""" Demonstrate what happens when PrivateUse1Hooks are NOT registered.

Registers everything EXCEPT hooks, then triggers the assert via backward(). """

import torch import torch._C

--- Setup: everything except hooks ---

torch.utils.rename_privateuse1_backend("new_device") torch.utils.generate_methods_for_privateuse1_backend()

class _DummyBackendModule: def is_available(self): return True def device_count(self): return 1 def current_device(self): return 0 def set_device(self, device): pass

torch._register_device_module("new_device", _DummyBackendModule())

class _DummyDeviceGuard(torch._C.acc.DeviceGuard): def type(self): return torch._C._autograd.DeviceType.PrivateUse1

torch._C._acc.register_python_privateuseone_device_guard(_DummyDeviceGuard())

--- Register minimal ops ---

def _make_tensor(size, dtype): return torch._C._acc.create_empty_tensor(list(size), dtype or torch.float32)

@torch.library.impl("aten::empty_strided", "PrivateUse1") def empty_strided(size, stride, *, dtype=None, layout=None, device=None, pin_memory=None): return _make_tensor(size, dtype)

@torch.library.impl("aten::empty.memory_format", "PrivateUse1") def empty_memory_format(size, *, dtype=None, layout=None, device=None, pin_memory=None, memory_format=None): return _make_tensor(size, dtype)

@torch.library.impl("aten::_copy_from", "PrivateUse1") def copy_from(src, dst): pass

@torch.library.impl("aten::mul.Tensor", "PrivateUse1") def mul_tensor(self, other): return _make_tensor(self.shape, self.dtype)

a = torch.randn(2, 3, requires_grad=True) a_new_device = a.to("new_device") b = a_new_device * a_new_device grad = torch.randn(2, 3).to("new_device")

RuntimeError: Please register PrivateUse1HooksInterface by RegisterPrivateUse1HooksInterface first.

b.backward(grad)

TL;DR

To fix the error, register the PrivateUse1HooksInterface using torch._C._acc.register_python_privateuseone_hook or its C++ equivalent.

Guidance

• The error occurs because the PrivateUse1HooksInterface is not registered, which is required for the backward pass.
• To verify the fix, run the code with the torch._C._acc.register_python_privateuseone_hook call added before the backward pass.
• The tutorial should be updated to include this registration step to avoid similar errors.
• The torch._C._acc.register_python_privateuseone_hook function should be called with the correct hook implementation to register the PrivateUse1HooksInterface.

Example

torch._C._acc.register_python_privateuseone_hook(my_hook_implementation)

Replace my_hook_implementation with the actual implementation of the PrivateUse1HooksInterface.

Notes

• The exact implementation of the PrivateUse1HooksInterface is not provided in the issue, so the example code snippet is incomplete.
• The fix assumes that the PrivateUse1HooksInterface implementation is available and can be registered using torch._C._acc.register_python_privateuseone_hook.

Recommendation

Apply workaround: Register the PrivateUse1HooksInterface using torch._C._acc.register_python_privateuseone_hook to fix the error. This is necessary to enable the backward pass for the custom device.