pytorch

366c59e2 - Allow PrivateUse1 backends to not have Storage (#86557) (#86803)

Allow PrivateUse1 backends to not have Storage (#86557) (#86803) * Allow PrivateUse1 backends to not have Storage (#86557) Allow PrivateUse1 backends to not have Storage To unblock the DirectML backend, this change would be needed for 1.13 as well. The DirectML backend creates tensors using the open registration pattern documented here: https://pytorch.org/tutorials/advanced/extend_dispatcher.html [registration example](https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fbdhirsh%2Fpytorch_open_registration_example&data=05%7C01%7CSheil.Kumar%40microsoft.com%7Cf107b0b4349e41f1a57808daa7ee8a2c%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638006940242882444%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=ivYLNmuC1WMitwu8n%2B1RAmeKkRM4ssb7EvhhGKJDFwk%3D&reserved=0) However, DirectML tensors are opaque, and do not have Storage. The DirectML Tensor Impl derives from OpaqueTensorImpl, which does not have a storage. Because of this various places in the code fail that expect storage to be present. We had made various changes in-tree to accommodate this: a. def __deepcopy__(self, memo): [https://github.com/pytorch/pytorch/blob/b5acba88959698d35cb548c78dd3fb151f85f28b/torch/_tensor.py#L119](https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fpytorch%2Fpytorch%2Fblob%2Fb5acba88959698d35cb548c78dd3fb151f85f28b%2Ftorch%2F_tensor.py%23L119&data=05%7C01%7CSheil.Kumar%40microsoft.com%7Cf107b0b4349e41f1a57808daa7ee8a2c%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638006940242882444%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=ajg23nMCzgRDwlinqSxS%2BRmOkAcDCr3LW%2BBEfNCn5hw%3D&reserved=0) or self.device.type in ["lazy", "xla", "mps", "ort", "meta", "hpu", 'dml'] b. def _reduce_ex_internal(self, proto): [https://github.com/pytorch/pytorch/blob/b5acba88959698d35cb548c78dd3fb151f85f28b/torch/_tensor.py#L275](https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fpytorch%2Fpytorch%2Fblob%2Fb5acba88959698d35cb548c78dd3fb151f85f28b%2Ftorch%2F_tensor.py%23L275&data=05%7C01%7CSheil.Kumar%40microsoft.com%7Cf107b0b4349e41f1a57808daa7ee8a2c%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638006940242882444%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=xDW6LwPSe2F396OJ6QSJY6mVzJVDeQiJgA0G347y2pw%3D&reserved=0) if self.device.type in ["xla", "ort", "hpu", "dml"]: c. TensorIteratorBase::build has an unsupported list for tensors without storage. [https://github.com/pytorch/pytorch/blob/b5acba88959698d35cb548c78dd3fb151f85f28b/aten/src/ATen/TensorIterator.cpp#L1497](https://nam06.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fpytorch%2Fpytorch%2Fblob%2Fb5acba88959698d35cb548c78dd3fb151f85f28b%2Faten%2Fsrc%2FATen%2FTensorIterator.cpp%23L1497&data=05%7C01%7CSheil.Kumar%40microsoft.com%7Cf107b0b4349e41f1a57808daa7ee8a2c%7C72f988bf86f141af91ab2d7cd011db47%7C1%7C0%7C638006940242882444%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=qAdgNgzKl0xrtOvsABpw1VGkSoGUpe7jwDPhHw3XjgU%3D&reserved=0) Using the PrivateUse1 backend, similar exemptions need to be made in order to relax requirements on Storage so that the DirectML backend tensors can work. Pull Request resolved: https://github.com/pytorch/pytorch/pull/86557 Approved by: https://github.com/bdhirsh, https://github.com/martinb35 * Fix incorrect tensor storage check (#86845) Fix incorrect tensor storage check This change contains an incorrect check for storage: https://github.com/pytorch/pytorch/pull/86557 **self.storage is not None** should have been: **not torch._C._has_storage(self)** These fixes were run through the DirectML test suite, and confirm the check is now working correctly. Pull Request resolved: https://github.com/pytorch/pytorch/pull/86845 Approved by: https://github.com/martinb35, https://github.com/bdhirsh