Yukio Siraichi 5224490ae9 Implement NumPy-like frombuffer tensor constructor. (#59077) ... Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/59077 Fixes #58549 `from_buffer` constructs a tensor object from an already allocated buffer through CPython's buffer protocol. Besides the standard `dtype`, `count`, and `offset` parameters, this function also accepts: - `device`: where the buffer lives - `requires_grad`: should autograd record operations on the new tensor A new test file _test_buffer_protocol.py_ was created. Currently, only CPU tests were implemented. That's because neither PyTorch nor Numba implements CPython's buffer protocol. Therefore, there's no way to create a CUDA buffer with the existing dependencies (could use PyCUDA for that, though). At the moment, if `device` differs from the device the buffer actually lives, two things may happen: - `RuntimeError`, if `device='cuda'` - Segmentation fault (not tested -- see above), if `device='cpu'` Test Plan: Imported from OSS Reviewed By: jbschlosser Differential Revision: D29870914 Pulled By: mruberry fbshipit-source-id: 9fa8611aeffedfe39c9af74558178157a11326bb		2021-07-23 13:17:48 -07:00
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__init__.py	remediation of S205607	2020-07-17 17:19:47 -07:00
gen_pyi.py	Implement NumPy-like frombuffer tensor constructor. (#59077)	2021-07-23 13:17:48 -07:00