/dynamo/lowering/test_aten_lowering_passes.py b/tests/py/dynamo/lowering/test_aten_lowering_passes.py
index 5c0a1bb774..2d7a4731f5 100644
--- a/tests/py/dynamo/lowering/test_aten_lowering_passes.py
+++ b/tests/py/dynamo/lowering/test_aten_lowering_passes.py
@@ -453,7 +453,7 @@ def forward(self, input, weight, bias):
         self.assertAlmostEqual(
             max_diff,
             0,
-            DECIMALS_OF_AGREEMENT_3,
+            DECIMALS_OF_AGREEMENT,
             msg=f"Linear TRT outputs don't match with the original model.",
         )
         torch._dynamo.reset()
diff --git a/tests/py/dynamo/testing_utilities.py b/tests/py/dynamo/testing_utilities.py
index c815d2fde4..742b9fc1a3 100644
--- a/tests/py/dynamo/testing_utilities.py
+++ b/tests/py/dynamo/testing_utilities.py
@@ -14,7 +14,6 @@
 )
 
 DECIMALS_OF_AGREEMENT = 4
-DECIMALS_OF_AGREEMENT_3 = 3
 
 
 def fx_dynamo_testing_backend(

From 44778e11f9feecad1f5123489911339c9a79bf99 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 19 Apr 2024 23:49:29 -0700
Subject: [PATCH 073/122] chore: updates

---
 cpp/include/torch_tensorrt/ptq.h                          | 8 ++++----
 .../dynamo/runtime/_PythonTorchTensorRTModule.py          | 5 -----
 pyproject.toml                                            | 2 ++
 3 files changed, 6 insertions(+), 9 deletions(-)

diff --git a/cpp/include/torch_tensorrt/ptq.h b/cpp/include/torch_tensorrt/ptq.h
index e88da06b0c..d8570f0e6e 100644
--- a/cpp/include/torch_tensorrt/ptq.h
+++ b/cpp/include/torch_tensorrt/ptq.h
@@ -21,10 +21,10 @@
 #include "torch_tensorrt/macros.h"
 
 #ifndef DOXYGEN_SHOULD_SKIP_THIS
-// namespace nvinfer1 {
-// class IInt8Calibrator;
-// class IInt8EntropyCalibrator2;
-// } // namespace nvinfer1
+namespace nvinfer1 {
+class IInt8Calibrator;
+class IInt8EntropyCalibrator2;
+} // namespace nvinfer1
 
 namespace torch_tensorrt {
 namespace ptq {
diff --git a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
index 49ed64a953..7b82d41cb6 100644
--- a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
+++ b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
@@ -209,11 +209,6 @@ def forward(self, *inputs: torch.Tensor) -> torch.Tensor | Tuple[torch.Tensor, .
 
                 contiguous_inputs: List[torch.Tensor] = [i.contiguous() for i in inputs]
                 bindings = []
-                # [None] * (
-                #     len(self.input_names)
-                #     + len(self.output_names)
-                #     # + len(self.hidden_output_names) # TODO: Verify if this is required
-                # )
                 for i, input_name in enumerate(self.input_names):
                     if not contiguous_inputs[i].is_cuda:
                         logger.warning(
diff --git a/pyproject.toml b/pyproject.toml
index 79e5391f52..ec6c0fe19c 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -8,6 +8,7 @@ requires = [
     "cffi>=1.15.1",
     "typing-extensions>=4.7.0",
     "future>=0.18.3",
+    "tensorrt",
     "torch==2.3.0",
     "pybind11==2.6.2",
     "numpy",
@@ -41,6 +42,7 @@ requires-python = ">=3.8"
 keywords = ["pytorch", "torch", "tensorrt", "trt", "ai", "artificial intelligence", "ml", "machine learning", "dl", "deep learning", "compiler", "dynamo", "torchscript", "inference"]
 dependencies = [
     "torch==2.3.0",
+    "tensorrt",
     "packaging>=23",
     "numpy",
     "typing-extensions>=4.7.0",

From 0dbbcd71da88f437e7c87a040138fdfe51d23031 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Sat, 20 Apr 2024 01:22:00 -0700
Subject: [PATCH 074/122] chore: updates

---
 cpp/include/torch_tensorrt/ptq.h | 8 ++++----
 packaging/pre_build_script.sh    | 2 +-
 py/requirements.txt              | 3 ++-
 3 files changed, 7 insertions(+), 6 deletions(-)

diff --git a/cpp/include/torch_tensorrt/ptq.h b/cpp/include/torch_tensorrt/ptq.h
index d8570f0e6e..e88da06b0c 100644
--- a/cpp/include/torch_tensorrt/ptq.h
+++ b/cpp/include/torch_tensorrt/ptq.h
@@ -21,10 +21,10 @@
 #include "torch_tensorrt/macros.h"
 
 #ifndef DOXYGEN_SHOULD_SKIP_THIS
-namespace nvinfer1 {
-class IInt8Calibrator;
-class IInt8EntropyCalibrator2;
-} // namespace nvinfer1
+// namespace nvinfer1 {
+// class IInt8Calibrator;
+// class IInt8EntropyCalibrator2;
+// } // namespace nvinfer1
 
 namespace torch_tensorrt {
 namespace ptq {
diff --git a/packaging/pre_build_script.sh b/packaging/pre_build_script.sh
index befb6e38d9..8f5d1d8acc 100755
--- a/packaging/pre_build_script.sh
+++ b/packaging/pre_build_script.sh
@@ -10,7 +10,7 @@ export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.0.6/lib:$LD_LIBR
 wget https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-linux-amd64 \
     && mv bazelisk-linux-amd64 /usr/bin/bazel \
     && chmod +x /usr/bin/bazel
-python -m pip install -r py/requirements.txt
+
 export TORCH_BUILD_NUMBER=$(python -c "import torch, urllib.parse as ul; print(ul.quote_plus(torch.__version__))")
 
 cat toolchains/ci_workspaces/WORKSPACE.x86_64.release.rhel.tmpl | envsubst > WORKSPACE
diff --git a/py/requirements.txt b/py/requirements.txt
index e3356a8c59..d402fd501e 100644
--- a/py/requirements.txt
+++ b/py/requirements.txt
@@ -5,4 +5,5 @@ pybind11==2.6.2
 torch==2.3.0
 torchvision==0.18.0
 --extra-index-url https://pypi.ngc.nvidia.com
-pyyaml
\ No newline at end of file
+pyyaml
+tensorrt
\ No newline at end of file

From 89c3d76b7e94a8f37df8937f0552f75633b3445e Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 22 Apr 2024 16:01:37 -0700
Subject: [PATCH 075/122] chore: updates

---
 core/runtime/TRTEngine.cpp                    |  2 +
 cpp/include/torch_tensorrt/ptq.h              |  5 --
 .../runtime/_PythonTorchTensorRTModule.py     | 53 ++-----------------
 3 files changed, 6 insertions(+), 54 deletions(-)

diff --git a/core/runtime/TRTEngine.cpp b/core/runtime/TRTEngine.cpp
index fcbb403e2c..4a33907bec 100644
--- a/core/runtime/TRTEngine.cpp
+++ b/core/runtime/TRTEngine.cpp
@@ -133,6 +133,7 @@ TRTEngine::TRTEngine(
           trt_idx = idx;
           if (cuda_engine->getTensorIOMode(binding_name.c_str()) == nvinfer1::TensorIOMode::kINPUT) {
             is_input = true;
+            break;
           }
         }
       }
@@ -161,6 +162,7 @@ TRTEngine::TRTEngine(
           trt_idx = idx;
           if (cuda_engine->getTensorIOMode(binding_name.c_str()) == nvinfer1::TensorIOMode::kOUTPUT) {
             is_output = true;
+            break;
           }
         }
       }
diff --git a/cpp/include/torch_tensorrt/ptq.h b/cpp/include/torch_tensorrt/ptq.h
index e88da06b0c..6650f45fe9 100644
--- a/cpp/include/torch_tensorrt/ptq.h
+++ b/cpp/include/torch_tensorrt/ptq.h
@@ -21,11 +21,6 @@
 #include "torch_tensorrt/macros.h"
 
 #ifndef DOXYGEN_SHOULD_SKIP_THIS
-// namespace nvinfer1 {
-// class IInt8Calibrator;
-// class IInt8EntropyCalibrator2;
-// } // namespace nvinfer1
-
 namespace torch_tensorrt {
 namespace ptq {
 TORCHTRT_API bool get_batch_impl(void* bindings[], const char* names[], int nbBindings, torch::Tensor& data);
diff --git a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
index 7b82d41cb6..0c152e15f1 100644
--- a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
+++ b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
@@ -15,6 +15,7 @@
     _select_rt_device,
     multi_gpu_device_check,
 )
+from torch_tensorrt.logging import TRT_LOGGER
 
 logger = logging.getLogger(__name__)
 
@@ -55,39 +56,13 @@ def __init__(
 
     def _initialize(self) -> None:
         self.initialized = True
-        logger = trt.Logger()
-        runtime = trt.Runtime(logger)
+        runtime = trt.Runtime(TRT_LOGGER)
         self.engine = runtime.deserialize_cuda_engine(self.engine)
         self.context = self.engine.create_execution_context()
-        # Indices of inputs/outputs in the trt engine bindings, in the order
-        # as they are in the original PyTorch model.
-
-        # TODO: Verify if the following is required especially the hidden outputs
-        # self.input_binding_indices_in_order: Sequence[int] = [
-        #     self.engine.get_binding_index(name) for name in self.input_names
-        # ]
-        # self.output_binding_indices_in_order: Sequence[int] = [
-        #     self.engine.get_binding_index(name) for name in self.output_names
-        # ]
-        # primary_input_outputs = set()
-        # primary_input_outputs.update(self.input_binding_indices_in_order)
-        # primary_input_outputs.update(self.output_binding_indices_in_order)
-        # self.hidden_output_binding_indices_in_order: Sequence[int] = []
-        # self.hidden_output_names: Sequence[str] = []
-        # for i in range(
-        #     self.engine.num_bindings // self.engine.num_optimization_profiles
-        # ):
-        #     if i not in primary_input_outputs:
-        #         self.hidden_output_binding_indices_in_order.append(i)
-        #         self.hidden_output_names.append(self.engine.get_binding_name(i))
 
         assert (
             self.engine.num_io_tensors // self.engine.num_optimization_profiles
-        ) == (
-            len(self.input_names)
-            + len(self.output_names)
-            # + len(self.hidden_output_names) #TODO: Verify if this is required
-        )
+        ) == (len(self.input_names) + len(self.output_names))
 
         self.input_dtypes = [
             dtype._from(self.engine.get_tensor_dtype(input_name))
@@ -105,14 +80,6 @@ def _initialize(self) -> None:
             for output_name in self.output_names
         ]
 
-        # TODO: Verify what this is for ?
-        # self.hidden_output_dtypes = [
-        #     unified_dtype_converter(
-        #         self.engine.get_binding_dtype(idx), Frameworks.TORCH
-        #     )
-        #     for idx in self.hidden_output_binding_indices_in_order
-        # ]
-
     def _check_initialized(self) -> None:
         if not self.initialized:
             raise RuntimeError("PythonTorchTensorRTModule is not initialized.")
@@ -138,8 +105,7 @@ def _load_from_state_dict(
         # Run multi-gpu device check to validate engine instantiation
         multi_gpu_device_check()
 
-        logger = trt.Logger()
-        runtime = trt.Runtime(logger)
+        runtime = trt.Runtime(TRT_LOGGER)
         self.engine = runtime.deserialize_cuda_engine(engine_bytes)
 
         self.input_names = state_dict[prefix + "input_names"]
@@ -253,16 +219,6 @@ def forward(self, *inputs: torch.Tensor) -> torch.Tensor | Tuple[torch.Tensor, .
                     bindings.append(output.data_ptr())
                     outputs.append(output)
 
-                # TODO: Check what is this for ?
-                # for i, idx in enumerate(self.hidden_output_binding_indices_in_order):
-                #     shape = tuple(self.context.get_binding_shape(idx))
-
-                #     output = torch.empty(
-                #         size=shape,
-                #         dtype=self.hidden_output_dtypes[i],
-                #         device=torch.cuda.current_device(),
-                #     )
-
             # Assign tensor address appropriately
             for idx in range(self.engine.num_io_tensors):
                 self.context.set_tensor_address(
@@ -300,7 +256,6 @@ def disable_profiling(self) -> None:
         Disable TensorRT profiling.
         """
         self._check_initialized()
-
         torch.cuda.synchronize()
         del self.context
         self.context = self.engine.create_execution_context()

From 3956749712d3b9e249f1fac438e67460add1de44 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 22 Apr 2024 17:41:22 -0700
Subject: [PATCH 076/122] chore: updates

---
 py/torch_tensorrt/dynamo/_defaults.py        | 2 +-
 tests/py/dynamo/models/test_models_export.py | 4 ++++
 2 files changed, 5 insertions(+), 1 deletion(-)

diff --git a/py/torch_tensorrt/dynamo/_defaults.py b/py/torch_tensorrt/dynamo/_defaults.py
index 27db215466..c9b8be6bea 100644
--- a/py/torch_tensorrt/dynamo/_defaults.py
+++ b/py/torch_tensorrt/dynamo/_defaults.py
@@ -26,7 +26,7 @@
 REQUIRE_FULL_COMPILATION = False
 DRYRUN = False
 HARDWARE_COMPATIBLE = False
-SUPPORTED_KERNEL_PRECISIONS = {dtype.f32, dtype.f16, dtype.i8}
+SUPPORTED_KERNEL_PRECISIONS = {dtype.f32, dtype.f16, dtype.i8, dtype.f8}
 
 
 def default_device() -> Device:
diff --git a/tests/py/dynamo/models/test_models_export.py b/tests/py/dynamo/models/test_models_export.py
index fe41cd1406..d3ab46725d 100644
--- a/tests/py/dynamo/models/test_models_export.py
+++ b/tests/py/dynamo/models/test_models_export.py
@@ -182,6 +182,10 @@ def test_resnet18_half(ir):
     torch._dynamo.reset()
 
 
+@unittest.skipIf(
+    not torch.cuda.get_device_properties(torch.cuda.current_device()).major < 9,
+    "FP8 compilation in Torch-TRT is not supported on cards older than Hopper",
+)
 @pytest.mark.unit
 def test_base_fp8(ir):
     class SimpleNetwork(nn.Module):

From 0a2337b1d2d9671578e0e2e04042b506a2b4ad5f Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 22 Apr 2024 17:48:31 -0700
Subject: [PATCH 077/122] chore: updates

---
 .github/workflows/build-test.yml | 8 ++++++++
 1 file changed, 8 insertions(+)

diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml
index f4d39bd056..4d123ea8b8 100644
--- a/.github/workflows/build-test.yml
+++ b/.github/workflows/build-test.yml
@@ -66,6 +66,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
+            smoke-test-script: packaging/smoke_test_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-torchscript-fe
@@ -104,6 +105,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
+            smoke-test-script: packaging/smoke_test_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-dynamo-converters
@@ -133,6 +135,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
+            smoke-test-script: packaging/smoke_test_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-dynamo-fe
@@ -163,6 +166,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
+            smoke-test-script: packaging/smoke_test_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-dynamo-serde
@@ -192,6 +196,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
+            smoke-test-script: packaging/smoke_test_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-torch-compile-be
@@ -223,6 +228,7 @@ jobs:
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
+            smoke-test-script: packaging/smoke_test_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-dynamo-core
@@ -253,6 +259,8 @@ jobs:
           - repository: pytorch/tensorrt
             package-name: torch_tensorrt
             pre-script: packaging/pre_build_script.sh
+            post-script: packaging/post_build_script.sh
+            smoke-test-script: packaging/smoke_test_script.sh
     uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
     with:
       job-name: tests-py-core

