71aefd5595
[reland] Allow setting grad_dtype on leaf tensors ( #164751 )
...
ghstack-source-id: e44b3941530be83a630ec93f1478eec741ffca2e
Pull-Request-resolved: https://github.com/pytorch/pytorch/pull/162815
Fixes #ISSUE_NUMBER
Relanding due to internal weirdness. Separate PR to codev w/o ghstack.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/164751
Approved by: https://github.com/albanD
2025-10-08 20:23:13 +00:00
3ddf2018d0
Revert "Support setting grad_dtype on leaf tensors ( #162815 )"
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This reverts commit dca73982c53e9f99f96246b5d9ed9bab83c7423f.
Reverted https://github.com/pytorch/pytorch/pull/162815 on behalf of https://github.com/yangw-dev due to break internal test D83850533, see more details below ([comment](https://github.com/pytorch/pytorch/pull/162815#issuecomment-3367498501 ))
2025-10-03 23:14:28 +00:00
dca73982c5
Support setting grad_dtype on leaf tensors ( #162815 )
...
`grad_dtype` is a new attribute on Tensor to control gradient dtype:
- Access/setting is leaf-only.
- grad_dtype is respected when (1) when assigning to .grad, and (2) in the engine after the previous node produces incoming gradients for AccumulateGrad. (See table below for details)
- Not setting grad_dtype preserves the current behavior. Accessing it returns `t.dtype`
- `grad_dtype` cannot be set when there is already a `.grad` present and the dtypes conflict.
| `grad_dtype` setting | Setting `.grad` manually | Incoming gradient from autograd engine |
|-----------------------|--------------------------|-----------------------------------------|
| **Default (tensor’s dtype)** | `.grad` must match tensor’s dtype | Engine casts incoming grad to tensor’s dtype |
| **Set to specific dtype** | `.grad` must match that dtype | Engine casts incoming grad to the specified dtype |
| **Set to `None`** | `.grad` may be any dtype | Engine does not cast; accepts incoming grad dtype as-is |
Pull Request resolved: https://github.com/pytorch/pytorch/pull/162815
Approved by: https://github.com/albanD
2025-10-02 23:09:07 +00:00
9685fc36d4
Add missing optional for tensor ops ( #159028 )
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## Test Result
<img width="872" height="340" alt="image" src="https://github.com/user-attachments/assets/20c3f1a2-0160-4ea3-b9f3-14630b4ec06d " />
<img width="906" height="429" alt="image" src="https://github.com/user-attachments/assets/68f8d8da-0570-4ae8-8e45-573b2c64cae5 " />
<img width="906" height="429" alt="image" src="https://github.com/user-attachments/assets/42d133f6-94eb-4a38-8b4b-5586f52bff88 " />
<img width="878" height="285" alt="image" src="https://github.com/user-attachments/assets/d3ad8950-81fa-4c4c-a5b5-621b0d9df99b " />
<img width="889" height="430" alt="image" src="https://github.com/user-attachments/assets/9aabeaff-bb8f-4990-b253-1bb053e72aca " />
Pull Request resolved: https://github.com/pytorch/pytorch/pull/159028
Approved by: https://github.com/Skylion007
2025-07-25 04:36:55 +00:00
8c5b070d1f
Documentation Fix: torch.tensor.scatter_ docs ( #157929 )
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updated torch.tensor.scatter_ docs to reflect proper broadcasting behavior
Fixes #157419
Pull Request resolved: https://github.com/pytorch/pytorch/pull/157929
Approved by: https://github.com/albanD
2025-07-10 19:22:52 +00:00
4cc8b60d1b
[BE][1/16] fix typos in torch/ ( #156311 )
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Pull Request resolved: https://github.com/pytorch/pytorch/pull/156311
Approved by: https://github.com/albanD
2025-07-09 11:02:22 +00:00
c8d39a1045
[docs] Add docstring indicating UB for converting inf to int ( #154781 )
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Fixes #154724
Pull Request resolved: https://github.com/pytorch/pytorch/pull/154781
Approved by: https://github.com/malfet
2025-06-10 14:04:50 +00:00
8817e5ac80
Render Example: and not Example:: in docs ( #153978 )
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Everything here is a grep except the changes in tools/autograd/load_derivatives.py which I manually corrected.
The correct notation is:
```
Example::
>>> ...
```
It is common and wrong to have:
```
Example::
>>> ...
