add pinned memory support for int8tensor

[liangel-02]

as title

Test

in torchao
python test/quantization/quantize_/workflows/int8/test_int8_tensor.py -k test_pin_memory

in diffusers
python -m pytest tests/quantization/torchao/test_torchao.py -k test_torch_compile_with_group_offload_leaf -s

no longer seeing

NotImplementedError: AffineQuantizedTensor dispatch: attempting to run unimplemented operator/function: func=<OpOverload(op='aten.is_pinned', overload='default')>, types=(<class 'torchao.dtypes.affine_quantized_tensor.AffineQuantizedTensor'>,), arg_types=(<class 'torchao.dtypes.affine_quantized_tensor.AffineQuantizedTensor'>,), kwarg_types={}` for `use_stream=True

however, still seeing the known Dynamo error

torch._dynamo.exc.TorchRuntimeError: Dynamo failed to run FX node with fake tensors: call_function <built-in function linear>(*(FakeTensor(..., device='cuda:0', size=(s65, 256), dtype=torch.bfloat16), Int8Tensor(act_quant_kwargs=None, qdata=FakeTensor(..., size=(1536, 256), dtype=torch.int8), scale=FakeTensor(..., size=(1536, 1), dtype=torch.bfloat16), act_scale=None, block_size=[1, 256], shape=torch.Size([1536, 256]), device=cpu, dtype=torch.bfloat16), Parameter(FakeTensor(..., device='cuda:0', size=(1536,), dtype=torch.bfloat16, requires_grad=True))), **{}): got RuntimeError('Unhandled FakeTensor Device Propagation for aten.mm.default, found two different devices cuda:0, cpu')

from user code:
      File "/home/liangel/local/diffusers/src/diffusers/hooks/hooks.py", line 189, in torch_dynamo_resume_in_new_forward_at_188
      output = function_reference.forward(*args, **kwargs)
      File "/home/liangel/local/pytorch/torch/nn/modules/linear.py", line 134, in forward
          return F.linear(input, self.weight, self.bias)

../pytorch/torch/_subclasses/fake_tensor.py:987: TorchRuntimeError

[pytorch-bot]

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❌ 1 New Failure

As of commit 5bb5818 with merge base ff6d9e2 ():

NEW FAILURE - The following job has failed:

• Run Regression Tests / test-nightly (CUDA Nightly, linux.g5.12xlarge.nvidia.gpu, --pre torch --index-url https://downloa... / linux-job (gh)
  test/test_low_bit_optim.py::TestFSDP2::test_fsdp2

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[jerryzh168]

looks great, thanks!

cc @sayakpaul please take a look as well and let us know if the current test is enough to cover the functionality of pin_memory

[jerryzh168]

for the known Dynamo error, what's the plan to resolve this?

[sayakpaul]

This is perfect! Thanks!

I guess float already supports this?

[jerryzh168]

Float8Tensor doesn't support this yet, I think we should follow up with that as well @liangel-02