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Fix deepcopy for tensor with MTIA device key. (#107427)

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Summary: Tensor with MTIA device type doesn't have storage and we need to treat it same as other tensors which don't have storage.

Test Plan: CI tests.

Differential Revision: D48456004

Pull Request resolved: https://github.com/pytorch/pytorch/pull/107427
Approved by: https://github.com/cx-yin, https://github.com/ezyang
This commit is contained in:
Jun Luo
2023-08-23 20:47:34 +00:00
committed by PyTorch MergeBot
parent 42b6ba3484
commit 221daeb1a7
1 changed files with 4 additions and 3 deletions
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7
torch/_tensor.py
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@ -100,7 +100,8 @@ class Tensor(torch._C._TensorBase):
# Update the test in test_serialization if you remove 'meta' from here
if (
self.is_sparse
or self.device.type in ["lazy", "xla", "mps", "ort", "meta", "ipu"]
or self.device.type
in ["lazy", "xla", "mtia", "mps", "ort", "meta", "ipu"]
or (
not torch._C._has_storage(self)
and self.device.type == torch._C._get_privateuse1_backend_name()
@ -248,7 +249,7 @@ class Tensor(torch._C._TensorBase):
# See Note [Don't serialize hooks]
torch.utils.hooks.warn_if_has_hooks(self)
backward_hooks: Dict[Any, Any] = OrderedDict()
# Note: Numpy array is chosen to be the rebuild component for XLA, ORT Tensors.
# Note: Numpy array is chosen to be the rebuild component for XLA, MTIA, ORT Tensors.
# We considered a few options:
# 1. CPU tensor can't be used here.
# Otherwise in torch.load CPU storage is reconstructed with randomly
@ -258,7 +259,7 @@ class Tensor(torch._C._TensorBase):
# 2. Python list is not a good fit due to performance reason.
# `tolist()` converts every single element in the tensor into python objects
# and serialize them one by one.
if self.device.type in ["xla", "ort"] or (
if self.device.type in ["xla", "mtia", "ort"] or (
not torch._C._has_storage(self)
and self.device.type == torch._C._get_privateuse1_backend_name()
):