From 358255df0ee9293b95274948ced696251c2148be Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 22 Apr 2024 17:49:47 -0700
Subject: [PATCH 078/122] chore: updates

---
 .github/workflows/build-test.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml
index 4d123ea8b8..5121302036 100644
--- a/.github/workflows/build-test.yml
+++ b/.github/workflows/build-test.yml
@@ -261,7 +261,7 @@ jobs:
             pre-script: packaging/pre_build_script.sh
             post-script: packaging/post_build_script.sh
             smoke-test-script: packaging/smoke_test_script.sh
-    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@main
+    uses: pytorch/tensorrt/.github/workflows/linux-test.yml@release/2.3
     with:
       job-name: tests-py-core
       repository: "pytorch/tensorrt"

From 7e717d63cf60f54f0d9505a0af7d37adb012c744 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 14 May 2024 10:42:53 -0700
Subject: [PATCH 079/122] chore: updates

---
 tests/py/dynamo/conversion/harness.py        | 19 ++++++++++---------
 tests/py/dynamo/models/test_models_export.py |  4 ++--
 tests/py/dynamo/testing_utilities.py         |  4 ++--
 3 files changed, 14 insertions(+), 13 deletions(-)

diff --git a/tests/py/dynamo/conversion/harness.py b/tests/py/dynamo/conversion/harness.py
index 7ce3939371..4825e45d26 100644
--- a/tests/py/dynamo/conversion/harness.py
+++ b/tests/py/dynamo/conversion/harness.py
@@ -14,7 +14,7 @@
 # Use interpreter, input spec, and test case from fx_ts_compat to test Dynamo Converter Registry
 from torch_tensorrt.dynamo.conversion import TRTInterpreter
 from torch_tensorrt.dynamo.conversion._conversion import infer_module_output_dtypes
-from torch_tensorrt.dynamo.lowering import apply_lowering_passes
+from torch_tensorrt.dynamo.lowering import post_lowering, pre_export_lowering
 from torch_tensorrt.dynamo.runtime import PythonTorchTensorRTModule
 
 _LOGGER: logging.Logger = logging.getLogger(__name__)
@@ -200,17 +200,18 @@ def generate_graph(
         enable_passes: bool,
     ):
         if use_dynamo_tracer:
-            fx_module = torch._dynamo.export(
-                mod,
-                *original_inputs,
-                aten_graph=True,
-                assume_static_by_default=True,
-                tracing_mode="real",
-            ).graph_module
+            exported_program = torch.export.export(mod, tuple(original_inputs))
+            exported_program = pre_export_lowering(exported_program, original_inputs)
+            exported_program = exported_program.run_decompositions(
+                get_decompositions(False)
+            )
+            fx_module = exported_program.module()
         else:
             fx_module = torch.fx.symbolic_trace(mod)
+
         if enable_passes:
-            fx_module = apply_lowering_passes(fx_module, original_inputs)
+            fx_module = post_lowering(fx_module, original_inputs)
+
         return fx_module
 
     def run_test(
diff --git a/tests/py/dynamo/models/test_models_export.py b/tests/py/dynamo/models/test_models_export.py
index dda466b048..79d6f8a42c 100644
--- a/tests/py/dynamo/models/test_models_export.py
+++ b/tests/py/dynamo/models/test_models_export.py
@@ -193,8 +193,8 @@ def test_base_fp8(ir):
     class SimpleNetwork(nn.Module):
         def __init__(self):
             super(SimpleNetwork, self).__init__()
-            self.linear1 = nn.Linear(in_features=10, out_features=5)
-            self.linear2 = nn.Linear(in_features=5, out_features=1)
+            self.linear1 = torch.nn.Linear(in_features=10, out_features=5)
+            self.linear2 = torch.nn.Linear(in_features=5, out_features=1)
 
         def forward(self, x):
             x = self.linear1(x)
diff --git a/tests/py/dynamo/testing_utilities.py b/tests/py/dynamo/testing_utilities.py
index 742b9fc1a3..e0112ae523 100644
--- a/tests/py/dynamo/testing_utilities.py
+++ b/tests/py/dynamo/testing_utilities.py
@@ -8,8 +8,8 @@
 from torch._functorch.aot_autograd import aot_export_joint_simple
 from torch_tensorrt.dynamo import partitioning
 from torch_tensorrt.dynamo.lowering import (
-    apply_lowering_passes,
     get_decompositions,
+    post_lowering,
     repair_input_aliasing,
 )
 
@@ -50,7 +50,7 @@ def fx_dynamo_testing_backend(
             decompositions=get_decompositions(),
         )
 
-        gm = apply_lowering_passes(gm, sample_inputs)
+        gm = post_lowering(gm, sample_inputs)
 
         trt_compiled = custom_backend(
             gm,

From c6d2f2ad84e25613f02d8cdbb5a864d65372433b Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 14 May 2024 11:20:50 -0700
Subject: [PATCH 080/122] chore: update to modelopt

---
 tests/py/dynamo/models/test_models_export.py | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/tests/py/dynamo/models/test_models_export.py b/tests/py/dynamo/models/test_models_export.py
index 79d6f8a42c..7bc9731147 100644
--- a/tests/py/dynamo/models/test_models_export.py
+++ b/tests/py/dynamo/models/test_models_export.py
@@ -202,8 +202,8 @@ def forward(self, x):
             x = self.linear2(x)
             return x
 
-    import ammo.torch.quantization as atq
-    from ammo.torch.quantization.torch_export import export_torch_mode
+    import modelopt.torch.quantization as mtq
+    from modelopt.torch.quantization.utils import export_torch_mode
 
     def calibrate_loop(model):
         """Simple calibration function for testing."""
@@ -212,12 +212,12 @@ def calibrate_loop(model):
     input_tensor = torch.randn(1, 10).cuda()
     model = SimpleNetwork().eval().cuda()
 
-    with torch.no_grad():
-        quant_cfg = atq.FP8_DEFAULT_CFG
-        atq.quantize(model, quant_cfg, forward_loop=calibrate_loop)
-        # model has FP8 qdq nodes at this point
-        output_pyt = model(input_tensor)
+    quant_cfg = mtq.FP8_DEFAULT_CFG
+    mtq.quantize(model, quant_cfg, forward_loop=calibrate_loop)
+    # model has FP8 qdq nodes at this point
+    output_pyt = model(input_tensor)
 
+    with torch.no_grad():
         with export_torch_mode():
             exp_program = torch.export.export(model, (input_tensor,))
             trt_model = torch_tensorrt.dynamo.compile(

From ceec39dc2b47aced90713e4c6032d3fe4fad15a8 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 14 May 2024 12:48:54 -0700
Subject: [PATCH 081/122] chore: updates

---
 tests/py/dynamo/conversion/harness.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/tests/py/dynamo/conversion/harness.py b/tests/py/dynamo/conversion/harness.py
index 4825e45d26..df95911065 100644
--- a/tests/py/dynamo/conversion/harness.py
+++ b/tests/py/dynamo/conversion/harness.py
@@ -14,7 +14,11 @@
 # Use interpreter, input spec, and test case from fx_ts_compat to test Dynamo Converter Registry
 from torch_tensorrt.dynamo.conversion import TRTInterpreter
 from torch_tensorrt.dynamo.conversion._conversion import infer_module_output_dtypes
-from torch_tensorrt.dynamo.lowering import post_lowering, pre_export_lowering
+from torch_tensorrt.dynamo.lowering import (
+    get_decompositions,
+    post_lowering,
+    pre_export_lowering,
+)
 from torch_tensorrt.dynamo.runtime import PythonTorchTensorRTModule
 
 _LOGGER: logging.Logger = logging.getLogger(__name__)

From a7e566b071b6f09bc56ce81f482def9603e1b928 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 14 May 2024 13:29:33 -0700
Subject: [PATCH 082/122] chore: updates

---
 py/torch_tensorrt/dynamo/_compiler.py                 |  1 -
 .../dynamo/lowering/_remove_sym_nodes.py              |  5 +++--
 .../dynamo/lowering/passes/fuse_prims_broadcast.py    | 11 -----------
 3 files changed, 3 insertions(+), 14 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/_compiler.py b/py/torch_tensorrt/dynamo/_compiler.py
index 28480418d3..540caad3b1 100644
--- a/py/torch_tensorrt/dynamo/_compiler.py
+++ b/py/torch_tensorrt/dynamo/_compiler.py
@@ -178,7 +178,6 @@ def compile(
             f"Input graph should be an ExportedProgram but got type {type(exported_program)}"
         )
 
-    exported_program = pre_export_lowering(exported_program, torch_inputs)
     exported_program = exported_program.run_decompositions(
         get_decompositions(enable_experimental_decompositions)
     )
diff --git a/py/torch_tensorrt/dynamo/lowering/_remove_sym_nodes.py b/py/torch_tensorrt/dynamo/lowering/_remove_sym_nodes.py
index e85117a423..8adebc87f8 100644
--- a/py/torch_tensorrt/dynamo/lowering/_remove_sym_nodes.py
+++ b/py/torch_tensorrt/dynamo/lowering/_remove_sym_nodes.py
@@ -10,17 +10,18 @@ def remove_sym_nodes(gm: torch.fx.GraphModule) -> torch.fx.GraphModule:
     dynamic=True behavior
     """
     # Extract SymInt placeholder Tensors
-    placeholders = [
+    placeholder_sym_ints = [
         node
         for node in gm.graph.nodes
         if (
             node.op == "placeholder"
             and isinstance(node.type, type)
             and issubclass(node.type, torch.SymInt)
+            and not node.users
         )
     ]
 
-    for node in placeholders:
+    for node in placeholder_sym_ints:
         gm.graph.erase_node(node)
 
     gm.graph.lint()
diff --git a/py/torch_tensorrt/dynamo/lowering/passes/fuse_prims_broadcast.py b/py/torch_tensorrt/dynamo/lowering/passes/fuse_prims_broadcast.py
index 312926e870..aa7403f94e 100644
--- a/py/torch_tensorrt/dynamo/lowering/passes/fuse_prims_broadcast.py
+++ b/py/torch_tensorrt/dynamo/lowering/passes/fuse_prims_broadcast.py
@@ -2,7 +2,6 @@
 from typing import Sequence
 
 import torch
-from torch.fx.passes.shape_prop import ShapeProp
 from torch_tensorrt.dynamo.lowering.passes.pass_utils import (
     clean_up_graph_after_modifications,
 )
@@ -17,16 +16,6 @@ def fuse_prims_broadcast(
     """Fuses prim nodes which are effectively the ATen equivalents with keep_dim=True"""
     modified_graph = False
 
-    # Propagate shapes through the graph to determine if broadcast can be resolved
-    try:
-        ShapeProp(gm).propagate(*sample_inputs)
-    except (RuntimeError, AssertionError):
-        logger.warning(
-            "Shape Propagation Failed on Graph, skipping fuse_prims_broadcast lowering pass",
-            exc_info=True,
-        )
-        return gm
-
     for node in gm.graph.nodes:
         # If the node is a sum prims operator, with broadcast_in_dim being the only consumer
         # it is a candidate for fusing

From 707b10ab4a1b9284ccad6a0f649fdff350f94eb7 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 14 May 2024 21:37:26 -0700
Subject: [PATCH 083/122] chore: updates

---
 tests/py/dynamo/conversion/harness.py        | 2 +-
 tests/py/dynamo/models/test_models_export.py | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/tests/py/dynamo/conversion/harness.py b/tests/py/dynamo/conversion/harness.py
index df95911065..f877871fc4 100644
--- a/tests/py/dynamo/conversion/harness.py
+++ b/tests/py/dynamo/conversion/harness.py
@@ -65,7 +65,6 @@ def run_test(
             for i in inputs:
                 cuda_inputs.append(i.cuda())
 
-            mod.eval()
             start = time.perf_counter()
             interpreter_result = interpreter.run()
             sec = time.perf_counter() - start
@@ -203,6 +202,7 @@ def generate_graph(
         use_dynamo_tracer: bool,
         enable_passes: bool,
     ):
+        mod = mod.eval()
         if use_dynamo_tracer:
             exported_program = torch.export.export(mod, tuple(original_inputs))
             exported_program = pre_export_lowering(exported_program, original_inputs)
diff --git a/tests/py/dynamo/models/test_models_export.py b/tests/py/dynamo/models/test_models_export.py
index 7bc9731147..b6c82a43c3 100644
--- a/tests/py/dynamo/models/test_models_export.py
+++ b/tests/py/dynamo/models/test_models_export.py
@@ -190,7 +190,7 @@ def test_resnet18_half(ir):
 )
 @pytest.mark.unit
 def test_base_fp8(ir):
-    class SimpleNetwork(nn.Module):
+    class SimpleNetwork(torch.nn.Module):
         def __init__(self):
             super(SimpleNetwork, self).__init__()
             self.linear1 = torch.nn.Linear(in_features=10, out_features=5)

From 22066c52dfa8f0a3fdb586af2ec8c813041cce78 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 14 May 2024 23:29:43 -0700
Subject: [PATCH 084/122] chore: minor fix

---
 tests/py/dynamo/models/test_models_export.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/py/dynamo/models/test_models_export.py b/tests/py/dynamo/models/test_models_export.py
index b6c82a43c3..af9abc41f2 100644
--- a/tests/py/dynamo/models/test_models_export.py
+++ b/tests/py/dynamo/models/test_models_export.py
@@ -185,7 +185,7 @@ def test_resnet18_half(ir):
 
 
 @unittest.skipIf(
-    not torch.cuda.get_device_properties(torch.cuda.current_device()).major < 9,
+    torch.cuda.get_device_properties(torch.cuda.current_device()).major < 9,
     "FP8 compilation in Torch-TRT is not supported on cards older than Hopper",
 )
 @pytest.mark.unit

From 6eed3832f2fe5bdd66489eea95dccdb4ab63e3bc Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 15 May 2024 09:39:42 -0700
Subject: [PATCH 085/122] chore: fixes

---
 py/torch_tensorrt/dynamo/_tracer.py                    | 10 +++-------
 py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py |  2 --
 tests/py/dynamo/conversion/harness.py                  |  7 +++----
 tests/py/dynamo/conversion/test_bitwise_and_aten.py    |  3 +++
 tests/py/dynamo/conversion/test_bitwise_not_aten.py    |  1 +
 tests/py/dynamo/conversion/test_bitwise_or_aten.py     |  3 +++
 tests/py/dynamo/conversion/test_bitwise_xor_aten.py    |  3 +++
 tests/py/dynamo/conversion/test_convolution_aten.py    |  5 ++---
 tests/py/dynamo/conversion/test_embedding_bag_aten.py  |  3 +++
 9 files changed, 21 insertions(+), 16 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/_tracer.py b/py/torch_tensorrt/dynamo/_tracer.py
index 11c0f6b3ac..6bc334f427 100644
--- a/py/torch_tensorrt/dynamo/_tracer.py
+++ b/py/torch_tensorrt/dynamo/_tracer.py
@@ -58,13 +58,9 @@ def trace(
 
     device = to_torch_device(kwargs.get("device", default_device()))
     torch_inputs = get_torch_inputs(inputs, device)
-    dynamic_shapes = {}
+    dynamic_shapes = []
     for input in inputs:
         if isinstance(input, Input) and input.shape_mode == Input._ShapeMode.DYNAMIC:
-            if not input.name:
-                raise AssertionError(
-                    f"Expected a name for a dynamic input with shape {input.shape} but found none"
-                )
             min_shape = input.shape["min_shape"]
             opt_shape = input.shape["opt_shape"]
             max_shape = input.shape["max_shape"]
@@ -80,8 +76,8 @@ def trace(
                         max=max_shape[dim],
                     )
 