```
In the wrong example, we get these pesky double colons:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/153978
Approved by: https://github.com/soulitzer , https://github.com/malfet
2025-05-21 01:03:26 +00:00
27f7b65a69
[BE] Ensure generated stub files by gen_pyi are properly formatted ( #150730 )
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Pull Request resolved: https://github.com/pytorch/pytorch/pull/150730
Approved by: https://github.com/aorenste
2025-05-17 12:30:40 +00:00
e2f9759bd0
Fix broken URLs ( #152237 )
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Pull Request resolved: https://github.com/pytorch/pytorch/pull/152237
Approved by: https://github.com/huydhn , https://github.com/malfet
2025-04-27 09:56:42 +00:00
bf7d8ef10d
[Docs] Clarify behavior when integer dtype is used with requires_grad=True in tensor.to() ( #150913 )
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Fixes #150618
Related comment: https://github.com/pytorch/pytorch/issues/3226#issuecomment-489362234
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150913
Approved by: https://github.com/janeyx99 , https://github.com/soulitzer , https://github.com/cyyever
Co-authored-by: Jane (Yuan) Xu <31798555+janeyx99@users.noreply.github.com >
2025-04-10 02:52:58 +00:00
47b494ef69
Add type hints to _tensor_docs.add_docstr_all ( #150715 )
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There is some sort of bug in `pytype` where if this function doesn't have type hints, `pytype` will spend 10 minutes inferring the types. Not that this matters much for a project not using `pytype`, but it led me to realize that this function could easily be type hinted and is not, so here is a PR adding some type hints.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/150715
Approved by: https://github.com/Skylion007
2025-04-06 22:25:34 +00:00
1b047d5d7a
Add link to non_blocking/pinmem tutorial in Tensor.to docstrings ( #145651 )
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Pull Request resolved: https://github.com/pytorch/pytorch/pull/145651
Approved by: https://github.com/svekars
2025-02-18 20:38:01 +00:00
ed309b9156
Re-add stft option to align window for center = false ( #146379 )
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Skips advancing the fc window on https://github.com/pytorch/pytorch/pull/145437 , since I just found that there were non-trivial efforts to do so a while ago that eventually was reverted: https://github.com/pytorch/pytorch/pull/73434
Works around the issue by keeping the stft sans center overload
Pull Request resolved: https://github.com/pytorch/pytorch/pull/146379
Approved by: https://github.com/justinchuby , https://github.com/iseeyuan
2025-02-06 14:07:13 +00:00
c07dc64017
Update pin memory related APIs to not pass 'device' argument ( #131858 )
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Based on https://github.com/pytorch/pytorch/pull/126376 , this PR tries to update all PT callers (e.g., `Tensor.is_pinned()`, `Tensor.pin_memory()`) to not pass `device` argument.
As for `storage/untyped_storage.is_pinned()/pin_memory()`, we keep the `device` argument but passing `device` is discouraged. And if not given, the default `device` is still 'cuda' for BC.
Additionally, based on device-agnostic pin_memory, `pin_memory_device` argument of `torch.utils.data.DataLoader` is discouraged now. For BC, explictly passing this argument is still effective. If not given, the default `device` will be the current accelerator.
Fixes #124908
Relates https://github.com/pytorch/pytorch/pull/126376
Pull Request resolved: https://github.com/pytorch/pytorch/pull/131858
Approved by: https://github.com/albanD
Co-authored-by: albanD <desmaison.alban@gmail.com >
2025-01-15 17:23:35 +00:00
c2c50d5f00
Fixed doc where more than one device specified since only one device is used ( #17553 ) ( #144043 )
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Fixes #17553
Pull Request resolved: https://github.com/pytorch/pytorch/pull/144043
Approved by: https://github.com/soulitzer
2025-01-07 23:06:52 +00:00
e4a05dec0f
[BE][Ez]: Fix docs recommending inefficient tensor op order ( #144270 )
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`detach().clone()` is faster than `.clone().detatch()` since the gradients are not cloned. Let's update all the documentation and tests so that users do not use the inefficient op ordering.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/144270
Approved by: https://github.com/awgu , https://github.com/XuehaiPan
2025-01-07 17:31:32 +00:00
e9d2765ec8
Revert "Add deterministic path for CUDA cumsum ( #136224 )"
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This reverts commit d1bb8e828f280d1c66fff193c043d5bc36154577.
