/opt/conda/lib/python3.8/site-packages/torch/_functorch/deprecated.py:93: UserWarning: We've integrated functorch into PyTorch. As the final step of the integration, functorch.functionalize is deprecated as of PyTorch 2.0 and will be deleted in a future version of PyTorch >= 2.3. Please use torch.func.functionalize instead; see the PyTorch 2.0 release notes and/or the torch.func migration guide for more details https://pytorch.org/docs/master/func.migrating.html
  warn_deprecated('functionalize')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/opt/conda/lib/python3.8/site-packages/torch/_functorch/vmap.py", line 39, in fn
    return f(*args, **kwargs)
  File "/opt/conda/lib/python3.8/site-packages/torch/_functorch/eager_transforms.py", line 1582, in wrapped
    func_outputs = func(*func_args, **func_kwargs)
  File "<stdin>", line 5, in test
NotImplementedError: Could not run 'aten::_amp_foreach_non_finite_check_and_unscale_' with arguments from the 'Meta' backend. This could be because the operator doesn't exist for this backend, or was omitted during the selective/custom build process (if using custom build). If you are a Facebook employee using PyTorch on mobile, please visit https://fburl.com/ptmfixes for possible resolutions. 'aten::_amp_foreach_non_finite_check_and_unscale_' is only available for these backends: [XLA, BackendSelect, Python, FuncTorchDynamicLayerBackMode, Functionalize, Named, Conjugate, Negative, ZeroTensor, ADInplaceOrView, AutogradOther, AutogradCPU, AutogradCUDA, AutogradHIP, AutogradXLA, AutogradMPS, AutogradIPU, AutogradXPU, AutogradHPU, AutogradVE, AutogradLazy, AutogradMeta, AutogradMTIA, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, AutogradNestedTensor, Tracer, AutocastCPU, AutocastCUDA, FuncTorchBatched, FuncTorchVmapMode, Batched, VmapMode, FuncTorchGradWrapper, PythonTLSSnapshot, FuncTorchDynamicLayerFrontMode, PythonDispatcher].

Warning: Failed to download action 'https://api.github.com/repos/actions/upload-artifact/tarball/0b7f8abb1508181956e8e162db84b466c27e18ce'. Error: Response status code does not indicate success: 500 (Internal Server Error).
Warning: Back off 20.144 seconds before retry.
Error: Response status code does not indicate success: 500 (Internal Server Error).

>>> print(torch._C._dispatch_dump("aten::nan_to_num.out"))
name: aten::nan_to_num.out
schema: aten::nan_to_num.out(Tensor self, float? nan=None, float? posinf=None, float? neginf=None, *, Tensor(a!) out) -> Tensor(a!)
debug: registered at /workspace/pytorch/build/aten/src/ATen/RegisterSchema.cpp:6
alias analysis kind: FROM_SCHEMA
Functionalize: registered at /workspace/pytorch/build/aten/src/ATen/RegisterFunctionalization_3.cpp:23953 :: (Tensor _0, float? _1, float? _2, float? _3, Tensor _4) -> Tensor _0 [ boxed unboxed ]
...
Meta: registered at /dev/null:219 :: (none) [ boxed ]
SparseCPU: registered at /workspace/pytorch/build/aten/src/ATen/RegisterSparseCPU.cpp:1379 :: (Tensor _0, float? _1, float? _2, float? _3, Tensor _4) -> Tensor _0 [ boxed unboxed ]
Autograd[alias]: registered at /workspace/pytorch/torch/csrc/autograd/generated/VariableType_2.cpp:17909 :: (Tensor _0, float? _1, float? _2, float? _3, Tensor _4) -> Tensor _0 [ boxed unboxed ]

x = torch.tensor([float('nan'), float('inf'), -float('inf'), 3.14])
x.nan_to_num_(1.0, 2.0, 3.0)
x_xla = torch.tensor([float('nan'), float('inf'), -float('inf'), 3.14], device='xla:0')
x_xla.nan_to_num_(1.0, 2.0, 3.0)