Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45232
**Summary**
This commit updates the TorchScript language reference to include
documentation on recently-added TorchScript enums. It also removed
`torch.no_grad` from the list of known unsupported `torch` modules and
classes because it is now supported.
**Test Plan**
Continuous integration.
Test Plan: Imported from OSS
Reviewed By: ZolotukhinM
Differential Revision: D23971884
Pulled By: SplitInfinity
fbshipit-source-id: 5e2c164ed59bc0926b11201106952cff86e9356e
Summary:
Fix for https://github.com/pytorch/pytorch/issues/37986
Follows the stack in https://github.com/pytorch/pytorch/pull/33783 stack to make functions in `torch/functional.py` resolve to their python implementations. Because the return type of `torch.unique` depends on `return_inverse` and `return_counts` I had to refactor the implementation to use our boolean_dispatch mechanism.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/38156
Differential Revision: D21504449
Pulled By: eellison
fbshipit-source-id: 7efb1dff3b5c00655da10168403ac4817286ff59
Summary:
Adds support for generating Vandermonde matrices based off of the Numpy implementation found [here](https://github.com/numpy/numpy/blob/v1.17.0/numpy/lib/twodim_base.py#L475-L563).
Adds test to ensure generated matrix matches expected Numpy implementation. Note test are only limited to torch.long and torch.double due to differences in now PyTorch and Numpy deal with type promotion.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/36725
Differential Revision: D21075138
Pulled By: jessebrizzi
fbshipit-source-id: 6bb1559e8247945714469b0e2b07c6f4d5fd1fd0
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/33705
The fact that there were two overloads appears to be a historical
artifact that dates back to when goldsborough originally added these
bindings in the first place. If TensorOptions is made optional,
then you only need one overload, not two, as they are exactly redundant
with each other. When MemoryFormat was added, it was made a little
harder to do this, as the C++ syntax at::empty_like(t, memory_format) would
not work if you collapsed the overload; but now it works because TensorOptions
supports MemoryFormat.
The upshot is, I can get rid of all the overloads and just have one overload.
Amazingly, this change is backwards compatible, as the test attests. While
I was at it, I also deleted the overload name from the functions entirely.
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Test Plan: Imported from OSS
Differential Revision: D20073355
Pulled By: bhosmer
fbshipit-source-id: c6a8908213b32ccf6737ea864d135e2cce34f56b
Summary:
Add a section for unsupported ops, and modules. Automatically generate the properties and attributes that aren't bound, and for ops that have semantic mismatches set up tests so the docs stay up to date.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/31329
Differential Revision: D19164472
Pulled By: eellison
fbshipit-source-id: 46290bb8a64d9de928cfb1eda5ff4558c3799c88