-            dynamic_shapes[input.name] = dynamic_dims
+            dynamic_shapes.append(dynamic_dims)
 
-    exp_program = export(mod, tuple(torch_inputs), dynamic_shapes=dynamic_shapes)
+    exp_program = export(mod, tuple(torch_inputs), dynamic_shapes=tuple(dynamic_shapes))
 
     return exp_program
diff --git a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
index d541282fa5..c1a41602ef 100644
--- a/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
+++ b/py/torch_tensorrt/dynamo/conversion/_TRTInterpreter.py
@@ -105,8 +105,6 @@ def __init__(
             [dtype._from(o) for o in output_dtypes] if output_dtypes else None
         )
 
-        _LOGGER.debug(f"Graph to be compiled to TensorRT: {self.module.graph}")
-
     def validate_conversion(self) -> Set[str]:
         missing_converters: Set[str] = set()
 
diff --git a/tests/py/dynamo/conversion/harness.py b/tests/py/dynamo/conversion/harness.py
index f877871fc4..250d41a566 100644
--- a/tests/py/dynamo/conversion/harness.py
+++ b/tests/py/dynamo/conversion/harness.py
@@ -6,6 +6,7 @@
 from typing import Callable, List, Optional, Set, Tuple
 
 import torch
+import torch_tensorrt
 from torch.testing._internal.common_utils import TestCase
 from torch_tensorrt import Input
 from torch_tensorrt._enums import dtype
@@ -204,8 +205,7 @@ def generate_graph(
     ):
         mod = mod.eval()
         if use_dynamo_tracer:
-            exported_program = torch.export.export(mod, tuple(original_inputs))
-            exported_program = pre_export_lowering(exported_program, original_inputs)
+            exported_program = torch_tensorrt.dynamo.trace(mod, tuple(original_inputs))
             exported_program = exported_program.run_decompositions(
                 get_decompositions(False)
             )
@@ -286,10 +286,9 @@ def run_test_with_dynamic_shape(
         enable_passes=False,
     ):
         mod.eval()
-        inputs = [spec.example_tensor("opt_shape") for spec in input_specs]
         mod = self.generate_graph(
             mod,
-            inputs,
+            input_specs,
             use_dynamo_tracer=use_dynamo_tracer,
             enable_passes=enable_passes,
         )
diff --git a/tests/py/dynamo/conversion/test_bitwise_and_aten.py b/tests/py/dynamo/conversion/test_bitwise_and_aten.py
index 5c2a78a18a..8e7d8cef73 100644
--- a/tests/py/dynamo/conversion/test_bitwise_and_aten.py
+++ b/tests/py/dynamo/conversion/test_bitwise_and_aten.py
@@ -26,6 +26,7 @@ def forward(self, lhs_val, rhs_val):
             bitwise_and(),
             inputs,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
     @parameterized.expand(
@@ -46,6 +47,7 @@ def forward(self, tensor):
             bitwise_and(),
             inputs,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
     @parameterized.expand(
@@ -66,6 +68,7 @@ def forward(self, tensor):
             bitwise_and(),
             inputs,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
 
diff --git a/tests/py/dynamo/conversion/test_bitwise_not_aten.py b/tests/py/dynamo/conversion/test_bitwise_not_aten.py
index b811f1e51a..33d8629aff 100644
--- a/tests/py/dynamo/conversion/test_bitwise_not_aten.py
+++ b/tests/py/dynamo/conversion/test_bitwise_not_aten.py
@@ -25,6 +25,7 @@ def forward(self, val):
             bitwise_not(),
             inputs,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
 
diff --git a/tests/py/dynamo/conversion/test_bitwise_or_aten.py b/tests/py/dynamo/conversion/test_bitwise_or_aten.py
index b5e0200734..e912a9c473 100644
--- a/tests/py/dynamo/conversion/test_bitwise_or_aten.py
+++ b/tests/py/dynamo/conversion/test_bitwise_or_aten.py
@@ -26,6 +26,7 @@ def forward(self, lhs_val, rhs_val):
             bitwise_or(),
             inputs,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
     @parameterized.expand(
@@ -46,6 +47,7 @@ def forward(self, tensor):
             bitwise_or(),
             inputs,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
     @parameterized.expand(
@@ -66,6 +68,7 @@ def forward(self, tensor):
             bitwise_or(),
             inputs,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
 
diff --git a/tests/py/dynamo/conversion/test_bitwise_xor_aten.py b/tests/py/dynamo/conversion/test_bitwise_xor_aten.py
index 8c1a8136ef..4bd2790bf9 100644
--- a/tests/py/dynamo/conversion/test_bitwise_xor_aten.py
+++ b/tests/py/dynamo/conversion/test_bitwise_xor_aten.py
@@ -26,6 +26,7 @@ def forward(self, lhs_val, rhs_val):
             bitwise_xor(),
             inputs,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
     @parameterized.expand(
@@ -46,6 +47,7 @@ def forward(self, tensor):
             bitwise_xor(),
             inputs,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
     @parameterized.expand(
@@ -66,6 +68,7 @@ def forward(self, tensor):
             bitwise_xor(),
             inputs,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
 
diff --git a/tests/py/dynamo/conversion/test_convolution_aten.py b/tests/py/dynamo/conversion/test_convolution_aten.py
index 7d69c871a9..95f4de92b5 100644
--- a/tests/py/dynamo/conversion/test_convolution_aten.py
+++ b/tests/py/dynamo/conversion/test_convolution_aten.py
@@ -1,7 +1,6 @@
 import torch
 from parameterized import param, parameterized
 from torch.testing._internal.common_utils import run_tests
-
 from torch_tensorrt import Input
 
 from .harness import DispatchTestCase
@@ -138,7 +137,7 @@ def forward(self, x):
             Input(
                 shape=(-1, 3, -1, -1),
                 dtype=torch.float32,
-                shape_ranges=[((1, 3, 1, 1), (1, 3, 4, 4), (32, 3, 128, 128))],
+                shape_ranges=[((1, 3, 1, 1), (2, 3, 4, 4), (32, 3, 128, 128))],
             ),
         ]
         self.run_test_with_dynamic_shape(
@@ -201,7 +200,7 @@ def forward(self, x):
             Input(
                 shape=(-1, 3, -1, -1, -1),
                 dtype=torch.float32,
-                shape_ranges=[((1, 3, 1, 1, 1), (1, 3, 4, 4, 4), (8, 3, 32, 32, 32))],
+                shape_ranges=[((1, 3, 1, 1, 1), (2, 3, 4, 4, 4), (8, 3, 32, 32, 32))],
             ),
         ]
         self.run_test_with_dynamic_shape(
diff --git a/tests/py/dynamo/conversion/test_embedding_bag_aten.py b/tests/py/dynamo/conversion/test_embedding_bag_aten.py
index 2154937b43..0e4d6c806f 100644
--- a/tests/py/dynamo/conversion/test_embedding_bag_aten.py
+++ b/tests/py/dynamo/conversion/test_embedding_bag_aten.py
@@ -144,6 +144,7 @@ def forward(self, weight, indices):
             inputs=[weight, indices],
             precision=weight.dtype,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
     @parameterized.expand(
@@ -340,6 +341,7 @@ def forward(self, weight, indices, offsets):
             inputs=[weight, indices, offsets],
             precision=weight.dtype,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
     @parameterized.expand(
@@ -403,6 +405,7 @@ def forward(self, weight, indices, offsets):
             inputs=[weight, indices, offsets],
             precision=weight.dtype,
             enable_passes=True,
+            use_dynamo_tracer=True,
         )
 
 

From ff231b5dd766c811c0023fb9d22186e884bce7f9 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 15 May 2024 23:44:24 -0700
Subject: [PATCH 086/122] chore: fixes

---
 tests/py/dynamo/conversion/harness.py         | 23 +++++++++++++++----
 .../conversion/test_deconvolution_aten.py     |  5 ++--
 .../conversion/test_embedding_bag_aten.py     |  6 ++---
 3 files changed, 23 insertions(+), 11 deletions(-)

diff --git a/tests/py/dynamo/conversion/harness.py b/tests/py/dynamo/conversion/harness.py
index 250d41a566..3f38824c55 100644
--- a/tests/py/dynamo/conversion/harness.py
+++ b/tests/py/dynamo/conversion/harness.py
@@ -7,20 +7,19 @@
 
 import torch
 import torch_tensorrt
+from torch.fx.passes.shape_prop import ShapeProp
 from torch.testing._internal.common_utils import TestCase
 from torch_tensorrt import Input
 from torch_tensorrt._enums import dtype
+from torch_tensorrt.dynamo import _defaults
 from torch_tensorrt.dynamo._settings import CompilationSettings
 
 # Use interpreter, input spec, and test case from fx_ts_compat to test Dynamo Converter Registry
 from torch_tensorrt.dynamo.conversion import TRTInterpreter
 from torch_tensorrt.dynamo.conversion._conversion import infer_module_output_dtypes
-from torch_tensorrt.dynamo.lowering import (
-    get_decompositions,
-    post_lowering,
-    pre_export_lowering,
-)
+from torch_tensorrt.dynamo.lowering import get_decompositions, post_lowering
 from torch_tensorrt.dynamo.runtime import PythonTorchTensorRTModule
+from torch_tensorrt.dynamo.utils import get_torch_inputs
 
 _LOGGER: logging.Logger = logging.getLogger(__name__)
 
@@ -202,6 +201,7 @@ def generate_graph(
         original_inputs: List[torch.Tensor],
         use_dynamo_tracer: bool,
         enable_passes: bool,
+        propagate_shapes: bool,
     ):
         mod = mod.eval()
         if use_dynamo_tracer:
@@ -216,6 +216,17 @@ def generate_graph(
         if enable_passes:
             fx_module = post_lowering(fx_module, original_inputs)
 
+        if propagate_shapes:
+            # TODO: This is currently being used to test embedding_bag_aten due to https://github.com/pytorch/TensorRT/issues/2843
+            torch_inputs = get_torch_inputs(original_inputs, _defaults.DEVICE)
+            try:
+                ShapeProp(fx_module).propagate(*torch_inputs)
+            except (RuntimeError, AssertionError):
+                logger.warning(
+                    "Shape Propagation failed on Graph, skipping it",
+                    exc_info=False,
+                )
+
         return fx_module
 
     def run_test(
@@ -228,6 +239,7 @@ def run_test(
         check_dtype=True,
         use_dynamo_tracer=False,
         enable_passes=False,
+        propagate_shapes=False,
     ):
         mod.eval()
         mod = self.generate_graph(
@@ -235,6 +247,7 @@ def run_test(
             inputs,
             use_dynamo_tracer=use_dynamo_tracer,
             enable_passes=enable_passes,
+            propagate_shapes=propagate_shapes,
         )
 
         # Previous instance of the interpreter auto-casted 64-bit inputs
diff --git a/tests/py/dynamo/conversion/test_deconvolution_aten.py b/tests/py/dynamo/conversion/test_deconvolution_aten.py
index 6024b6946e..307275dba1 100644
--- a/tests/py/dynamo/conversion/test_deconvolution_aten.py
+++ b/tests/py/dynamo/conversion/test_deconvolution_aten.py
@@ -1,7 +1,6 @@
 import torch
 from parameterized import param, parameterized
 from torch.testing._internal.common_utils import run_tests
-
 from torch_tensorrt import Input
 
 from .harness import DispatchTestCase
@@ -152,7 +151,7 @@ def forward(self, x):
             Input(
                 shape=(-1, 3, -1, -1),
                 dtype=torch.float32,
-                shape_ranges=[((1, 3, 1, 1), (1, 3, 4, 4), (32, 3, 128, 128))],
+                shape_ranges=[((1, 3, 1, 1), (2, 3, 4, 4), (32, 3, 128, 128))],
             ),
         ]
         self.run_test_with_dynamic_shape(
@@ -221,7 +220,7 @@ def forward(self, x):
             Input(
                 shape=(-1, 3, -1, -1, -1),
                 dtype=torch.float32,
-                shape_ranges=[((1, 3, 1, 1, 1), (1, 3, 4, 4, 4), (8, 3, 32, 32, 32))],
+                shape_ranges=[((1, 3, 1, 1, 1), (2, 3, 4, 4, 4), (8, 3, 32, 32, 32))],
             ),
         ]
         self.run_test_with_dynamic_shape(
diff --git a/tests/py/dynamo/conversion/test_embedding_bag_aten.py b/tests/py/dynamo/conversion/test_embedding_bag_aten.py
index 0e4d6c806f..9664e1be58 100644
--- a/tests/py/dynamo/conversion/test_embedding_bag_aten.py
+++ b/tests/py/dynamo/conversion/test_embedding_bag_aten.py
@@ -144,7 +144,7 @@ def forward(self, weight, indices):
             inputs=[weight, indices],
             precision=weight.dtype,
             enable_passes=True,
-            use_dynamo_tracer=True,
+            propagate_shapes=True,
         )
 
     @parameterized.expand(
@@ -341,7 +341,7 @@ def forward(self, weight, indices, offsets):
             inputs=[weight, indices, offsets],
             precision=weight.dtype,
             enable_passes=True,
-            use_dynamo_tracer=True,
+            propagate_shapes=True,
         )
 
     @parameterized.expand(
@@ -405,7 +405,7 @@ def forward(self, weight, indices, offsets):
             inputs=[weight, indices, offsets],
             precision=weight.dtype,
             enable_passes=True,
-            use_dynamo_tracer=True,
+            propagate_shapes=True,
         )
 
 

From 2f167c6c65325e6e69e03f4367f68dff53cb6e24 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 16 May 2024 09:24:09 -0700
Subject: [PATCH 087/122] chore: updates

---
 tests/py/dynamo/conversion/harness.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/tests/py/dynamo/conversion/harness.py b/tests/py/dynamo/conversion/harness.py
index 3f38824c55..1c2727aa33 100644
--- a/tests/py/dynamo/conversion/harness.py
+++ b/tests/py/dynamo/conversion/harness.py
@@ -201,7 +201,7 @@ def generate_graph(
         original_inputs: List[torch.Tensor],
         use_dynamo_tracer: bool,
         enable_passes: bool,
-        propagate_shapes: bool,
+        propagate_shapes: bool = False,
     ):
         mod = mod.eval()
         if use_dynamo_tracer:
@@ -297,6 +297,7 @@ def run_test_with_dynamic_shape(
         output_dtypes=None,
         use_dynamo_tracer=False,
         enable_passes=False,
+        propagate_shapes=False,
     ):
         mod.eval()
         mod = self.generate_graph(
@@ -304,6 +305,7 @@ def run_test_with_dynamic_shape(
             input_specs,
             use_dynamo_tracer=use_dynamo_tracer,
             enable_passes=enable_passes,
+            propagate_shapes=propagate_shapes,
         )
 
