feat(aten::size [static]): Implement a aten::size converter for stati…

…c input size

Signed-off-by: Naren Dasan <naren@narendasan.com>
Signed-off-by: Naren Dasan <narens@nvidia.com>

core/conversion/conversion.cpp

@@ -78,7 +78,7 @@ void AddLayer(ConversionCtx* ctx, const torch::jit::Node* n) {
                 } else {
                     LOG_DEBUG(ctx->logger, "Found the value to be a tensor (shape " << eval.value().toTensor().sizes() << ')');
                 }
-                ctx->evaluated_value_map[input] = std::move(eval.value());
+                ctx->AssociateValueAndIValue(input, eval.value());
                 node_args.push_back(&(ctx->evaluated_value_map[input]));
             } else {
                 LOG_DEBUG(ctx->logger, "Found the value is None");;

core/conversion/conversionctx/ConversionCtx.cpp

@@ -103,9 +103,15 @@ nvinfer1::ITensor* ConversionCtx::AssociateValueAndTensor(const torch::jit::Valu
     return tensor;
 }
 
+torch::jit::IValue* ConversionCtx::AssociateValueAndIValue(const torch::jit::Value* value, torch::jit::IValue ivalue) {
+    this->evaluated_value_map[value] = std::move(ivalue);
+    return &this->evaluated_value_map[value];
+}
+
 std::string ConversionCtx::SerializeEngine() {
     auto engine = builder->buildEngineWithConfig(*net, *cfg);
     auto serialized_engine = engine->serialize();
+    engine->destroy();
     return std::string((const char*)serialized_engine->data(), serialized_engine->size());
 }
 

core/conversion/conversionctx/ConversionCtx.h

@@ -10,7 +10,6 @@
 
 #include "core/util/prelude.h"
 
-
 namespace trtorch {
 namespace core {
 namespace conversion {
@@ -39,6 +38,7 @@ struct ConversionCtx {
     ConversionCtx(BuilderSettings settings);
     std::string SerializeEngine();
     nvinfer1::ITensor* AssociateValueAndTensor(const torch::jit::Value* value, nvinfer1::ITensor* tensor);
+    torch::jit::IValue* AssociateValueAndIValue(const torch::jit::Value* value, torch::jit::IValue tensor);
     bool CheckLayerAddition(const torch::jit::Node* n);
 
     ~ConversionCtx();

core/conversion/converters/BUILD

@@ -18,6 +18,7 @@ cc_library(
         "impl/matrix_multiply.cpp",
         "impl/pooling.cpp",
         "impl/reduce.cpp",
+        "impl/shape.cpp",
         "impl/shuffle.cpp",
         "impl/softmax.cpp",
         "impl/unary.cpp",

core/conversion/converters/impl/shape.cpp

@@ -0,0 +1,32 @@
+#include "core/conversion/converters/converters.h"
+
+#include "torch/torch.h"
+
+namespace trtorch {
+namespace core {
+namespace conversion {
+namespace converters {
+namespace impl {
+namespace {
+
+static auto shape_registrations = RegisterNodeConversionPatterns()
+  .pattern({
+    // To use in static input size cases (explicit batch)
+    "aten::size.int(Tensor self, int dim) -> (Tensor)",
+    [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
+      auto in = args[0].ITensor();
+      auto in_shape = util::toVec(in->getDimensions());
+
+      auto size = in_shape[args[1].unwrapToInt()];
+
+      ctx->AssociateValueAndIValue(n->outputs()[0], size);
+      LOG_DEBUG("Output Value: " << size);
+      return true;
+    }
+  });
+} // namespace
+} // namespace impl
+} // namespace converters
+} // namespace conversion
+} // namespace core
+} // namespace trtorch

core/conversion/converters/impl/shuffle.cpp

@@ -32,11 +32,12 @@ static auto shuffle_registrations = RegisterNodeConversionPatterns()
     "aten::reshape(Tensor self, int[] shape) -> (Tensor)",
     [](ConversionCtx* ctx, const torch::jit::Node* n, args& args) -> bool {
       auto in = args[0].ITensor();
-      auto new_shape = util::toDimsPad(args[1].unwrapToIntList(), 2);
+      auto in_shape = util::toVec(in->getDimensions());
+      auto new_shape = torch::reshape(torch::rand(in_shape), args[1].unwrapToIntList().vec()).sizes();
 
       auto shuffle = ctx->net->addShuffle(*in);
       TRTORCH_CHECK(shuffle, "Unable to create shuffle layer from node: " << *n);
-      shuffle->setReshapeDimensions(new_shape);
+      shuffle->setReshapeDimensions(util::toDims(new_shape));
       shuffle->setName(util::node_info(n).c_str());
 
       auto out_tensor = ctx->AssociateValueAndTensor(n->outputs()[0], shuffle->getOutput(0));

core/execution/TRTEngine.cpp

@@ -10,8 +10,6 @@ namespace trtorch {
 namespace core {
 namespace execution {
 
-TRTEngine::TRTEngine() {}
-
 TRTEngine::TRTEngine(nvinfer1::ILogger& logger, std::string& serialized_engine) {
     rt = nvinfer1::createInferRuntime(logger);
 

core/execution/execution.h

@@ -17,7 +17,7 @@ struct TRTEngine {
     std::pair<uint64_t, uint64_t> num_io;
     EngineID id;
 
-    TRTEngine();
+    TRTEngine() = default;
     TRTEngine(nvinfer1::ILogger& logger, std::string& serialized_engine);
     TRTEngine& operator=(const TRTEngine& other);
 };