[E2E] Torchbench models load weight got failed

[mengfei25]

🐛 Describe the bug

xpu train functorch_maml_omniglot
Traceback (most recent call last):
File "/home/sdp/actions-runner/_work/torch-xpu-ops/pytorch/benchmarks/dynamo/common.py", line 4886, in run
) = runner.load_model(
File "/home/sdp/actions-runner/_work/torch-xpu-ops/pytorch/benchmarks/dynamo/torchbench.py", line 312, in load_model
benchmark = benchmark_cls(
File "/home/sdp/actions-runner/_work/torch-xpu-ops/benchmark/torchbenchmark/util/model.py", line 39, in call
obj = type.call(cls, *args, **kwargs)
File "/home/sdp/actions-runner/_work/torch-xpu-ops/benchmark/torchbenchmark/models/functorch_maml_omniglot/init.py", line 73, in init
self.meta_inputs = torch.load(f'{root}/maml_omniglot/batch.pt')
File "/home/sdp/miniforge3/envs/e2e_ci/lib/python3.10/site-packages/torch/serialization.py", line 1493, in load
raise pickle.UnpicklingError(_get_wo_message(str(e))) from None
_pickle.UnpicklingError: Weights only load failed. This file can still be loaded, to do so you have two options, �[1mdo those steps only if you trust the source of the checkpoint�[0m.
(1) In PyTorch 2.6, we changed the default value of the weights_only argument in torch.load from False to True. Re-running torch.load with weights_only set to False will likely succeed, but it can result in arbitrary code execution. Do it only if you got the file from a trusted source.
(2) Alternatively, to load with weights_only=True please check the recommended steps in the following error message.
WeightsUnpickler error: Unsupported global: GLOBAL numpy.core.multiarray._reconstruct was not an allowed global by default. Please use torch.serialization.add_safe_globals([_reconstruct]) or the torch.serialization.safe_globals([_reconstruct]) context manager to allowlist this global if you trust this class/function.

Check the documentation of torch.load to learn more about types accepted by default with weights_only https://pytorch.org/docs/stable/generated/torch.load.html.

Versions

env:
python: 3.10
XPU_OPS: 9ed0a1a
TRITON_COMMIT_ID: e98b6fcb8df5b44eb0d0addb6767c573d37ba024
TORCH_COMMIT_ID: 4f8b7c4272db521f7ffc4070ce1bdece513d1183
TORCHBENCH_COMMIT_ID: 03cde49eba0580ed17f9ae2250832fd8af4ed756
TORCHVISION_COMMIT_ID: d23a6e1664d20707c11781299611436e1f0c104f
TORCHAUDIO_COMMIT_ID: a6b0a140cc13216975e8922093459019537bb80a
TRANSFORMERS_VERSION: 243e186efbf7fb93328dd6b34927a4e8c8f24395
TIMM_COMMIT_ID: ac3470188b914c5d7a5058a7e28b9eb685a62427
DRIVER_VERSION: 1.23.10.49.231129.50
KERNEL_VERSION: 5.15.0-73-generic #80-Ubuntu SMP Mon May 15 15:18:26 UTC 2023
BUNDLE_VERSION: 2025.0.1.20241113
OS_PRETTY_NAME: Ubuntu 22.04.2 LTS
GCC_VERSION: 11

[mengfei25]

Same as #510

[mengfei25]

Use pytorch pinned torchbench as CUDA and should be fixed in #1226