         # Previous instance of the interpreter auto-casted 64-bit inputs

From 367eaf0f82250f77b5992fe6bb3c766ec5774979 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 16 May 2024 13:53:54 -0700
Subject: [PATCH 088/122] chore: updates

---
 py/torch_tensorrt/dynamo/_compiler.py                      | 2 +-
 py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py | 2 +-
 .../dynamo/lowering/passes/_aten_lowering_pass.py          | 7 +++----
 3 files changed, 5 insertions(+), 6 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/_compiler.py b/py/torch_tensorrt/dynamo/_compiler.py
index 540caad3b1..68e73e58f1 100644
--- a/py/torch_tensorrt/dynamo/_compiler.py
+++ b/py/torch_tensorrt/dynamo/_compiler.py
@@ -177,7 +177,7 @@ def compile(
         raise AssertionError(
             f"Input graph should be an ExportedProgram but got type {type(exported_program)}"
         )
-
+    exported_program = pre_export_lowering(exported_program, torch_inputs)
     exported_program = exported_program.run_decompositions(
         get_decompositions(enable_experimental_decompositions)
     )
diff --git a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
index 0fed20a9fd..e8f10489be 100644
--- a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
+++ b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
@@ -571,7 +571,7 @@ def aten_ops_neg(
     assert torch.ops.trt.quantize_fp8.default
 except Exception as e:
     _LOGGER.warning(
-        f"Unable to import quantize_fp8 op.: {e}. Please install nvidia-ammo library in order to register torch.ops.trt.quantize_fp8 op"
+        "Unable to import torch.ops.trt.quantize_fp8 op. Please install modelopt library (https://github.com/NVIDIA/TensorRT-Model-Optimizer?tab=readme-ov-file#installation) to register torch.ops.trt.quantize_fp8 op"
     )
 else:
 
diff --git a/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py b/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py
index 05a171e264..d73f234871 100644
--- a/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py
+++ b/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py
@@ -103,11 +103,10 @@ def pre_export_lowering(
     logging.debug(
         f"Invoking DynamoPassManager and applying lowering passes: {ATEN_PRE_LOWERING_PASSES}"
     )
-    gm = ep.module()
+    gm = ep._graph_module
     gm = ATEN_PRE_LOWERING_PASSES(gm, sample_inputs)
-    # TODO: Check if re-exporting changes the metadata
-    transformed_ep = torch.export.export(gm, tuple(sample_inputs), strict=False)
-    return transformed_ep
+    ep._graph_module = gm
+    return ep
 
 
 def dump_lowering_passes() -> str:

From 8cb6b91c121715bb9255ff4b914a4c6c7f217fa0 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 16 May 2024 16:25:04 -0700
Subject: [PATCH 089/122] chore: updates

---
 .../dynamo/lowering/passes/_aten_lowering_pass.py              | 3 +--
 tests/py/dynamo/models/test_models_export.py                   | 3 ++-
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py b/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py
index d73f234871..3d1663fe0b 100644
--- a/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py
+++ b/py/torch_tensorrt/dynamo/lowering/passes/_aten_lowering_pass.py
@@ -103,9 +103,8 @@ def pre_export_lowering(
     logging.debug(
         f"Invoking DynamoPassManager and applying lowering passes: {ATEN_PRE_LOWERING_PASSES}"
     )
-    gm = ep._graph_module
+    gm = ep.graph_module
     gm = ATEN_PRE_LOWERING_PASSES(gm, sample_inputs)
-    ep._graph_module = gm
     return ep
 
 
diff --git a/tests/py/dynamo/models/test_models_export.py b/tests/py/dynamo/models/test_models_export.py
index af9abc41f2..332872e6de 100644
--- a/tests/py/dynamo/models/test_models_export.py
+++ b/tests/py/dynamo/models/test_models_export.py
@@ -220,11 +220,12 @@ def calibrate_loop(model):
     with torch.no_grad():
         with export_torch_mode():
             exp_program = torch.export.export(model, (input_tensor,))
-            trt_model = torch_tensorrt.dynamo.compile(
+            trt_model = torchtrt.dynamo.compile(
                 exp_program,
                 inputs=[input_tensor],
                 enabled_precisions={torch.float8_e4m3fn},
                 min_block_size=1,
+                debug=True,
             )
             outputs_trt = trt_model(input_tensor)
             assert torch.allclose(output_pyt, outputs_trt, rtol=1e-3, atol=1e-2)

From 4d38368dd39c502ffaad176f05b66569f3d349ea Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 16 May 2024 16:31:52 -0700
Subject: [PATCH 090/122] chore: updates

---
 tests/py/dynamo/conversion/harness.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/tests/py/dynamo/conversion/harness.py b/tests/py/dynamo/conversion/harness.py
index 1c2727aa33..e93bb87743 100644
--- a/tests/py/dynamo/conversion/harness.py
+++ b/tests/py/dynamo/conversion/harness.py
@@ -204,8 +204,10 @@ def generate_graph(
         propagate_shapes: bool = False,
     ):
         mod = mod.eval()
+        torch_inputs = get_torch_inputs(original_inputs, _defaults.DEVICE)
         if use_dynamo_tracer:
             exported_program = torch_tensorrt.dynamo.trace(mod, tuple(original_inputs))
+            exported_program = pre_export_lowering(exported_program, torch_inputs)
             exported_program = exported_program.run_decompositions(
                 get_decompositions(False)
             )
@@ -218,7 +220,6 @@ def generate_graph(
 
         if propagate_shapes:
             # TODO: This is currently being used to test embedding_bag_aten due to https://github.com/pytorch/TensorRT/issues/2843
-            torch_inputs = get_torch_inputs(original_inputs, _defaults.DEVICE)
             try:
                 ShapeProp(fx_module).propagate(*torch_inputs)
             except (RuntimeError, AssertionError):

From ee54da64b3098fe3f21d29b8cfbf17edca948b02 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 16 May 2024 17:16:56 -0700
Subject: [PATCH 091/122] chore: updates

---
 py/torch_tensorrt/dynamo/backend/backends.py        |  4 ++++
 py/torch_tensorrt/dynamo/lowering/__init__.py       |  1 +
 .../dynamo/lowering/passes/remove_detach.py         | 13 +++----------
 3 files changed, 8 insertions(+), 10 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/backend/backends.py b/py/torch_tensorrt/dynamo/backend/backends.py
index 6d138c4d4d..870f1da692 100644
--- a/py/torch_tensorrt/dynamo/backend/backends.py
+++ b/py/torch_tensorrt/dynamo/backend/backends.py
@@ -13,6 +13,7 @@
 from torch_tensorrt.dynamo.lowering import (
     get_decompositions,
     post_lowering,
+    remove_detach,
     remove_sym_nodes,
     repair_input_aliasing,
 )
@@ -82,6 +83,9 @@ def _pretraced_backend(
                 input for input in sample_inputs if isinstance(input, torch.Tensor)
             ]
 
+            # Remove detach nodes
+            remove_detach(gm, torch_inputs)
+
             # Invoke AOTAutograd to translate operators to aten
             gm = aot_export_joint_simple(
                 gm,
diff --git a/py/torch_tensorrt/dynamo/lowering/__init__.py b/py/torch_tensorrt/dynamo/lowering/__init__.py
index ff2715fa5d..83c85855fe 100644
--- a/py/torch_tensorrt/dynamo/lowering/__init__.py
+++ b/py/torch_tensorrt/dynamo/lowering/__init__.py
@@ -6,3 +6,4 @@
 from ._remove_sym_nodes import remove_sym_nodes
 from ._repair_input_aliasing import repair_input_aliasing
 from .passes import post_lowering, pre_export_lowering
+from .passes.remove_detach import remove_detach
diff --git a/py/torch_tensorrt/dynamo/lowering/passes/remove_detach.py b/py/torch_tensorrt/dynamo/lowering/passes/remove_detach.py
index 5c47a8e288..5f1ab3738d 100644
--- a/py/torch_tensorrt/dynamo/lowering/passes/remove_detach.py
+++ b/py/torch_tensorrt/dynamo/lowering/passes/remove_detach.py
@@ -2,9 +2,6 @@
 from typing import Sequence
 
 import torch
-from torch_tensorrt.dynamo.lowering.passes.pass_utils import (
-    clean_up_graph_after_modifications,
-)
 
 logger = logging.getLogger(__name__)
 
@@ -13,20 +10,16 @@ def remove_detach(
     gm: torch.fx.GraphModule, sample_inputs: Sequence[torch.Tensor]
 ) -> torch.fx.GraphModule:
     """Remove detach ops in the graph"""
-
-    modified_graph = False
     count = 0
     for node in gm.graph.nodes:
-        # If the node is a detach node
-        if node.target == torch.ops.aten.detach.default:
+        # node.target = "detach" in torch.compile workflow
+        if node.target == torch.ops.aten.detach.default or node.target == "detach":
             # Detach node has only one input
             node_input = node.all_input_nodes[0]
             node.replace_all_uses_with(node_input)
             gm.graph.erase_node(node)
             count += 1
 
-    if modified_graph:
-        gm = clean_up_graph_after_modifications(gm)
-        logger.debug(f"Removed {count} detach nodes:\n{gm.graph}")
+    logger.debug(f"Removed {count} detach nodes:\n{gm.graph}")
 
     return gm

From f4ccd62ba7aceeeb1417e5c01333724bacd90b84 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 16 May 2024 18:31:01 -0700
Subject: [PATCH 092/122] chore: updates

---
 py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
index e8f10489be..7bba7a9da6 100644
--- a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
+++ b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
@@ -568,6 +568,8 @@ def aten_ops_neg(
 
 
 try:
+    import modelopt.torch.quantization as mtq
+
     assert torch.ops.trt.quantize_fp8.default
 except Exception as e:
     _LOGGER.warning(

From 681a6d1aae1dbc526d213c19d078681469f65623 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 17 May 2024 09:12:08 -0700
Subject: [PATCH 093/122] chore: fixes

---
 tests/py/dynamo/conversion/harness.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/tests/py/dynamo/conversion/harness.py b/tests/py/dynamo/conversion/harness.py
index e93bb87743..620ec36f56 100644
--- a/tests/py/dynamo/conversion/harness.py
+++ b/tests/py/dynamo/conversion/harness.py
@@ -17,7 +17,11 @@
 # Use interpreter, input spec, and test case from fx_ts_compat to test Dynamo Converter Registry
 from torch_tensorrt.dynamo.conversion import TRTInterpreter
 from torch_tensorrt.dynamo.conversion._conversion import infer_module_output_dtypes
-from torch_tensorrt.dynamo.lowering import get_decompositions, post_lowering
+from torch_tensorrt.dynamo.lowering import (
+    get_decompositions,
+    post_lowering,
+    pre_export_lowering,
+)
 from torch_tensorrt.dynamo.runtime import PythonTorchTensorRTModule
 from torch_tensorrt.dynamo.utils import get_torch_inputs
 

From 44071aa1ffd2b6a49bb0656684e092ccb9f035d5 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 17 May 2024 11:38:11 -0700
Subject: [PATCH 094/122] chore: updates

---
 .github/workflows/build-test.yml | 23 ++++++++---------------
 1 file changed, 8 insertions(+), 15 deletions(-)

diff --git a/.github/workflows/build-test.yml b/.github/workflows/build-test.yml
index 200dee7a6c..d89a842594 100644
--- a/.github/workflows/build-test.yml
+++ b/.github/workflows/build-test.yml
@@ -79,16 +79,15 @@ jobs:
       script: |
         export USE_HOST_DEPS=1
         export LD_LIBRARY_PATH=/usr/lib64:$LD_LIBRARY_PATH
-        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.1.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/modules
         # Don't use requirements.txt here as it contains tensorrt and torch which should have been installed by now.
-        ${CONDA_RUN} python -m pip install numpy packaging pyyaml transformers timm pybind11==2.6.2
+        ${CONDA_RUN} python -m pip install numpy packaging pyyaml transformers==4.40.2 timm==0.9.16 pybind11==2.6.2
         ${CONDA_RUN} python hub.py
         popd
         pushd .
         cd tests/py/ts
-        ${CONDA_RUN} python -m pip install --pre pytest timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
+        ${CONDA_RUN} python -m pip install --pre pytest timm==0.9.16 transformers==4.40.2 parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/ts_api_test_results.xml api/
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/ts_models_test_results.xml models/
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/ts_integrations_test_results.xml integrations/
@@ -117,10 +116,9 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
-        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.1.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
+        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm==0.9.16 transformers==4.40.2 parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_converters_test_results.xml -n 10 conversion/
         popd
 
@@ -147,10 +145,9 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
-        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.1.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre pytest timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
+        ${CONDA_RUN} python -m pip install --pre pytest timm==0.9.16 transformers==4.40.2 parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_fe_test_results.xml --ir dynamo models/test_models_export.py
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dyn_models_export.xml --ir dynamo models/test_dyn_models.py
         popd
@@ -178,10 +175,9 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
-        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.1.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre pytest timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
+        ${CONDA_RUN} python -m pip install --pre pytest timm==0.9.16 transformers==4.40.2 parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/export_serde_test_results.xml --ir dynamo models/test_export_serde.py
         popd
 
@@ -208,10 +204,9 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
-        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.1.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
+        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm==0.9.16 transformers==4.40.2 parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 10 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_compile_be_test_results.xml backend/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_comple_be_e2e_test_results.xml --ir torch_compile models/test_models.py
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_compile_dyn_models_export.xml --ir torch_compile models/test_dyn_models.py
@@ -240,10 +235,9 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
-        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.1.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
+        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm==0.9.16 transformers==4.40.2 parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_runtime_test_results.xml runtime/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_partitioning_test_results.xml partitioning/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_lowering_test_results.xml lowering/
@@ -272,9 +266,8 @@ jobs:
       pre-script: ${{ matrix.pre-script }}
       script: |
         export USE_HOST_DEPS=1
-        export LD_LIBRARY_PATH=/opt/torch-tensorrt-builds/TensorRT-10.0.1.6/lib:$LD_LIBRARY_PATH
         pushd .
         cd tests/py/core
-        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
+        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm==0.9.16 transformers==4.40.2 parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_core_test_results.xml .
         popd

From 3f6999d6ab2f9b62c63b78e8405cacf216370214 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 17 May 2024 13:25:08 -0700
Subject: [PATCH 095/122] chore: updates

---
 .github/workflows/build-test-windows.yml | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/build-test-windows.yml b/.github/workflows/build-test-windows.yml
index c7f1ba1d6b..66bcc86995 100644
--- a/.github/workflows/build-test-windows.yml
+++ b/.github/workflows/build-test-windows.yml
@@ -72,7 +72,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
+        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm==0.9.16 transformers==4.40.2 parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_converters_test_results.xml -n 10 conversion/
         popd
 
@@ -98,7 +98,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
+        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm==0.9.16 transformers==4.40.2 parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_fe_test_results.xml --ir dynamo models/test_models_export.py
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dyn_models_export.xml --ir dynamo models/test_dyn_models.py
         popd
@@ -125,7 +125,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
+        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm==0.9.16 transformers==4.40.2 parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 10 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_compile_be_test_results.xml backend/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_comple_be_e2e_test_results.xml --ir torch_compile models/test_models.py
         popd
@@ -152,7 +152,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm transformers parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
+        ${CONDA_RUN} python -m pip install --pre pytest-xdist timm==0.9.16 transformers==4.40.2 parameterized expecttest==0.1.6 --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_runtime_test_results.xml runtime/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_partitioning_test_results.xml partitioning/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_lowering_test_results.xml lowering/

