build: manually update PyTorch version (llvm#3896)

This commit sets the PyTorch and TorchVision version to nightly release
2024-12-01.

This commit also updates the test checks in
`test/python/fx_importer/v2.3/auto_functionalized.py`.

Failing tests are tracked through
llvm#3796.

---------

Signed-off-by: Vivek Khandelwal <vivekkhandelwal1424@gmail.com>

projects/pt1/e2e_testing/xfail_sets.py

@@ -514,8 +514,6 @@
     "RepeatInterleaveModule_basic",
     "RepeatInterleaveStaticModule_basic",
     "ScalarImplicitFloatModule_basic",
-    "SortIntListReverse_basic",
-    "SortIntList_basic",
     "SplitDimDynamicModule_basic",
     "SplitDimStaticModule_basic",
     "SqrtIntModule_basic",
@@ -557,27 +555,18 @@
     "CrossEntropyLossNoReductionModule_basic",
     "ElementwiseExpm1IntModule_basic",
     "ElementwiseExpm1Module_basic",
-    "IndexPutImpl1DFloatAccumulateModule_basic",
-    "IndexPutImpl1DFloatNonAccumulateModule_basic",
-    "IndexPutImpl1DIntAccumulateModule_basic",
-    "IndexPutImpl1DIntNonAccumulateModule_basic",
-    "IndexPutImpl2DFloatNonAccumulateModule_basic",
-    "IndexPutImpl2DImplicitModule_basic",
-    "IndexPutImpl2DIndexModule_basic",
-    "IndexPutImpl2DNoneIndexStaticModule_basic",
-    "IndexPutImpl3DFloatNonAccumulateModule_basic",
-    "IndexPutImplIndexWithNoneModule_basic",
     "InterpolateDynamicModule_sizes_nearest",
     "IouOfModule_basic",
     "MeshgridIndexingIJ_basic",
     "MeshgridIndexingXY_basic",
     "Meshgrid_basic",
-    "OneHotModule_basic",
     # RuntimeError: cannot mutate tensors with frozen storage
-    "ElementwiseRreluTrainModule_basic",
-    "ElementwiseRreluTrainStaticModule_basic",
     "ElementwiseRreluWithNoiseTrainModule_basic",
     "ElementwiseRreluWithNoiseTrainStaticModule_basic",
+    "BernoulliFloatModule_basic",
+    "BernoulliTensorModule_basic",
+    "UniformModule_basic",
+    "UniformStaticShapeModule_basic",
 }
 
 if torch_version_for_comparison() < version.parse("2.6.0.dev"):
@@ -920,8 +909,6 @@
     "ScatterValueFloatModule_basic",
     "ScatterValueIntModule_basic",
     "SliceOutOfLowerBoundEndIndexModule_basic",
-    "SortIntListReverse_basic",
-    "SortIntList_basic",
     "SortTensorDescending_basic",
     "SortTensorInteger_basic",
     "SortTensorNegativeDimension_basic",
@@ -1008,7 +995,6 @@
     "MeshgridIndexingXY_basic",
     "Meshgrid_basic",
     "MulIntModule_basic",
-    "OneHotModule_basic",
     "ReduceFrobeniusNormComplexModule_basic",
     "ScalarImplicitIntModule_basic",
     "ScaledDotProductAttentionBoolMaskModule_basic",
@@ -1027,10 +1013,11 @@
     "UpSampleNearest2dStaticSize_basic",
     "UpSampleNearest2d_basic",
     # RuntimeError: cannot mutate tensors with frozen storage
-    "ElementwiseRreluTrainModule_basic",
-    "ElementwiseRreluTrainStaticModule_basic",
     "ElementwiseRreluWithNoiseTrainModule_basic",
     "ElementwiseRreluWithNoiseTrainStaticModule_basic",
+    "BernoulliFloatModule_basic",
+    "UniformModule_basic",
+    "UniformStaticShapeModule_basic",
 }
 
 FX_IMPORTER_STABLEHLO_CRASHING_SET = {
@@ -1049,6 +1036,14 @@
     #  materialization callback produced value of incorrect type failed
     "ReduceMaxAlongDimUnsignedInt_basic",
     "ReduceMinAlongDimUnsignedInt_basic",
+    "Aten_TrilinearModuleSumdims_basic",
+    "Aten_TrilinearModuleSumAllDims_basic",
+    "Aten_TrilinearModuleVaryingRanksUnorderedExpands_basic",
+    # torch export: RuntimeError: cannot mutate tensors with frozen storage
+    "ElementwiseRreluWithNoiseTrainModule_basic",
+    "ElementwiseRreluWithNoiseTrainStaticModule_basic",
+    "CrossEntropyLossModule_basic",
+    "CrossEntropyLossNoReductionModule_basic",
 }
 
 STABLEHLO_PASS_SET = {

pytorch-hash.txt

@@ -1 +1 @@
-0d5247caf3ffd618d31cf4cf880c47b7dbd323a7
+798d5b7ddd08899fb62672d56044dbf1f63a4d17

pytorch-requirements.txt

@@ -4,4 +4,4 @@
 # release page, and we use this page as an additional source for the wheels.
 -f https://xilinx.github.io/torch-mlir/package-index/
 --pre
-torch==2.6.0.dev20241107
+torch==2.6.0.dev20241201

test/python/fx_importer/v2.3/auto_functionalized.py

@@ -59,8 +59,9 @@ def forward(self, x):
         # AssertionError: Current active mode <torch._subclasses.functional_tensor.FunctionalTensorMode object at 0x7a1106504fd0> not registered
         decomposition_table=[],
     )
-    # CHECK: %[[TIED:.*]] = torch.operator "torch.torch_mlir_test.inplace_modify"({{.*}}) : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32>
-    # CHECK: torch.aten.mul.Tensor %[[TIED]], %[[TIED]]
+    # The Torch 2.6 expects the IR to be same as the below one, while the torch versions < 2.6 does not, hence this check is kept as a "COM".
+    # COM: torch.operator "torch.torch_mlir_test.inplace_modify"({{.*}}) : (!torch.vtensor<[3,4],f32>) -> ()
+    # CHECK: torch.aten.mul.Tensor %{{.*}}, %{{.*}}
     print(m)
     m.operation.verify()
 
@@ -86,7 +87,8 @@ def forward(self, x):
         # AssertionError: Current active mode <torch._subclasses.functional_tensor.FunctionalTensorMode object at 0x7a1106504fd0> not registered
         decomposition_table=[],
     )
-    # CHECK: %[[TIED:.*]]:2 = torch.operator "torch.torch_mlir_test.inplace_modify_calc"(%0) : (!torch.vtensor<[3,4],f32>) -> (!torch.vtensor<[3,4],f32>, !torch.vtensor<[3,4],f32>)
-    # CHECK: torch.aten.mul.Tensor %[[TIED]]#1, %[[TIED]]#0
+    # The Torch 2.6 expects the IR to be same as the below one, while the torch versions < 2.6 does not, hence this check is kept as a "COM".
+    # COM: %[[TIED:.*]] = torch.operator "torch.torch_mlir_test.inplace_modify_calc"(%arg0) : (!torch.vtensor<[3,4],f32>) -> !torch.vtensor<[3,4],f32>
+    # CHECK: torch.aten.mul.Tensor %{{.*}}, %{{.*}}
     print(m)
     m.operation.verify()

torchvision-requirements.txt

@@ -4,4 +4,4 @@
 # release page, and we use this page as an additional source for the wheels.
 -f https://xilinx.github.io/torch-mlir/package-index/
 --pre
-torchvision==0.20.0.dev20241107
+torchvision==0.20.0.dev20241201