Reverted https://github.com/pytorch/pytorch/pull/136224 on behalf of https://github.com/atalman due to Break internal CI ([comment](https://github.com/pytorch/pytorch/pull/136224#issuecomment-2379214226 ))
2024-09-27 12:54:47 +00:00
d1bb8e828f
Add deterministic path for CUDA cumsum ( #136224 )
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Change `cumsum` to call its decomposition when `use_deterministic_algorithms(True)` and input is CUDA.
Fixes #89492
Pull Request resolved: https://github.com/pytorch/pytorch/pull/136224
Approved by: https://github.com/ezyang , https://github.com/justinchuby
2024-09-26 04:52:05 +00:00
e3b89ca124
Revert "Add deterministic path for CUDA cumsum ( #136224 )"
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This reverts commit b1a02bf70824a4802411ddd5be1d3610e7a2e269.
Reverted https://github.com/pytorch/pytorch/pull/136224 on behalf of https://github.com/ezyang due to Failing internall CI ([comment](https://github.com/pytorch/pytorch/pull/136224#issuecomment-2374201626 ))
2024-09-25 14:11:01 +00:00
b1a02bf708
Add deterministic path for CUDA cumsum ( #136224 )
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Change `cumsum` to call its decomposition when `use_deterministic_algorithms(True)` and input is CUDA.
Fixes #89492
Pull Request resolved: https://github.com/pytorch/pytorch/pull/136224
Approved by: https://github.com/ezyang , https://github.com/justinchuby
2024-09-24 21:34:43 +00:00
fd182b90a7
Revert "Add deterministic path for CUDA cumsum ( #136224 )"
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This reverts commit d45b0151e5d9a9358368b9fbd7fa454edd5d9709.
Reverted https://github.com/pytorch/pytorch/pull/136224 on behalf of https://github.com/atalman due to Failing internall CI ([comment](https://github.com/pytorch/pytorch/pull/136224#issuecomment-2369244135 ))
2024-09-23 19:57:13 +00:00
d45b0151e5
Add deterministic path for CUDA cumsum ( #136224 )
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Change `cumsum` to call its decomposition when `use_deterministic_algorithms(True)` and input is CUDA.
Fixes #89492
Pull Request resolved: https://github.com/pytorch/pytorch/pull/136224
Approved by: https://github.com/ezyang , https://github.com/justinchuby
2024-09-20 02:41:56 +00:00
4226ed1585
[BE] Format uncategorized Python files with ruff format ( #132576 )
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Remove patterns `**`, `test/**`, and `torch/**` in `tools/linter/adapters/pyfmt_linter.py` and run `lintrunner`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/132576
Approved by: https://github.com/ezyang , https://github.com/Skylion007
ghstack dependencies: #132574
2024-08-04 17:13:31 +00:00
00e19ae97a
[MTIA] Support module.mtia() ( #131499 )
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Summary: Following other device backends' implementation to support module.mtia() API.
Test Plan: OSS and Internal CIs.
Differential Revision: D60076584
Pull Request resolved: https://github.com/pytorch/pytorch/pull/131499
Approved by: https://github.com/mikaylagawarecki
2024-07-25 04:23:48 +00:00
5c78581fc9
Fix documentation for tensor.repeat. ( #131195 )
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Fixes #130930 .
Adjusts the documentation which used `sizes` instead of `repeats`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/131195
Approved by: https://github.com/mikaylagawarecki , https://github.com/soulitzer
2024-07-22 14:48:18 +00:00
afe15d2d2f
Flip default value for mypy disallow_untyped_defs [3/11] ( #127840 )
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See #127836 for details.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/127840
Approved by: https://github.com/oulgen
2024-06-08 18:28:01 +00:00
d6fb1da806
Fix doc example of masked_scatter ( #123664 )
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mask has to be a bool tensor
Pull Request resolved: https://github.com/pytorch/pytorch/pull/123664
Approved by: https://github.com/peterbell10 , https://github.com/albanD
2024-04-09 22:15:12 +00:00
3426c6f559
update the tensor.scatter_ doc ( #120169 )
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Fixes #119543
- doc fixed with the `reduce` being a kwarg (see below for details)
- doc added another interface `(int dim, Tensor index, Number value, *, str reduce)` where
the full signature in the pyi file after build is
```
def scatter_(self, dim: _int, index: Tensor, value: Union[Number, _complex], *, reduce: str) -> Tensor:
```
. This can be further verified in
02fb043522/aten/src/ATen/native/native_functions.yaml (L8014)70bc3b3be4/test/test_scatter_gather_ops.py (L86)mikaylagawarecki@gmail.com >
Pull Request resolved: https://github.com/pytorch/pytorch/pull/120169
Approved by: https://github.com/mikaylagawarecki
2024-02-23 02:51:55 +00:00
75818adcf7
Pyi doc inclusion + fix ( #117267 )
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Reland of https://github.com/pytorch/pytorch/pull/114705 with extra fix to smoothly handle when the modules we're trying to load are not available (and thus the pyi won't contain the docs in this case).
