Summary:
Fixes https://github.com/pytorch/pytorch/issues/42860
The `__cuda_array_interface__` tensor specification is missing the appropriate datatypes for the newly merged complex64 and complex128 tensors. This PR addresses this issue by casting:
* `torch.complex64` to 'c8'
* `torch.complex128` to 'c16'
Pull Request resolved: https://github.com/pytorch/pytorch/pull/42918
Reviewed By: izdeby
Differential Revision: D23130219
Pulled By: anjali411
fbshipit-source-id: 5f8ee8446a71cad2f28811afdeae3a263a31ad11
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35615
Python 2 has reached end-of-life and is no longer supported by PyTorch.
Now we can clean up a lot of cruft that we put in place to support it.
These changes were all done manually, and I skipped anything that seemed
like it would take more than a few seconds, so I think it makes sense to
review it manually as well (though using side-by-side view and ignoring
whitespace change might be helpful).
Test Plan: CI
Differential Revision: D20842886
Pulled By: dreiss
fbshipit-source-id: 8cad4e87c45895e7ce3938a88e61157a79504aed
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/30445
Create distributed and rpc directories under caffe/test for better management
of unit tests.
Differential Revision: D18702786
fbshipit-source-id: e9daeed0cfb846ef68806f6decfcb57c0e0e3606
Summary:
When converting a contiguous CuPy ndarray to Tensor via `__cuda_array_interface__`, an error occurs due to incorrect handling of default strides. This PR fixes this problem. It makes `torch.tensor(cupy_ndarray)` works for contiguous inputs.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/24947
Differential Revision: D18838986
Pulled By: ezyang
fbshipit-source-id: 2d827578f54ea22836037fe9ea8735b99f2efb42
Summary:
The semantic of the _auto-convert GPU arrays that support the __cuda_array_interface__ protocol_ has changed a bit.
It used to throw an exception when using `touch.as_tensor(...,device=D)` where `D` is a CUDA device not used in `__cuda_array_interface__`. Now, this is supported and will result in an implicit copy.
I do not what have changes but `from_blob()` now supports that the input and the output device differ.
I have updated the tests to reflect this, which fixes https://github.com/pytorch/pytorch/issues/24968
Pull Request resolved: https://github.com/pytorch/pytorch/pull/25017
Differential Revision: D16986240
Pulled By: soumith
fbshipit-source-id: e6f7e2472365f924ca155ce006c8a9213f0743a7
Summary:
Fixed#21269 by removed the the expected `ValueError` when converting a tensor to a Numpy `int8` array in the Numba interoperability test.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21458
Differential Revision: D15696363
Pulled By: ezyang
fbshipit-source-id: f4ee9910173aab0b90a757e75c35925b026d1cc4
Summary:
This PR implements auto-conversion of GPU arrays that support the `__cuda_array_interface__` protocol (fixes#15601).
If an object exposes the `__cuda_array_interface__` attribute, `touch.as_tensor()` and `touch.tensor()` will use the exposed device memory.
#### Zero-copy
When using `touch.as_tensor(...,device=D)` where `D` is the same device as the one used in `__cuda_array_interface__`.
#### Implicit copy
When using `touch.as_tensor(...,device=D)` where `D` is the CPU or another non-CUDA device.
#### Explicit copy
When using `torch.tensor()`.
#### Exception
When using `touch.as_tensor(...,device=D)` where `D` is a CUDA device not used in `__cuda_array_interface__`.
#### Lifetime
`torch.as_tensor(obj)` tensor grabs a reference to `obj` so that the lifetime of `obj` exceeds the tensor
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20584
Differential Revision: D15435610
Pulled By: ezyang
fbshipit-source-id: c423776ba2f2c073b902e0a0ce272d54e9005286
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/12794
common.py is used in base_module for almost all tests in test/. The
name of this file is so common that can easily conflict with other dependencies
if they happen to have another common.py in the base module. Rename the file to
avoid conflict.
Reviewed By: orionr
Differential Revision: D10438204
fbshipit-source-id: 6a996c14980722330be0a9fd3a54c20af4b3d380
Summary:
_Implements pytorch/pytorch#11914, cc: ezyang_
Implements `__cuda_array_interface__` for non-sparse cuda tensors,
providing compatibility with numba (and other cuda projects...).
Adds `numba` installation to the `xenial-cuda9` jenkins test environments via direct installation in `.jenkins/pytorch/test.sh` and numba-oriented test suite in `test/test_numba_integration.py`.
See interface reference at:
https://numba.pydata.org/numba-doc/latest/cuda/cuda_array_interface.html
Pull Request resolved: https://github.com/pytorch/pytorch/pull/11984
Differential Revision: D10361430
Pulled By: ezyang
fbshipit-source-id: 6e7742a7ae4e8d5f534afd794ab6f54f67808b63