From 5de9325b917ec2d49701919520f9d43b2cede576 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 17 May 2024 14:40:14 -0700
Subject: [PATCH 096/122] chore: updates

---
 py/torch_tensorrt/__init__.py | 3 ---
 1 file changed, 3 deletions(-)

diff --git a/py/torch_tensorrt/__init__.py b/py/torch_tensorrt/__init__.py
index 1b9faf08a8..156ec843dd 100644
--- a/py/torch_tensorrt/__init__.py
+++ b/py/torch_tensorrt/__init__.py
@@ -6,7 +6,6 @@
 
 from torch_tensorrt._version import (  # noqa: F401
     __cuda_version__,
-    __cudnn_version__,
     __tensorrt_version__,
     __version__,
 )
@@ -40,11 +39,9 @@ def _find_lib(name: str, paths: List[str]) -> str:
     import tensorrt  # noqa: F401
 except ImportError:
     cuda_version = _parse_semver(__cuda_version__)
-    cudnn_version = _parse_semver(__cudnn_version__)
     tensorrt_version = _parse_semver(__tensorrt_version__)
 
     CUDA_MAJOR = cuda_version["major"]
-    CUDNN_MAJOR = cudnn_version["major"]
     TENSORRT_MAJOR = tensorrt_version["major"]
 
     if sys.platform.startswith("win"):

From c677ef9612d40c1ada52ee6011c029e5dd9f49ef Mon Sep 17 00:00:00 2001
From: Evan Li <zewenl@nvidia.com>
Date: Tue, 21 May 2024 16:20:16 -0700
Subject: [PATCH 097/122] refactor vgg16 with fp8 and ptq example

---
 docsrc/index.rst                              |   1 +
 examples/dynamo/README.rst                    |   1 +
 examples/dynamo/vgg16_fp8_ptq.py              | 261 ++++++++++++++++++
 examples/int8/training/vgg16/requirements.txt |   2 +
 4 files changed, 265 insertions(+)
 create mode 100644 examples/dynamo/vgg16_fp8_ptq.py

diff --git a/docsrc/index.rst b/docsrc/index.rst
index 455aeab8b3..2842e3f9cd 100644
--- a/docsrc/index.rst
+++ b/docsrc/index.rst
@@ -111,6 +111,7 @@ Tutorials
    tutorials/_rendered_examples/dynamo/torch_compile_transformers_example
    tutorials/_rendered_examples/dynamo/torch_compile_advanced_usage
    tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion
+   tutorials/_rendered_examples/dynamo/vgg16_fp8_ptq
 
 Python API Documenation
 ------------------------
diff --git a/examples/dynamo/README.rst b/examples/dynamo/README.rst
index d895cc0113..cf8cd831c0 100644
--- a/examples/dynamo/README.rst
+++ b/examples/dynamo/README.rst
@@ -10,3 +10,4 @@ a number of ways you can leverage this backend to accelerate inference.
 * :ref:`torch_compile_transformer`: Compiling a Transformer model using ``torch.compile``
 * :ref:`torch_compile_advanced_usage`: Advanced usage including making a custom backend to use directly with the ``torch.compile`` API
 * :ref:`torch_compile_stable_diffusion`: Compiling a Stable Diffusion model using ``torch.compile``
+* :ref:`vgg16_fp8_ptq`: Compiling a VGG16 model with FP8 and PTQ using ``torch.compile``
diff --git a/examples/dynamo/vgg16_fp8_ptq.py b/examples/dynamo/vgg16_fp8_ptq.py
new file mode 100644
index 0000000000..5432dea7d6
--- /dev/null
+++ b/examples/dynamo/vgg16_fp8_ptq.py
@@ -0,0 +1,261 @@
+"""
+.. _vgg16_fp8_ptq:
+
+Torch Compile VGG16 with FP8 and PTQ
+======================================================
+
+This script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a VGG16 model with FP8 and PTQ.
+"""
+
+# %%
+# Imports and Model Definition
+# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+import argparse
+
+import modelopt.torch.quantization as mtq
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+import torch_tensorrt as torchtrt
+import torchvision.datasets as datasets
+import torchvision.transforms as transforms
+from modelopt.torch.quantization.utils import export_torch_mode
+
+
+class VGG(nn.Module):
+    def __init__(self, layer_spec, num_classes=1000, init_weights=False):
+        super(VGG, self).__init__()
+
+        layers = []
+        in_channels = 3
+        for l in layer_spec:
+            if l == "pool":
+                layers.append(nn.MaxPool2d(kernel_size=2, stride=2))
+            else:
+                layers += [
+                    nn.Conv2d(in_channels, l, kernel_size=3, padding=1),
+                    nn.BatchNorm2d(l),
+                    nn.ReLU(),
+                ]
+                in_channels = l
+
+        self.features = nn.Sequential(*layers)
+        self.avgpool = nn.AdaptiveAvgPool2d((1, 1))
+        self.classifier = nn.Sequential(
+            nn.Linear(512 * 1 * 1, 4096),
+            nn.ReLU(),
+            nn.Dropout(),
+            nn.Linear(4096, 4096),
+            nn.ReLU(),
+            nn.Dropout(),
+            nn.Linear(4096, num_classes),
+        )
+        if init_weights:
+            self._initialize_weights()
+
+    def _initialize_weights(self):
+        for m in self.modules():
+            if isinstance(m, nn.Conv2d):
+                nn.init.kaiming_normal_(m.weight, mode="fan_out", nonlinearity="relu")
+                if m.bias is not None:
+                    nn.init.constant_(m.bias, 0)
+            elif isinstance(m, nn.BatchNorm2d):
+                nn.init.constant_(m.weight, 1)
+                nn.init.constant_(m.bias, 0)
+            elif isinstance(m, nn.Linear):
+                nn.init.normal_(m.weight, 0, 0.01)
+                nn.init.constant_(m.bias, 0)
+
+    def forward(self, x):
+        x = self.features(x)
+        x = self.avgpool(x)
+        x = torch.flatten(x, 1)
+        x = self.classifier(x)
+        return x
+
+
+def vgg16(num_classes=1000, init_weights=False):
+    vgg16_cfg = [
+        64,
+        64,
+        "pool",
+        128,
+        128,
+        "pool",
+        256,
+        256,
+        256,
+        "pool",
+        512,
+        512,
+        512,
+        "pool",
+        512,
+        512,
+        512,
+        "pool",
+    ]
+    return VGG(vgg16_cfg, num_classes, init_weights)
+
+
+PARSER = argparse.ArgumentParser(
+    description="Load pre-trained VGG model and then tune with FP8 and PTQ"
+)
+PARSER.add_argument("--ckpt", type=str, help="Path to the pre-trained checkpoint")
+PARSER.add_argument(
+    "--batch-size",
+    default=128,
+    type=int,
+    help="Batch size for tuning the model with PTQ",
+)
+PARSER.add_argument(
+    "--fp8-epochs",
+    default=10,
+    type=int,
+    help="The number of epochs to quantize the model to FP8",
+)
+
+args = PARSER.parse_args()
+
+model = vgg16(num_classes=10, init_weights=False)
+model = model.cuda()
+
+# %%
+# Load the pre-trained model weights
+# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+ckpt = torch.load(args.ckpt)
+weights = ckpt["model_state_dict"]
+
+if torch.cuda.device_count() > 1:
+    from collections import OrderedDict
+
+    new_state_dict = OrderedDict()
+    for k, v in weights.items():
+        name = k[7:]  # remove `module.`
+        new_state_dict[name] = v
+    weights = new_state_dict
+
+model.load_state_dict(weights)
+# Don't forget to set the model to evaluation mode!
+model.eval()
+
+# %%
+# Load training dataset and define loss function for PTQ
+# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+training_dataset = datasets.CIFAR10(
+    root="./data",
+    train=True,
+    download=True,
+    transform=transforms.Compose(
+        [
+            transforms.RandomCrop(32, padding=4),
+            transforms.RandomHorizontalFlip(),
+            transforms.ToTensor(),
+            transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)),
+        ]
+    ),
+)
+training_dataloader = torch.utils.data.DataLoader(
+    training_dataset, batch_size=args.batch_size, shuffle=True, num_workers=2
+)
+
+data = iter(training_dataloader)
+images, _ = next(data)
+
+crit = nn.CrossEntropyLoss()
+
+# %%
+# Define Calibration Loop for quantization
+# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+
+def calibrate_loop(model):
+    # calibrate on a small number of batches
+    for fp8_ep in range(args.fp8_epochs):
+        print("Epoch: [%5d / %5d]" % (fp8_ep + 1, args.fp8_epochs))
+        total = 0
+        correct = 0
+        loss = 0.0
+        for data, labels in training_dataloader:
+            data, labels = data.cuda(), labels.cuda(non_blocking=True)
+            out = model(data)
+            loss += crit(out, labels)
+            preds = torch.max(out, 1)[1]
+            total += labels.size(0)
+            correct += (preds == labels).sum().item()
+
+        print(
+            "PTQ Training Loss: {:.5f} Acc: {:.2f}%".format(
+                loss / total, 100 * correct / total
+            )
+        )
+
+
+# %%
+# Tune the pre-trained model with FP8 and PTQ
+# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+quant_cfg = mtq.FP8_DEFAULT_CFG
+# PTQ with in-place replacement to quantized modules
+mtq.quantize(model, quant_cfg, forward_loop=calibrate_loop)
+# model has FP8 qdq nodes at this point
+
+# %%
+# Inference
+# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+# Load the testing dataset
+testing_dataset = datasets.CIFAR10(
+    root="./data",
+    train=False,
+    download=True,
+    transform=transforms.Compose(
+        [
+            transforms.ToTensor(),
+            transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)),
+        ]
+    ),
+)
+
+testing_dataloader = torch.utils.data.DataLoader(
+    testing_dataset, batch_size=args.batch_size, shuffle=False, num_workers=2
+)
+
+with torch.no_grad():
+    with export_torch_mode():
+        # Compile the model with Torch-TensorRT Dynamo backend
+        input_tensor = images.cuda()
+        exp_program = torch.export.export(model, (input_tensor,))
+        trt_model = torchtrt.dynamo.compile(
+            exp_program,
+            inputs=[input_tensor],
+            enabled_precisions={torch.float8_e4m3fn},
+            min_block_size=1,
+            debug=False,
+        )
+
+        # Inference compiled Torch-TensorRT model over the testing dataset
+        total = 0
+        correct = 0
+        loss = 0.0
+        class_probs = []
+        class_preds = []
+        model.eval()
+        for data, labels in testing_dataloader:
+            data, labels = data.cuda(), labels.cuda(non_blocking=True)
+            out = model(data)
+            loss += crit(out, labels)
+            preds = torch.max(out, 1)[1]
+            class_probs.append([F.softmax(i, dim=0) for i in out])
+            class_preds.append(preds)
+            total += labels.size(0)
+            correct += (preds == labels).sum().item()
+
+        test_probs = torch.cat([torch.stack(batch) for batch in class_probs])
+        test_preds = torch.cat(class_preds)
+        test_loss = loss / total
+        test_acc = correct / total
+        print("Test Loss: {:.5f} Test Acc: {:.2f}%".format(test_loss, 100 * test_acc))
diff --git a/examples/int8/training/vgg16/requirements.txt b/examples/int8/training/vgg16/requirements.txt
index d02af2c616..3b0b03f5d7 100644
--- a/examples/int8/training/vgg16/requirements.txt
+++ b/examples/int8/training/vgg16/requirements.txt
@@ -4,3 +4,5 @@ nvidia-pyindex
 --extra-index-url https://pypi.nvidia.com
 pytorch-quantization
 tqdm
+nvidia-modelopt
+--extra-index-url https://pypi.nvidia.com

From f0b8d47daf6a7f1e34a4f074b02c6b127601ed46 Mon Sep 17 00:00:00 2001
From: Evan Li <zewenl@nvidia.com>
Date: Wed, 22 May 2024 15:27:23 -0700
Subject: [PATCH 098/122] fix bugs

---
 examples/dynamo/vgg16_fp8_ptq.py | 44 ++++++++++++--------------------
 1 file changed, 17 insertions(+), 27 deletions(-)

diff --git a/examples/dynamo/vgg16_fp8_ptq.py b/examples/dynamo/vgg16_fp8_ptq.py
index 5432dea7d6..b2a82cc4f8 100644
--- a/examples/dynamo/vgg16_fp8_ptq.py
+++ b/examples/dynamo/vgg16_fp8_ptq.py
@@ -102,18 +102,14 @@ def vgg16(num_classes=1000, init_weights=False):
 PARSER = argparse.ArgumentParser(
     description="Load pre-trained VGG model and then tune with FP8 and PTQ"
 )
-PARSER.add_argument("--ckpt", type=str, help="Path to the pre-trained checkpoint")
 PARSER.add_argument(
-    "--batch-size",
-    default=128,
-    type=int,
-    help="Batch size for tuning the model with PTQ",
+    "--ckpt", type=str, required=True, help="Path to the pre-trained checkpoint"
 )
 PARSER.add_argument(
-    "--fp8-epochs",
-    default=10,
+    "--batch-size",
+    default=128,
     type=int,
-    help="The number of epochs to quantize the model to FP8",
+    help="Batch size for tuning the model with PTQ and FP8",
 )
 
 args = PARSER.parse_args()
@@ -173,25 +169,19 @@ def vgg16(num_classes=1000, init_weights=False):
 
 
 def calibrate_loop(model):
-    # calibrate on a small number of batches
-    for fp8_ep in range(args.fp8_epochs):
-        print("Epoch: [%5d / %5d]" % (fp8_ep + 1, args.fp8_epochs))
-        total = 0
-        correct = 0
-        loss = 0.0
-        for data, labels in training_dataloader:
-            data, labels = data.cuda(), labels.cuda(non_blocking=True)
-            out = model(data)
-            loss += crit(out, labels)
-            preds = torch.max(out, 1)[1]
-            total += labels.size(0)
-            correct += (preds == labels).sum().item()
-
-        print(
-            "PTQ Training Loss: {:.5f} Acc: {:.2f}%".format(
-                loss / total, 100 * correct / total
-            )
-        )
+    # calibrate over the training dataset
+    total = 0
+    correct = 0
+    loss = 0.0
+    for data, labels in training_dataloader:
+        data, labels = data.cuda(), labels.cuda(non_blocking=True)
+        out = model(data)
+        loss += crit(out, labels)
+        preds = torch.max(out, 1)[1]
+        total += labels.size(0)
+        correct += (preds == labels).sum().item()
+
+    print("PTQ Loss: {:.5f} Acc: {:.2f}%".format(loss / total, 100 * correct / total))
 
 
 # %%

From beb888dec855b029bbb2ae1905e2efe60c1323b1 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 23 May 2024 10:00:02 -0700
Subject: [PATCH 099/122] chore: updates

---
 py/torch_tensorrt/dynamo/conversion/impl/quantize.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/py/torch_tensorrt/dynamo/conversion/impl/quantize.py b/py/torch_tensorrt/dynamo/conversion/impl/quantize.py
index 478e8a5771..ac9252a182 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/quantize.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/quantize.py
@@ -23,7 +23,7 @@ def quantize_fp8(
     on the output_type set and dequantizes them back.
     """
     if (isinstance(input_tensor, TRTTensor)) and not (
-        input_tensor.dtype != trt.float32 or input_tensor.dtype != trt.float16
+        input_tensor.dtype == trt.float32 or input_tensor.dtype == trt.float16
     ):
         raise ValueError(
             f"quantize_fp8 converter received an input of {input_tensor.dtype} type. Supported types: float32 | float16"

