Revert "[nvfuser_upstream_push] nvfuser code base bump 060822 (pytorc…

…h#79147)"

This reverts commit 49c41b8.

Reverted pytorch#79147 on behalf of https://github.com/janeyx99 due to Broke 11.3 builds on trunk https://hud.pytorch.org/pytorch/pytorch/commit/49c41b87a28848655d7fe8168e9a717d53508609

benchmarks/cpp/nvfuser/timm.cpp

@@ -692,7 +692,7 @@ static void nhwc_seresnet152d_transpose65(Fusion* fusion, void* null) {
   auto t17 = set(t16);
   auto t29 = castOp(DataType::Half, t17);
   auto t18 = mul(t17, t3);
-  auto t19 = permute(t18, {0, 2, 3, 1});
+  auto t19 = transpose(t18, {{0, 0}, {1, 3}, {2, 1}, {3, 2}});
   auto t30 = castOp(DataType::Half, t19);
 
   fusion->addOutput(t29);

benchmarks/cpp/nvfuser/transpose.cpp

@@ -81,8 +81,14 @@ static void setupTranspose(
   FusionGuard fg(fusion);
   typedef std::pair<int, int> transpose_axes;
 
-  auto optionalTranspose = [axes](TensorView* tv, bool is_transpose) {
-    return (is_transpose) ? transpose(tv, axes.first, axes.second) : tv;
+  auto getTransposeMap =
+      [](const transpose_axes& axes) -> std::unordered_map<int, int> {
+    return {{axes.first, axes.second}, {axes.second, axes.first}};
+  };
+
+  auto optionalTranspose = [&getTransposeMap, axes](
+                               TensorView* tv, bool is_transpose) {
+    return (is_transpose) ? transpose(tv, getTransposeMap(axes)) : tv;
   };
 
   auto input1 = makeContigTensor(num_dims);
@@ -408,8 +414,8 @@ static void Baseline_Transpose(
   auto at_input1 = aten_inputs[0];
   auto at_input2 = aten_inputs[1];
 
-  auto optionalTransposeAten = [&axes](at::Tensor x, bool is_transpose) {
-    return (is_transpose) ? at::transpose(x, axes.first, axes.second) : x;
+  auto optionalTransposeAten = [&axes](at::Tensor at, bool is_transpose) {
+    return (is_transpose) ? at::transpose(at, axes.first, axes.second) : at;
   };
 
   for (auto _ : benchmark_state) {

setup.py

@@ -1076,9 +1076,6 @@ def print_box(msg):
                 'include/torch/csrc/jit/testing/*.h',
                 'include/torch/csrc/jit/tensorexpr/*.h',
                 'include/torch/csrc/jit/tensorexpr/operators/*.h',
-                'include/torch/csrc/jit/codegen/cuda/*.h',
-                'include/torch/csrc/jit/codegen/cuda/ops/*.h',
-                'include/torch/csrc/jit/codegen/cuda/scheduler/*.h',
                 'include/torch/csrc/onnx/*.h',
                 'include/torch/csrc/profiler/*.h',
                 'include/torch/csrc/utils/*.h',

test/test_jit_cuda_fuser.py

@@ -2228,7 +2228,7 @@ def t(x, y):
             self.assertEqual(o.stride(), jit_o.stride())
         except Exception as e:
             warnings.warn(
-                "permutation propagation is broken, proper support should come after nvfuser permutation scheduler update")
+                "permutation propagatoin is broken, proper support should come after nvfuser permutation scheduler update")
         self.assertGraphContains(t_jit.graph_for(x, bias), FUSION_GUARD)
 
     @unittest.skipIf(not RUN_NVFUSER, "requires CUDA")