build: manually update PyTorch version and fix CI failure (#3830)

This commit sets the PyTorch and TorchVision version to nightly release
2024-10-29.

This commit also fixes the CI failure after this commit
54d9e24
got merged. The issue was that the CI checks in the PR were run before
the previous roll pytorch update but the PR was actually merged after
the roll pytorch update. Hence, the failure was not caught before
merging the PR.

While exporting the fx_graph through fx_importer for `rrelu` and
`rrelu_with_noise` op for train mode, it decomposes the
`aten.rrelu_with_noise` op based on the PyTorch decomposition which is
the default behavior. However, the decomposition contains an input
mutation specifically here
https://github.com/pytorch/pytorch/blob/9bbe4a67ad137032add6a3b0b74bda66f5ef83d2/torch/_decomp/decompositions.py#L325,
resulting in the runtime failure. This issue would probably be fixed by
pytorch/pytorch#138503. Until then, the failing
tests are added to the xfail set.

Also, after the roll pytorch update following tests started passing for
fx_importer, and fx_importer_stablehlo config.

- "ElementwiseRreluTrainModule_basic"
- "ElementwiseRreluTrainStaticModule_basic"
- "ElementwiseRreluWithNoiseTrainModule_basic"
- "ElementwiseRreluWithNoiseTrainStaticModule_basic"

This commit also updates the dtype check for the `aten.linear` op since
the op now expects both the input tensors to have the same dtype.

Signed-Off By: Vivek Khandelwal <[email protected]>

projects/pt1/e2e_testing/xfail_sets.py

@@ -420,7 +420,6 @@
     "DeformConv2D_basic",
     "DivFloatModule_basic",
     "DivIntModule_basic",
-    "ElementwiseAddScalar_NumToTensorFloat_Module_basic",
     "ElementwiseDequantizePerChannelModule_basic",
     "ElementwiseDequantizePerTensorModule_basic",
     "ElementwiseQuantizePerTensorModule_basic",
@@ -446,8 +445,6 @@
     "NllLossModuleBackward1DSum_basic",
     "NllLossModuleBackward1DWeight_basic",
     "NllLossModuleBackward1D_basic",
-    "NumToTensorFloatModule_basic",
-    "NumToTensorIntModule_basic",
     "NumelModule_basic",
     "NumelZeroRankModule_basic",
     "PowIntFloatModule_basic",
@@ -464,7 +461,6 @@
     "QuantizedSingleLayer_basic",
     "ReduceMaxAlongDimUnsignedInt_basic",
     "ReduceMinAlongDimUnsignedInt_basic",
-    "RsubInt0d_NumToTensor_Module_basic",
     "ScalarImplicitFloatModule_basic",
     "SortIntListReverse_basic",
     "SortIntList_basic",
@@ -523,6 +519,11 @@
     "MeshgridIndexingXY_basic",
     "Meshgrid_basic",
     "OneHotModule_basic",
+    # RuntimeError: cannot mutate tensors with frozen storage
+    "ElementwiseRreluTrainModule_basic",
+    "ElementwiseRreluTrainStaticModule_basic",
+    "ElementwiseRreluWithNoiseTrainModule_basic",
+    "ElementwiseRreluWithNoiseTrainStaticModule_basic",
 }
 
 FX_IMPORTER_CRASHING_SET = LINALG_CRASHING_SET | {
@@ -690,7 +691,6 @@
     "DiagonalModule_with_offset",
     "DivFloatModule_basic",
     "DivIntModule_basic",
-    "ElementwiseAddScalar_NumToTensorFloat_Module_basic",
     "ElementwiseDequantizePerChannelModule_basic",
     "ElementwiseDequantizePerTensorModule_basic",
     "ElementwiseErfIntModule_basic",
@@ -792,8 +792,6 @@
     "NormScalarComplexModule_basic",
     "NormScalarModule_basic",
     "NormalFunctionalModule_basic",
-    "NumToTensorFloatModule_basic",
-    "NumToTensorIntModule_basic",
     "NumelModule_basic",
     "NumelZeroRankModule_basic",
     "PowIntFloatModule_basic",
@@ -829,7 +827,6 @@
     "ReplicationPad2dModule_left0",
     "ReplicationPad2dModule_right0",
     "ReplicationPad2dModule_top0",
-    "RsubInt0d_NumToTensor_Module_basic",
     "ScalarImplicitFloatModule_basic",
     # REMOVE WHEN ENABLE_GQA IS ADDED
     "ScatterReduceFloatMaxModule",
@@ -964,6 +961,11 @@
     "UpSampleNearest2dStaticFactor_basic",
     "UpSampleNearest2dStaticSize_basic",
     "UpSampleNearest2d_basic",
+    # RuntimeError: cannot mutate tensors with frozen storage
+    "ElementwiseRreluTrainModule_basic",
+    "ElementwiseRreluTrainStaticModule_basic",
+    "ElementwiseRreluWithNoiseTrainModule_basic",
+    "ElementwiseRreluWithNoiseTrainStaticModule_basic",
 }
 
 FX_IMPORTER_STABLEHLO_CRASHING_SET = {

projects/pt1/python/torch_mlir/jit_ir_importer/build_tools/abstract_interp_lib_gen.py

@@ -5371,7 +5371,7 @@ def aten〇atanh〡dtype(self_rank_dtype: Tuple[int, int]) -> int:
         return torch.float32
     return self_dtype
 
-@check_dtype_function(_check_two_tensor_op())
+@check_dtype_function(_check_tensors_with_the_same_dtype(num_of_tensors=2))
 def aten〇linear〡dtype(input_rank_dtype: Tuple[int, int], weight_rank_dtype: Tuple[int, int], bias_rank_dtype: Optional[Tuple[int, int]] = None) -> int:
     input_rank, input_dtype = input_rank_dtype
     weight_rank, weight_dtype = weight_rank_dtype

pytorch-hash.txt

@@ -1 +1 @@
-160d421a40e934ac8183e47f9cbc8618a4bd97dd
+c787213d413e85c66bdad0d8c9cde1c5ced34b1b

pytorch-requirements.txt

@@ -1,3 +1,3 @@
 -f https://download.pytorch.org/whl/nightly/cpu/torch/
 --pre
-torch==2.6.0.dev20241020
+torch==2.6.0.dev20241029

torchvision-requirements.txt

@@ -1,3 +1,3 @@
 -f https://download.pytorch.org/whl/nightly/cpu/torchvision/
 --pre
-torchvision==0.20.0.dev20241020
+torchvision==0.20.0.dev20241029