From e7989a0185e30d10805e85dd259dbc7eba018a65 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Thu, 23 May 2024 12:14:04 -0700
Subject: [PATCH 100/122] chore: address review comments

---
 py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py | 2 +-
 py/torch_tensorrt/dynamo/conversion/impl/quantize.py       | 3 +--
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
index 4c17902882..9113d6ed22 100644
--- a/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
+++ b/py/torch_tensorrt/dynamo/conversion/aten_ops_converters.py
@@ -585,7 +585,7 @@ def aten_ops_neg(
     assert torch.ops.trt.quantize_fp8.default
 except Exception as e:
     _LOGGER.warning(
-        "Unable to import torch.ops.trt.quantize_fp8 op. Please install modelopt library (https://github.com/NVIDIA/TensorRT-Model-Optimizer?tab=readme-ov-file#installation) to register torch.ops.trt.quantize_fp8 op"
+        "Unable to import quantization op. Please install modelopt library (https://github.com/NVIDIA/TensorRT-Model-Optimizer?tab=readme-ov-file#installation) to add support for compiling quantized models"
     )
 else:
 
diff --git a/py/torch_tensorrt/dynamo/conversion/impl/quantize.py b/py/torch_tensorrt/dynamo/conversion/impl/quantize.py
index ac9252a182..de78385ce9 100644
--- a/py/torch_tensorrt/dynamo/conversion/impl/quantize.py
+++ b/py/torch_tensorrt/dynamo/conversion/impl/quantize.py
@@ -29,8 +29,7 @@ def quantize_fp8(
             f"quantize_fp8 converter received an input of {input_tensor.dtype} type. Supported types: float32 | float16"
         )
 
-    if isinstance(scale, np.ndarray):
-        scale = get_trt_tensor(ctx, scale, name + "_scale")
+    scale = get_trt_tensor(ctx, scale, name + "_scale")
     # Add Q node
     quantize_layer = ctx.net.add_quantize(input_tensor, scale)
     quantize_layer.set_output_type(0, trt.DataType.FP8)

From ad9d82507bb7d3bf0a708b9a83fab3ce77184b45 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 24 May 2024 11:08:41 -0700
Subject: [PATCH 101/122] chore: updates

---
 tests/py/dynamo/lowering/test_aten_lowering_passes.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/tests/py/dynamo/lowering/test_aten_lowering_passes.py b/tests/py/dynamo/lowering/test_aten_lowering_passes.py
index 0dd9a8de1c..d756ac8da2 100644
--- a/tests/py/dynamo/lowering/test_aten_lowering_passes.py
+++ b/tests/py/dynamo/lowering/test_aten_lowering_passes.py
@@ -2,9 +2,8 @@
 import unittest
 
 import torch
-from torch.testing._internal.common_utils import TestCase, run_tests
-
 import torch_tensorrt
+from torch.testing._internal.common_utils import TestCase, run_tests
 
 from ..testing_utilities import DECIMALS_OF_AGREEMENT, lower_graph_testing
 
@@ -397,6 +396,9 @@ def forward(self, q, k, v):
 
 
 class TestLowerLinear(TestCase):
+    @unittest.skip(
+        "This test has threshold failures. This is tracked at https://github.com/pytorch/TensorRT/issues/2715",
+    )
     def test_lower_linear(self):
         class Linear(torch.nn.Module):
             def forward(self, input, weight, bias):

From 0059c1c8888756c2fde47c8320dd5955c84cdfe9 Mon Sep 17 00:00:00 2001
From: Naren Dasan <1790613+narendasan@users.noreply.github.com>
Date: Fri, 24 May 2024 12:41:19 -0600
Subject: [PATCH 102/122] Update build-test-windows.yml

---
 .github/workflows/build-test-windows.yml | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/build-test-windows.yml b/.github/workflows/build-test-windows.yml
index 03c658ae6b..f39286167c 100644
--- a/.github/workflows/build-test-windows.yml
+++ b/.github/workflows/build-test-windows.yml
@@ -72,7 +72,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt
+        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_converters_test_results.xml -n 10 conversion/
         popd
 
@@ -98,7 +98,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt
+        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_fe_test_results.xml --ir dynamo models/test_models_export.py
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dyn_models_export.xml --ir dynamo models/test_dyn_models.py
         popd
@@ -125,7 +125,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt
+        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 10 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_compile_be_test_results.xml backend/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_comple_be_e2e_test_results.xml --ir torch_compile models/test_models.py
         popd
@@ -152,7 +152,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt
+        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_runtime_test_results.xml runtime/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_partitioning_test_results.xml partitioning/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_lowering_test_results.xml lowering/

From f98abd686f8088397493ff127d6a708edc642f1e Mon Sep 17 00:00:00 2001
From: Naren Dasan <1790613+narendasan@users.noreply.github.com>
Date: Fri, 24 May 2024 12:40:58 -0600
Subject: [PATCH 103/122] Update build-test-linux.yml

---
 .github/workflows/build-test-linux.yml | 14 +++++++-------
 1 file changed, 7 insertions(+), 7 deletions(-)

diff --git a/.github/workflows/build-test-linux.yml b/.github/workflows/build-test-linux.yml
index 1bad21deef..5de2d272ec 100644
--- a/.github/workflows/build-test-linux.yml
+++ b/.github/workflows/build-test-linux.yml
@@ -81,7 +81,7 @@ jobs:
         export LD_LIBRARY_PATH=/usr/lib64:$LD_LIBRARY_PATH
         pushd .
         cd tests/modules
-        ${CONDA_RUN} python -m pip install --pre -r ../py/requirements.txt
+        ${CONDA_RUN} python -m pip install --pre -r ../py/requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python hub.py
         popd
         pushd .
@@ -116,7 +116,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt
+        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_converters_test_results.xml -n 10 conversion/
         popd
 
@@ -145,7 +145,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt
+        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_fe_test_results.xml --ir dynamo models/test_models_export.py
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dyn_models_export.xml --ir dynamo models/test_dyn_models.py
         popd
@@ -175,7 +175,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt
+        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/export_serde_test_results.xml --ir dynamo models/test_export_serde.py
         popd
 
@@ -204,7 +204,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre  -r ../requirements.txt
+        ${CONDA_RUN} python -m pip install --pre  -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 10 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_compile_be_test_results.xml backend/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_comple_be_e2e_test_results.xml --ir torch_compile models/test_models.py
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_compile_dyn_models_export.xml --ir torch_compile models/test_dyn_models.py
@@ -235,7 +235,7 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt
+        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_runtime_test_results.xml runtime/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_partitioning_test_results.xml partitioning/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_lowering_test_results.xml lowering/
@@ -266,6 +266,6 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/core
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt
+        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_core_test_results.xml .
         popd

From 0d2021dcd4278e65f2860f23a78015eb60b3e2c1 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Fri, 24 May 2024 13:58:05 -0700
Subject: [PATCH 104/122] chore: updates

---
 .github/scripts/install-torch-tensorrt.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index 32d6613c10..fa4a72ae5f 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -2,7 +2,7 @@
 set -eou pipefail
 # Source conda so it's available to the script environment
 source ${BUILD_ENV_FILE}
-${CONDA_RUN} ${PIP_INSTALL_TORCH} torchvision
+${CONDA_RUN} ${PIP_INSTALL_TORCH} torchvision==0.18.0
 ${CONDA_RUN} python -m pip install pyyaml mpmath==1.3.0
 export TRT_VERSION=$(${CONDA_RUN} python -c "import versions; versions.tensorrt_version()")
 

From 1940267a28eb96136f112313822ad453009513a7 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 27 May 2024 01:05:00 -0700
Subject: [PATCH 105/122] chore: updates

---
 .../scripts/install-torch-tensorrt-windows.sh | 15 +++++++++++---
 .github/scripts/install-torch-tensorrt.sh     | 20 ++++++++++++++++---
 2 files changed, 29 insertions(+), 6 deletions(-)

diff --git a/.github/scripts/install-torch-tensorrt-windows.sh b/.github/scripts/install-torch-tensorrt-windows.sh
index 81adc4e1d5..c8c5e45dc4 100644
--- a/.github/scripts/install-torch-tensorrt-windows.sh
+++ b/.github/scripts/install-torch-tensorrt-windows.sh
@@ -1,12 +1,21 @@
 set -eou pipefail
 source "${BUILD_ENV_FILE}"
 
-# Install test index version of Torch and Torchvision
-${CONDA_RUN} ${PIP_INSTALL_TORCH} torchvision
+# Install stable versions of Torch and Torchvision since this is a release branch.
+# For main branches, the INDEX_URL will always point to nightly and for RC releases,
+# it will contain test tag in the url.
+export TORCH_VERSION_CI="2.3.0"
+export TORCHVISION_VERSION_CI="0.18.0"
+export TENSORRT_VERSION_CI="10.0.1"
+export INDEX_URL="https://download.pytorch.org/whl/${CU_VERSION}"
+
 ${CONDA_RUN} pip install pyyaml mpmath==1.3.0
 
+# Install appropriate torch and torchvision versions for the platform
+${CONDA_RUN} pip install torch==${TORCH_VERSION_CI} torchvision==${TORCHVISION_VERSION_CI} --index-url ${INDEX_URL}
+
 # Install TRT 10 from PyPi
-${CONDA_RUN} pip install tensorrt==10.0.0b6 tensorrt-${CU_VERSION::4}-bindings==10.0.0b6 tensorrt-${CU_VERSION::4}-libs==10.0.0b6 --extra-index-url https://pypi.nvidia.com
+${CONDA_RUN} pip install tensorrt==${TENSORRT_VERSION_CI}
 
 # Install pre-built Torch-TRT
 ${CONDA_RUN} pip install ${RUNNER_ARTIFACT_DIR}/torch_tensorrt*.whl
diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index fa4a72ae5f..822b3bcf0b 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -2,11 +2,25 @@
 set -eou pipefail
 # Source conda so it's available to the script environment
 source ${BUILD_ENV_FILE}
-${CONDA_RUN} ${PIP_INSTALL_TORCH} torchvision==0.18.0
+
+# Install stable versions of Torch and Torchvision since this is a release branch.
+# For main branches, the INDEX_URL will always point to nightly and for RC releases,
+# it will contain test tag in the url.
+export TORCH_VERSION_CI="2.3.0"
+export TORCHVISION_VERSION_CI="0.18.0"
+export TENSORRT_VERSION_CI="10.0.1"
+export INDEX_URL="https://download.pytorch.org/whl/${CU_VERSION}"
+
+
 ${CONDA_RUN} python -m pip install pyyaml mpmath==1.3.0
-export TRT_VERSION=$(${CONDA_RUN} python -c "import versions; versions.tensorrt_version()")
+
+# Install appropriate torch and torchvision versions for the platform
+${CONDA_RUN} pip install torch==${TORCH_VERSION_CI} torchvision==${TORCHVISION_VERSION_CI} --index-url ${INDEX_URL}
+
+# Install TRT 10 from PyPi
+${CONDA_RUN} pip install tensorrt==${TENSORRT_VERSION_CI}
 
 # Install Torch-TensorRT
-${CONDA_RUN} python -m pip install /opt/torch-tensorrt-builds/torch_tensorrt*+${CU_VERSION}*.whl tensorrt~=${TRT_VERSION} --extra-index-url=https://pypi.ngc.nvidia.com
+${CONDA_RUN} python -m pip install /opt/torch-tensorrt-builds/torch_tensorrt*+${CU_VERSION}*.whl
 
 echo -e "Running test script";

From 58144024f9392d8541792c6d89ae17ffd95be62c Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 27 May 2024 11:37:14 -0700
Subject: [PATCH 106/122] chore: disable all lower_linear tests

---
 tests/py/dynamo/lowering/test_aten_lowering_passes.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/tests/py/dynamo/lowering/test_aten_lowering_passes.py b/tests/py/dynamo/lowering/test_aten_lowering_passes.py
index d756ac8da2..840a556e44 100644
--- a/tests/py/dynamo/lowering/test_aten_lowering_passes.py
+++ b/tests/py/dynamo/lowering/test_aten_lowering_passes.py
@@ -466,6 +466,9 @@ def forward(self, input, weight, bias):
         )
         torch._dynamo.reset()
 
+    @unittest.skip(
+        "This test has threshold failures. This is tracked at https://github.com/pytorch/TensorRT/issues/2715",
+    )
     def test_lower_linear_batch(self):
         class Linear(torch.nn.Module):
             def forward(self, input, weight, bias):

From 338a92b952095c237571a80ab4fdb2da79b5fc93 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 27 May 2024 13:13:34 -0700
Subject: [PATCH 107/122] chore: updates

---
 .../scripts/install-torch-tensorrt-windows.sh | 17 ++++++------
 .github/scripts/install-torch-tensorrt.sh     | 19 +++++++-------
 versions.py                                   | 26 ++++++++++++++++++-
 3 files changed, 43 insertions(+), 19 deletions(-)

diff --git a/.github/scripts/install-torch-tensorrt-windows.sh b/.github/scripts/install-torch-tensorrt-windows.sh
index c8c5e45dc4..00cc5aa32d 100644
--- a/.github/scripts/install-torch-tensorrt-windows.sh
+++ b/.github/scripts/install-torch-tensorrt-windows.sh
@@ -1,18 +1,19 @@
 set -eou pipefail
 source "${BUILD_ENV_FILE}"
 
+# Install pyyaml first to parse dev_dep_versions.yml in versions.py
+${CONDA_RUN} pip install pyyaml
+
 # Install stable versions of Torch and Torchvision since this is a release branch.
 # For main branches, the INDEX_URL will always point to nightly and for RC releases,
 # it will contain test tag in the url.
-export TORCH_VERSION_CI="2.3.0"
-export TORCHVISION_VERSION_CI="0.18.0"
-export TENSORRT_VERSION_CI="10.0.1"
-export INDEX_URL="https://download.pytorch.org/whl/${CU_VERSION}"
-
-${CONDA_RUN} pip install pyyaml mpmath==1.3.0
+export TORCH_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.torch_version()")
+export TORCHVISION_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.torchvision_version()")
+export TENSORRT_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.tensorrt_version()")
+export INDEX_URL_CI=$(${CONDA_RUN} python -c "import versions; versions.index_url()")
 
 # Install appropriate torch and torchvision versions for the platform
-${CONDA_RUN} pip install torch==${TORCH_VERSION_CI} torchvision==${TORCHVISION_VERSION_CI} --index-url ${INDEX_URL}
+${CONDA_RUN} pip install torch==${TORCH_VERSION_CI} torchvision==${TORCHVISION_VERSION_CI} --index-url ${INDEX_URL_CI}
 
 # Install TRT 10 from PyPi
 ${CONDA_RUN} pip install tensorrt==${TENSORRT_VERSION_CI}
@@ -20,4 +21,4 @@ ${CONDA_RUN} pip install tensorrt==${TENSORRT_VERSION_CI}
 # Install pre-built Torch-TRT
 ${CONDA_RUN} pip install ${RUNNER_ARTIFACT_DIR}/torch_tensorrt*.whl
 
