pytorch - 💡(How to fix) Fix DISABLED test_opcheck_opinfo_NumpySplitCopyWithIntCustomOp_cpu_float32 (__main__.TestCustomOpTestingCPU) [2 comments, 1 participants]

Traceback (most recent call last): File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/optests/generate_tests.py", line 695, in opcheck tester(op, args, kwargs, rtol=rtol, atol=atol) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/optests/generate_tests.py", line 61, in safe_schema_check result = op(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_ops.py", line 871, in call return self._op(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_compile.py", line 54, in inner return disable_fn(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 1281, in _fn return fn(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_subclasses/schema_check_mode.py", line 184, in torch_dispatch out = func(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_ops.py", line 871, in call return self._op(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py", line 375, in backend_impl result = self._backend_fns[device_type](*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_compile.py", line 54, in inner return disable_fn(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 1281, in _fn return fn(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/_library/custom_ops.py", line 410, in wrapped_fn return fn(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/custom_op_db.py", line 353, in numpy_split_copy_with_int x_np = to_numpy(x) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/custom_op_db.py", line 29, in to_numpy return tensor.cpu().numpy() RuntimeError: Can't call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead.

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_device_type.py", line 1175, in test_wrapper return test(*args, **kwargs) File "/__w/pytorch/pytorch/test/test_custom_ops.py", line 444, in test_opcheck_opinfo torch.library.opcheck(op.op, args, kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/library.py", line 1749, in opcheck return optests.opcheck( File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/optests/generate_tests.py", line 699, in opcheck raise OpCheckError( torch.testing._internal.optests.generate_tests.OpCheckError: opcheck(op, ...): test_schema failed with Can't call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead. (scroll up for stack trace)

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3444, in wrapper method(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_device_type.py", line 439, in instantiated_test result = test(self, **param_kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 1821, in wrapper fn(*args, **kwargs) File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_device_type.py", line 1187, in test_wrapper raise e_tracked from e Exception: opcheck(op, ...): test_schema failed with Can't call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead. (scroll up for stack trace)

Caused by sample input at index 0: SampleInput(input=Tensor[size=(2, 9), device="cpu", dtype=torch.float32], args=((1,3,6),1), kwargs={}, broadcasts_input=False, name='')

To execute this test, run the following from the base repo dir: PYTORCH_OPINFO_SAMPLE_INPUT_INDEX=0 python test/test_custom_ops.py TestCustomOpTestingCPU.test_opcheck_opinfo_NumpySplitCopyWithIntCustomOp_cpu_float32

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0

TL;DR

The most likely fix is to modify the to_numpy function to use tensor.detach().numpy() instead of tensor.numpy() to avoid the error caused by calling numpy() on a Tensor that requires grad.

Guidance

• Identify the to_numpy function in torch/testing/_internal/custom_op_db.py and modify it to use tensor.detach().numpy() instead of tensor.numpy().
• Verify that the test test_opcheck_opinfo_NumpySplitCopyWithIntCustomOp_cpu_float32 in test_custom_ops.py passes after making the change.
• Check the PyTorch documentation for any other instances where tensor.numpy() is used on Tensors that require grad and update those cases as well.
• Run the test with the modified code using the command PYTORCH_OPINFO_SAMPLE_INPUT_INDEX=0 python test/test_custom_ops.py TestCustomOpTestingCPU.test_opcheck_opinfo_NumpySplitCopyWithIntCustomOp_cpu_float32 to ensure the fix works.

Example

# In torch/testing/_internal/custom_op_db.py
def to_numpy(x):
    return x.detach().numpy()  # Use detach() to avoid the error

Notes

This fix assumes that the error is caused by the to_numpy function being called on a Tensor that requires grad. If the issue persists after making this change, further investigation may be needed to identify the root cause.

Recommendation

Apply the workaround by modifying the to_numpy function to use tensor.detach().numpy() instead of tensor.numpy(), as this should fix the immediate issue and allow the test to pass.