Fix FakeTensorProp on Module with Parameters or Buffers (#88700)
In `FakeTensorMode.__torch_dispatch__`, the output is now always computed by meta kernels in
```python
try:
with in_kernel_invocation_manager(self):
r = func(*args, **kwargs) # <----- "r" can be a real tensor.
except NotImplementedError as not_implemented_error:
# no meta kernel registered, fallback to kernel for the device
if not self.allow_fallback_kernels:
raise not_implemented_error
return run_fallback_kernel(self, func, args, kwargs, not_implemented_error)
return self.wrap_meta_outputs_with_default_device_logic(r, func, args, kwargs)
```
For example, I observed a CPU tensor is generated when executing `aten.addmm` when running `FakeTensorProp`. Therefore, I'd like to allow `FakeTensorMode` to wrap real tensor as `FakeTensor` during the computation. Does this PR look a good direction to fix this problem? If yes, I can go ahead and add some tests.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/88700
Approved by: https://github.com/eellison, https://github.com/ezyang