-echo -e "Running test script";
+echo -e "Running test script";
\ No newline at end of file
diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index 822b3bcf0b..367fb14ddd 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -3,24 +3,23 @@ set -eou pipefail
 # Source conda so it's available to the script environment
 source ${BUILD_ENV_FILE}
 
+# Install pyyaml first to parse dev_dep_versions.yml in versions.py
+${CONDA_RUN} python -m pip install pyyaml
+
 # Install stable versions of Torch and Torchvision since this is a release branch.
 # For main branches, the INDEX_URL will always point to nightly and for RC releases,
 # it will contain test tag in the url.
-export TORCH_VERSION_CI="2.3.0"
-export TORCHVISION_VERSION_CI="0.18.0"
-export TENSORRT_VERSION_CI="10.0.1"
-export INDEX_URL="https://download.pytorch.org/whl/${CU_VERSION}"
-
-
-${CONDA_RUN} python -m pip install pyyaml mpmath==1.3.0
+export TORCH_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.torch_version()")
+export TORCHVISION_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.torchvision_version()")
+export TENSORRT_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.tensorrt_version()")
+export INDEX_URL_CI=$(${CONDA_RUN} python -c "import versions; versions.index_url()")
 
 # Install appropriate torch and torchvision versions for the platform
-${CONDA_RUN} pip install torch==${TORCH_VERSION_CI} torchvision==${TORCHVISION_VERSION_CI} --index-url ${INDEX_URL}
+${CONDA_RUN} pip install torch==${TORCH_VERSION_CI} torchvision==${TORCHVISION_VERSION_CI} --index-url ${INDEX_URL_CI}
 
 # Install TRT 10 from PyPi
 ${CONDA_RUN} pip install tensorrt==${TENSORRT_VERSION_CI}
 
 # Install Torch-TensorRT
 ${CONDA_RUN} python -m pip install /opt/torch-tensorrt-builds/torch_tensorrt*+${CU_VERSION}*.whl
-
-echo -e "Running test script";
+echo -e "Running test script";
\ No newline at end of file
diff --git a/versions.py b/versions.py
index db418a06d2..cf9b3603bd 100644
--- a/versions.py
+++ b/versions.py
@@ -10,7 +10,12 @@
 __cuda_version__ = "0.0"
 __cudnn_version__ = "0.0"
 __tensorrt_version__ = "0.0"
-
+# The following variables are used to install the correct versions of torch & torchvision in CI
+__torch_version__ = "0.0"
+__torchvision_version__ = "0.0"
+# / is necessary at the end
+__index_url__ = "https://download.pytorch.org/whl/test/"
+DEFAULT_CUDA_INDEX = "cu121"
 
 LEADING_V_PATTERN = re.compile("^v")
 TRAILING_RC_PATTERN = re.compile("-rc[0-9]*$")
@@ -106,6 +111,9 @@ def load_dep_info():
     global __cuda_version__
     global __cudnn_version__
     global __tensorrt_version__
+    global __torch_version__
+    global __torchvision_version__
+    global __index_url__
     with open("dev_dep_versions.yml", "r") as stream:
         versions = yaml.safe_load(stream)
         gpu_arch_version = os.environ.get("CU_VERSION")
@@ -113,10 +121,14 @@ def load_dep_info():
             __cuda_version__ = (
                 (gpu_arch_version[2:])[:-1] + "." + (gpu_arch_version[2:])[-1:]
             )
+            __index_url__ = versions["__index_url__"] + gpu_arch_version
         else:
             __cuda_version__ = versions["__cuda_version__"]
+            __index_url__ = versions["__index_url__"] + DEFAULT_CUDA_INDEX
         __cudnn_version__ = versions["__cudnn_version__"]
         __tensorrt_version__ = versions["__tensorrt_version__"]
+        __torch_version__ = versions["__torch_version__"]
+        __torchvision_version__ = versions["__torchvision_version__"]
 
 
 load_dep_info()
@@ -147,3 +159,15 @@ def cudnn_version():
 
 def tensorrt_version():
     print(__tensorrt_version__)
+
+
+def torch_version():
+    print(__torch_version__)
+
+
+def torchvision_version():
+    print(__torchvision_version__)
+
+
+def index_url():
+    print(__index_url__)

From 59d0bd0ef5b434d1f24f3f792882b7cddd6883b5 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 27 May 2024 13:53:50 -0700
Subject: [PATCH 108/122] chore: fixes

---
 dev_dep_versions.yml | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/dev_dep_versions.yml b/dev_dep_versions.yml
index 2838da15c5..3f11248ce1 100644
--- a/dev_dep_versions.yml
+++ b/dev_dep_versions.yml
@@ -2,3 +2,7 @@ __version__: "2.3.0"
 __cuda_version__: "12.1"
 __cudnn_version__: "8.9"
 __tensorrt_version__: "10.0.1"
+__torch_version__: "2.3.0"
+# torchvision version here is not a direct dependency but the one used during testing
+__torchvision_version__: "0.18.0"
+__index_url__: "https://download.pytorch.org/whl/test/"
\ No newline at end of file

From 020fe63916c7039781445b1f352db611576e8da1 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 27 May 2024 15:19:50 -0700
Subject: [PATCH 109/122] chore: updates

---
 .../scripts/install-torch-tensorrt-windows.sh | 24 -------------------
 .github/scripts/install-torch-tensorrt.sh     |  6 ++++-
 2 files changed, 5 insertions(+), 25 deletions(-)
 delete mode 100644 .github/scripts/install-torch-tensorrt-windows.sh

diff --git a/.github/scripts/install-torch-tensorrt-windows.sh b/.github/scripts/install-torch-tensorrt-windows.sh
deleted file mode 100644
index 00cc5aa32d..0000000000
--- a/.github/scripts/install-torch-tensorrt-windows.sh
+++ /dev/null
@@ -1,24 +0,0 @@
-set -eou pipefail
-source "${BUILD_ENV_FILE}"
-
-# Install pyyaml first to parse dev_dep_versions.yml in versions.py
-${CONDA_RUN} pip install pyyaml
-
-# Install stable versions of Torch and Torchvision since this is a release branch.
-# For main branches, the INDEX_URL will always point to nightly and for RC releases,
-# it will contain test tag in the url.
-export TORCH_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.torch_version()")
-export TORCHVISION_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.torchvision_version()")
-export TENSORRT_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.tensorrt_version()")
-export INDEX_URL_CI=$(${CONDA_RUN} python -c "import versions; versions.index_url()")
-
-# Install appropriate torch and torchvision versions for the platform
-${CONDA_RUN} pip install torch==${TORCH_VERSION_CI} torchvision==${TORCHVISION_VERSION_CI} --index-url ${INDEX_URL_CI}
-
-# Install TRT 10 from PyPi
-${CONDA_RUN} pip install tensorrt==${TENSORRT_VERSION_CI}
-
-# Install pre-built Torch-TRT
-${CONDA_RUN} pip install ${RUNNER_ARTIFACT_DIR}/torch_tensorrt*.whl
-
-echo -e "Running test script";
\ No newline at end of file
diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index 367fb14ddd..5f33addb74 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -21,5 +21,9 @@ ${CONDA_RUN} pip install torch==${TORCH_VERSION_CI} torchvision==${TORCHVISION_V
 ${CONDA_RUN} pip install tensorrt==${TENSORRT_VERSION_CI}
 
 # Install Torch-TensorRT
-${CONDA_RUN} python -m pip install /opt/torch-tensorrt-builds/torch_tensorrt*+${CU_VERSION}*.whl
+${CONDA_RUN} pip install /opt/torch-tensorrt-builds/torch_tensorrt*+${CU_VERSION}*.whl
+
+# Install additional libraries like timm/transformers which are used during testing
+${CONDA_RUN} pip install --pre -r tests/py/requirements.txt --use-deprecated=legacy-resolver
+
 echo -e "Running test script";
\ No newline at end of file

From 3f8297eb6301f6b08d93ee68d1aa80a3205b9cb0 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 27 May 2024 15:20:11 -0700
Subject: [PATCH 110/122] chore: updates

---
 .github/workflows/build-test-linux.yml | 7 -------
 .github/workflows/windows-test.yml     | 2 +-
 2 files changed, 1 insertion(+), 8 deletions(-)

diff --git a/.github/workflows/build-test-linux.yml b/.github/workflows/build-test-linux.yml
index 5de2d272ec..04fc69de33 100644
--- a/.github/workflows/build-test-linux.yml
+++ b/.github/workflows/build-test-linux.yml
@@ -81,7 +81,6 @@ jobs:
         export LD_LIBRARY_PATH=/usr/lib64:$LD_LIBRARY_PATH
         pushd .
         cd tests/modules
-        ${CONDA_RUN} python -m pip install --pre -r ../py/requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python hub.py
         popd
         pushd .
@@ -116,7 +115,6 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_converters_test_results.xml -n 10 conversion/
         popd
 
@@ -145,7 +143,6 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_fe_test_results.xml --ir dynamo models/test_models_export.py
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dyn_models_export.xml --ir dynamo models/test_dyn_models.py
         popd
@@ -175,7 +172,6 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/export_serde_test_results.xml --ir dynamo models/test_export_serde.py
         popd
 
@@ -204,7 +200,6 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre  -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 10 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_compile_be_test_results.xml backend/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_comple_be_e2e_test_results.xml --ir torch_compile models/test_models.py
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_compile_dyn_models_export.xml --ir torch_compile models/test_dyn_models.py
@@ -235,7 +230,6 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_runtime_test_results.xml runtime/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_partitioning_test_results.xml partitioning/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_lowering_test_results.xml lowering/
@@ -266,6 +260,5 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/core
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_core_test_results.xml .
         popd
diff --git a/.github/workflows/windows-test.yml b/.github/workflows/windows-test.yml
index b00b4c3dd1..2d61068b1a 100644
--- a/.github/workflows/windows-test.yml
+++ b/.github/workflows/windows-test.yml
@@ -118,7 +118,7 @@ jobs:
           {
             echo "${SCRIPT}";
           } > "user_script"
-          cat .github/scripts/install-torch-tensorrt-windows.sh user_script > exec_script
+          cat .github/scripts/install-torch-tensorrt.sh user_script > exec_script
       - name: Run script
         uses: ./test-infra/.github/actions/run-script-with-cache
         with:

From 5ce0ee19a7330e5725523d35102ed243efdbdcea Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 27 May 2024 15:21:13 -0700
Subject: [PATCH 111/122] chore: updates

---
 .github/workflows/build-test-windows.yml | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/.github/workflows/build-test-windows.yml b/.github/workflows/build-test-windows.yml
index f39286167c..d745e5c7d0 100644
--- a/.github/workflows/build-test-windows.yml
+++ b/.github/workflows/build-test-windows.yml
@@ -72,7 +72,6 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_converters_test_results.xml -n 10 conversion/
         popd
 
@@ -98,7 +97,6 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dynamo_fe_test_results.xml --ir dynamo models/test_models_export.py
         ${CONDA_RUN} python -m pytest --junitxml=${RUNNER_TEST_RESULTS_DIR}/dyn_models_export.xml --ir dynamo models/test_dyn_models.py
         popd
@@ -125,7 +123,6 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 10 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_compile_be_test_results.xml backend/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/torch_comple_be_e2e_test_results.xml --ir torch_compile models/test_models.py
         popd
@@ -152,7 +149,6 @@ jobs:
         export USE_HOST_DEPS=1
         pushd .
         cd tests/py/dynamo
-        ${CONDA_RUN} python -m pip install --pre -r ../requirements.txt --use-deprecated=legacy-resolver
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_runtime_test_results.xml runtime/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_partitioning_test_results.xml partitioning/
         ${CONDA_RUN} python -m pytest -n 4 --junitxml=${RUNNER_TEST_RESULTS_DIR}/tests_py_dynamo_core_lowering_test_results.xml lowering/

From 65c5c3e24dc9ea7ba970151ed1c67319b47559ec Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 27 May 2024 20:42:24 -0700
Subject: [PATCH 112/122] chore: updates

---
 .github/scripts/install-torch-tensorrt.sh | 22 +++-----------------
 packaging/pre_build_script.sh             |  1 -
 packaging/pre_build_script_windows.sh     |  2 +-
 versions.py                               | 25 -----------------------
 4 files changed, 4 insertions(+), 46 deletions(-)

diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index 5f33addb74..90f665d20f 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -2,28 +2,12 @@
 set -eou pipefail
 # Source conda so it's available to the script environment
 source ${BUILD_ENV_FILE}
+export EXTRA_INDEX_URL="https://download.pytorch.org/whl/nightly/${CU_VERSION}"
 
-# Install pyyaml first to parse dev_dep_versions.yml in versions.py
-${CONDA_RUN} python -m pip install pyyaml
-
-# Install stable versions of Torch and Torchvision since this is a release branch.
-# For main branches, the INDEX_URL will always point to nightly and for RC releases,
-# it will contain test tag in the url.
-export TORCH_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.torch_version()")
-export TORCHVISION_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.torchvision_version()")
-export TENSORRT_VERSION_CI=$(${CONDA_RUN} python -c "import versions; versions.tensorrt_version()")
-export INDEX_URL_CI=$(${CONDA_RUN} python -c "import versions; versions.index_url()")
-
-# Install appropriate torch and torchvision versions for the platform
-${CONDA_RUN} pip install torch==${TORCH_VERSION_CI} torchvision==${TORCHVISION_VERSION_CI} --index-url ${INDEX_URL_CI}
-
-# Install TRT 10 from PyPi
-${CONDA_RUN} pip install tensorrt==${TENSORRT_VERSION_CI}
+# Install all the dependencies required for Torch-TensorRT
+${CONDA_RUN} pip install --pre -r ${PWD}/tests/py/requirements.txt --use-deprecated=legacy-resolver --extra-index-url=${EXTRA_INDEX_URL}
 
 # Install Torch-TensorRT
 ${CONDA_RUN} pip install /opt/torch-tensorrt-builds/torch_tensorrt*+${CU_VERSION}*.whl
 
-# Install additional libraries like timm/transformers which are used during testing
-${CONDA_RUN} pip install --pre -r tests/py/requirements.txt --use-deprecated=legacy-resolver
-
 echo -e "Running test script";
\ No newline at end of file
diff --git a/packaging/pre_build_script.sh b/packaging/pre_build_script.sh
index 59dd3774fe..a8833361e1 100755
--- a/packaging/pre_build_script.sh
+++ b/packaging/pre_build_script.sh
@@ -3,7 +3,6 @@
 # Install dependencies
 python3 -m pip install pyyaml
 yum install -y ninja-build gettext
-TRT_VERSION=$(python3 -c "import versions; versions.tensorrt_version()")
 
 wget https://github.com/bazelbuild/bazelisk/releases/download/v1.17.0/bazelisk-linux-amd64 \
     && mv bazelisk-linux-amd64 /usr/bin/bazel \
diff --git a/packaging/pre_build_script_windows.sh b/packaging/pre_build_script_windows.sh
index 2004966613..51d3e1499e 100644
--- a/packaging/pre_build_script_windows.sh
+++ b/packaging/pre_build_script_windows.sh
@@ -1,7 +1,7 @@
 python -m pip install -U numpy packaging pyyaml setuptools wheel
 
 # Install TRT 10 from PyPi
-python -m pip install tensorrt==10.0.0b6 tensorrt-${CU_VERSION::4}-bindings==10.0.0b6 tensorrt-${CU_VERSION::4}-libs==10.0.0b6 --extra-index-url https://pypi.nvidia.com
+python -m pip install tensorrt==10.0.1 --extra-index-url https://pypi.nvidia.com
 
 choco install bazelisk -y
 
diff --git a/versions.py b/versions.py
index cf9b3603bd..7f8d8a445c 100644
--- a/versions.py
+++ b/versions.py
@@ -10,12 +10,6 @@
 __cuda_version__ = "0.0"
 __cudnn_version__ = "0.0"
 __tensorrt_version__ = "0.0"
-# The following variables are used to install the correct versions of torch & torchvision in CI
-__torch_version__ = "0.0"
-__torchvision_version__ = "0.0"
-# / is necessary at the end
-__index_url__ = "https://download.pytorch.org/whl/test/"
-DEFAULT_CUDA_INDEX = "cu121"
 
 LEADING_V_PATTERN = re.compile("^v")
 TRAILING_RC_PATTERN = re.compile("-rc[0-9]*$")
@@ -111,9 +105,6 @@ def load_dep_info():
     global __cuda_version__
     global __cudnn_version__
     global __tensorrt_version__
-    global __torch_version__
-    global __torchvision_version__
-    global __index_url__
     with open("dev_dep_versions.yml", "r") as stream:
         versions = yaml.safe_load(stream)
         gpu_arch_version = os.environ.get("CU_VERSION")
@@ -121,14 +112,10 @@ def load_dep_info():
             __cuda_version__ = (
                 (gpu_arch_version[2:])[:-1] + "." + (gpu_arch_version[2:])[-1:]
             )
-            __index_url__ = versions["__index_url__"] + gpu_arch_version
         else:
             __cuda_version__ = versions["__cuda_version__"]
-            __index_url__ = versions["__index_url__"] + DEFAULT_CUDA_INDEX
         __cudnn_version__ = versions["__cudnn_version__"]
         __tensorrt_version__ = versions["__tensorrt_version__"]
-        __torch_version__ = versions["__torch_version__"]
-        __torchvision_version__ = versions["__torchvision_version__"]
 
 
 load_dep_info()
@@ -159,15 +146,3 @@ def cudnn_version():
 
 def tensorrt_version():
     print(__tensorrt_version__)
-
-
-def torch_version():
-    print(__torch_version__)
-
-
-def torchvision_version():
-    print(__torchvision_version__)
-
-
-def index_url():
-    print(__index_url__)

From d99989d5f76eaddb1f1c7015d1e053027a567073 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 27 May 2024 20:45:54 -0700
Subject: [PATCH 113/122] chore: updates

---
 .github/scripts/install-torch-tensorrt.sh |  2 +-
 tests/py/requirements.txt                 | 10 ++++++++--
 2 files changed, 9 insertions(+), 3 deletions(-)

diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index 90f665d20f..f1b39e92d6 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -2,7 +2,7 @@
 set -eou pipefail
 # Source conda so it's available to the script environment
 source ${BUILD_ENV_FILE}
-export EXTRA_INDEX_URL="https://download.pytorch.org/whl/nightly/${CU_VERSION}"
+export EXTRA_INDEX_URL="https://download.pytorch.org/whl/test/${CU_VERSION}"
 
 # Install all the dependencies required for Torch-TensorRT
 ${CONDA_RUN} pip install --pre -r ${PWD}/tests/py/requirements.txt --use-deprecated=legacy-resolver --extra-index-url=${EXTRA_INDEX_URL}
diff --git a/tests/py/requirements.txt b/tests/py/requirements.txt
index 0df01cb0f2..db2c968a6a 100644
--- a/tests/py/requirements.txt
+++ b/tests/py/requirements.txt
@@ -1,6 +1,12 @@
+# This file is specifically to install correct version of libraries during CI testing.
+# The index url for torch & torchvision libs is configured in install-torch-tensorrt.sh based on CUDA version
 pytest>=8.2.1
 pytest-xdist>=3.6.1
+torch==2.3.0
+torchvision==0.18.0
+--extra-index-url https://pypi.ngc.nvidia.com
+pyyaml
+tensorrt==10.0.1
 timm>=1.0.3
 transformers==4.39.3
-parameterized>=0.2.0
-expecttest==0.1.6
\ No newline at end of file
+parameterized>=0.2.0
\ No newline at end of file

From 99dfbdc0b0927d32295977eb66b22d5f2ff9748c Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 27 May 2024 21:01:03 -0700
Subject: [PATCH 114/122] chore: updates

---
 tests/py/requirements.txt | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/tests/py/requirements.txt b/tests/py/requirements.txt
index db2c968a6a..ab718475f1 100644
--- a/tests/py/requirements.txt
+++ b/tests/py/requirements.txt
@@ -1,7 +1,9 @@
 # This file is specifically to install correct version of libraries during CI testing.
 # The index url for torch & torchvision libs is configured in install-torch-tensorrt.sh based on CUDA version
+# networkx library issue: https://discuss.pytorch.org/t/installing-pytorch-under-python-3-8-question-about-networkx-version/196740
 pytest>=8.2.1
 pytest-xdist>=3.6.1
+networkx==2.8.8
 torch==2.3.0
 torchvision==0.18.0
 --extra-index-url https://pypi.ngc.nvidia.com

From ad996a55e740511ade43447218b3e6362aa8c4fc Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Mon, 27 May 2024 21:47:51 -0700
Subject: [PATCH 115/122] chore: updates

---
 tests/py/requirements.txt | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/tests/py/requirements.txt b/tests/py/requirements.txt
index ab718475f1..bdb8ed48bc 100644
--- a/tests/py/requirements.txt
+++ b/tests/py/requirements.txt
@@ -11,4 +11,5 @@ pyyaml
 tensorrt==10.0.1
 timm>=1.0.3
 transformers==4.39.3
-parameterized>=0.2.0
\ No newline at end of file
+parameterized>=0.2.0
+expecttest==0.1.6
\ No newline at end of file

From 6ada35182c3ff3fd341e74d352fd0c953c178ba5 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 28 May 2024 10:42:49 -0700
Subject: [PATCH 116/122] chore: updates

---
 .github/scripts/install-torch-tensorrt.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index f1b39e92d6..a9bb2de410 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -8,6 +8,6 @@ export EXTRA_INDEX_URL="https://download.pytorch.org/whl/test/${CU_VERSION}"
 ${CONDA_RUN} pip install --pre -r ${PWD}/tests/py/requirements.txt --use-deprecated=legacy-resolver --extra-index-url=${EXTRA_INDEX_URL}
 
 # Install Torch-TensorRT
-${CONDA_RUN} pip install /opt/torch-tensorrt-builds/torch_tensorrt*+${CU_VERSION}*.whl
+${CONDA_RUN} pip install /opt/torch-tensorrt-builds/torch_tensorrt*.whl
 
 echo -e "Running test script";
\ No newline at end of file

From 88fd7ee68aa7a0be46e00295ec67f475f224a9bd Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 28 May 2024 12:08:13 -0700
Subject: [PATCH 117/122] chore: fixes

---
 .github/scripts/install-torch-tensorrt.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index a9bb2de410..955f4d830a 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -8,6 +8,6 @@ export EXTRA_INDEX_URL="https://download.pytorch.org/whl/test/${CU_VERSION}"
 ${CONDA_RUN} pip install --pre -r ${PWD}/tests/py/requirements.txt --use-deprecated=legacy-resolver --extra-index-url=${EXTRA_INDEX_URL}
 
 # Install Torch-TensorRT
-${CONDA_RUN} pip install /opt/torch-tensorrt-builds/torch_tensorrt*.whl
+${CONDA_RUN} pip install ${RUNNER_ARTIFACT_DIR}/torch_tensorrt*.whl
 
 echo -e "Running test script";
\ No newline at end of file

From 2511095105edd048ecc0a63a7702286c6db9b550 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Tue, 28 May 2024 13:43:37 -0700
Subject: [PATCH 118/122] chore: updates

---
 .github/scripts/install-torch-tensorrt.sh | 10 +++++++---
 1 file changed, 7 insertions(+), 3 deletions(-)

diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index 955f4d830a..176a5b5ce4 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -3,11 +3,15 @@ set -eou pipefail
 # Source conda so it's available to the script environment
 source ${BUILD_ENV_FILE}
 export EXTRA_INDEX_URL="https://download.pytorch.org/whl/test/${CU_VERSION}"
-
+export PLATFORM=$(${CONDA_RUN} python -c "import sys; print(sys.platform)")
 # Install all the dependencies required for Torch-TensorRT
 ${CONDA_RUN} pip install --pre -r ${PWD}/tests/py/requirements.txt --use-deprecated=legacy-resolver --extra-index-url=${EXTRA_INDEX_URL}
 
-# Install Torch-TensorRT
-${CONDA_RUN} pip install ${RUNNER_ARTIFACT_DIR}/torch_tensorrt*.whl
+# Install Torch-TensorRT via pre-built wheels. On windows, the location of wheels is not fixed.
+if ${PLATFORM} == "win32"; then
+    ${CONDA_RUN} pip install ${RUNNER_ARTIFACT_DIR}/torch_tensorrt*.whl
+else
+    ${CONDA_RUN} pip install /opt/torch-tensorrt-builds/torch_tensorrt*.whl
+fi
 
 echo -e "Running test script";
\ No newline at end of file

From 5346a4542c4be26ac7873943dcafe0b2cec01d15 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 29 May 2024 11:54:35 -0700
Subject: [PATCH 119/122] chore: updates

---
 .github/scripts/install-torch-tensorrt.sh | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index 176a5b5ce4..4833fd12f1 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -8,7 +8,7 @@ export PLATFORM=$(${CONDA_RUN} python -c "import sys; print(sys.platform)")
 ${CONDA_RUN} pip install --pre -r ${PWD}/tests/py/requirements.txt --use-deprecated=legacy-resolver --extra-index-url=${EXTRA_INDEX_URL}
 
 # Install Torch-TensorRT via pre-built wheels. On windows, the location of wheels is not fixed.
-if ${PLATFORM} == "win32"; then
+if [[ "$PLATFORM" == "win32" ]]; then
     ${CONDA_RUN} pip install ${RUNNER_ARTIFACT_DIR}/torch_tensorrt*.whl
 else
     ${CONDA_RUN} pip install /opt/torch-tensorrt-builds/torch_tensorrt*.whl

From d284b8f245217ac8343de77cbb16b0d70da07d6f Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 29 May 2024 13:23:04 -0700
Subject: [PATCH 120/122] chore: updates

---
 .github/workflows/windows-test.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/windows-test.yml b/.github/workflows/windows-test.yml
index 2d61068b1a..b00b4c3dd1 100644
--- a/.github/workflows/windows-test.yml
+++ b/.github/workflows/windows-test.yml
@@ -118,7 +118,7 @@ jobs:
           {
             echo "${SCRIPT}";
           } > "user_script"
-          cat .github/scripts/install-torch-tensorrt.sh user_script > exec_script
+          cat .github/scripts/install-torch-tensorrt-windows.sh user_script > exec_script
       - name: Run script
         uses: ./test-infra/.github/actions/run-script-with-cache
         with:

From c71c01785642340e41624be11817291fdabda591 Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 29 May 2024 13:23:18 -0700
Subject: [PATCH 121/122] chore: updates

---
 .github/scripts/install-torch-tensorrt-windows.sh | 13 +++++++++++++
 1 file changed, 13 insertions(+)
 create mode 100644 .github/scripts/install-torch-tensorrt-windows.sh

diff --git a/.github/scripts/install-torch-tensorrt-windows.sh b/.github/scripts/install-torch-tensorrt-windows.sh
new file mode 100644
index 0000000000..2c746ef435
--- /dev/null
+++ b/.github/scripts/install-torch-tensorrt-windows.sh
@@ -0,0 +1,13 @@
+#!/usr/bin/env bash
+set -eou pipefail
+# Source conda so it's available to the script environment
+source ${BUILD_ENV_FILE}
+export EXTRA_INDEX_URL="https://download.pytorch.org/whl/test/${CU_VERSION}"
+export PLATFORM=$(${CONDA_RUN} python -c "import sys; print(sys.platform)")
+# Install all the dependencies required for Torch-TensorRT
+${CONDA_RUN} pip install --pre -r ${PWD}/tests/py/requirements.txt --use-deprecated=legacy-resolver --extra-index-url=${EXTRA_INDEX_URL}
+
+# Install Torch-TensorRT via pre-built wheels. On windows, the location of wheels is not fixed.
+${CONDA_RUN} pip install ${RUNNER_ARTIFACT_DIR}/torch_tensorrt*.whl
+
+echo -e "Running test script";
\ No newline at end of file

From a983064318c42d0f110e36dc86fce82d1270c9ee Mon Sep 17 00:00:00 2001
From: Dheeraj Peri <peri.dheeraj@gmail.com>
Date: Wed, 29 May 2024 13:27:51 -0700
Subject: [PATCH 122/122] chore: updates

---
 .github/scripts/install-torch-tensorrt-windows.sh | 1 -
 .github/scripts/install-torch-tensorrt.sh         | 7 +------
 2 files changed, 1 insertion(+), 7 deletions(-)

diff --git a/.github/scripts/install-torch-tensorrt-windows.sh b/.github/scripts/install-torch-tensorrt-windows.sh
index 2c746ef435..bd8041a2e2 100644
--- a/.github/scripts/install-torch-tensorrt-windows.sh
+++ b/.github/scripts/install-torch-tensorrt-windows.sh
@@ -3,7 +3,6 @@ set -eou pipefail
 # Source conda so it's available to the script environment
 source ${BUILD_ENV_FILE}
 export EXTRA_INDEX_URL="https://download.pytorch.org/whl/test/${CU_VERSION}"
-export PLATFORM=$(${CONDA_RUN} python -c "import sys; print(sys.platform)")
 # Install all the dependencies required for Torch-TensorRT
 ${CONDA_RUN} pip install --pre -r ${PWD}/tests/py/requirements.txt --use-deprecated=legacy-resolver --extra-index-url=${EXTRA_INDEX_URL}
 
diff --git a/.github/scripts/install-torch-tensorrt.sh b/.github/scripts/install-torch-tensorrt.sh
index 4833fd12f1..90db1d5fca 100644
--- a/.github/scripts/install-torch-tensorrt.sh
+++ b/.github/scripts/install-torch-tensorrt.sh
@@ -3,15 +3,10 @@ set -eou pipefail
 # Source conda so it's available to the script environment
 source ${BUILD_ENV_FILE}
 export EXTRA_INDEX_URL="https://download.pytorch.org/whl/test/${CU_VERSION}"
-export PLATFORM=$(${CONDA_RUN} python -c "import sys; print(sys.platform)")
 # Install all the dependencies required for Torch-TensorRT
 ${CONDA_RUN} pip install --pre -r ${PWD}/tests/py/requirements.txt --use-deprecated=legacy-resolver --extra-index-url=${EXTRA_INDEX_URL}
 
 # Install Torch-TensorRT via pre-built wheels. On windows, the location of wheels is not fixed.
-if [[ "$PLATFORM" == "win32" ]]; then
-    ${CONDA_RUN} pip install ${RUNNER_ARTIFACT_DIR}/torch_tensorrt*.whl
-else
-    ${CONDA_RUN} pip install /opt/torch-tensorrt-builds/torch_tensorrt*.whl
-fi
+${CONDA_RUN} pip install /opt/torch-tensorrt-builds/torch_tensorrt*.whl
 
 echo -e "Running test script";
\ No newline at end of file