Tested locally that it works properly in fbcode.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/117267
Approved by: https://github.com/ezyang
2024-01-15 13:06:53 +00:00
767e1b6349
Revert "Bring docstring to .pyi file ( #114705 )"
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This reverts commit 0dd5deecedd136852c7ccc81630eaefbebe5be29.
Reverted https://github.com/pytorch/pytorch/pull/114705 on behalf of https://github.com/facebook-github-bot due to Diff reverted internally ([comment](https://github.com/pytorch/pytorch/pull/114705#issuecomment-1887165326 ))
2024-01-11 13:30:44 +00:00
0dd5deeced
Bring docstring to .pyi file ( #114705 )
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Fixes #37762
Since the original issue hasn't been making progress for more than 3 years, I am attempting to make this PR to at least make some progress forward.
This PR attempts to add docstring to the `.pyi` files. The docstrings are read from [`_torch_docs`](https://github.com/pytorch/pytorch/blob/main/torch/_torch_docs.py ) by mocking [`_add_docstr`](9f073ae304/torch/csrc/Module.cpp (L329)https://github.com/pytorch/pytorch/files/13494263/_VariableFunctions.pyi.txt )
<img width="787" alt="image" src="https://github.com/pytorch/pytorch/assets/6421097/73c2e884-f06b-4529-8301-0ca0b9de173c ">
And the docstring can be picked up by VSCode:
<img width="839" alt="image" src="https://github.com/pytorch/pytorch/assets/6421097/1999dc89-a591-4c7a-80ac-aa3456672af4 ">
<img width="908" alt="image" src="https://github.com/pytorch/pytorch/assets/6421097/ecf3fa92-9822-4a3d-9263-d224d87ac288 ">
Pull Request resolved: https://github.com/pytorch/pytorch/pull/114705
Approved by: https://github.com/albanD
2024-01-09 18:37:16 +00:00
6f4409073f
[doc] two diff meanings of rv generated by torch.tensor.geometric_ and torch.distributions.geometric.Geometric ( #113183 )
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The meaning of random variables generated by `torch.tensor.geometric_` and `torch.distributions.geometric.Geometric` are different, and they are defined by two different PMFs.
Inform the user, so the user can choose their desired one.
Background: https://github.com/pytorch/pytorch/pull/37984#issuecomment-630336511
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113183
Approved by: https://github.com/albanD
2023-11-15 03:49:04 +00:00
31e16847ea
[doc] torch.tensor.geometric_, torch.tensor.uniform_ fix PMF vs PDF ( #113109 )
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- Geometric distribution is discrete, fix to PMF (probability mass function)
- Continuous uniform distribution is continuous, fix to PDF (probability density function)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113109
Approved by: https://github.com/albanD
2023-11-15 00:30:19 +00:00
56c453233f
[doc] clarify the range of sampled rv for torch.tensor.exponential_ ( #113195 )
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Range of sampled random variable needs to be clarified for `torch.tensor.exponential_` whose supported interval is (0, inf) is different from [0, inf] of exponential distribution.
Background: https://github.com/pytorch/pytorch/pull/37984#discussion_r1059527457 , https://github.com/pytorch/pytorch/issues/48841#issuecomment-1530439039 , https://github.com/pytorch/pytorch/pull/91673#discussion_r1069955813
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113195
Approved by: https://github.com/albanD
2023-11-15 00:30:14 +00:00
f22486b0fc
[doc] scale parameter notation for torch.Tensor.cauchy_ is misleading ( #113178 )
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Scale parameter notation currently used for `torch.Tensor.cauchy_` is misleading.
Sigma (σ) is usually used to denote square root of variance. Variance is undefined in Cauchy distribution.
Replace sigma (σ) with gamma (γ).
Background: https://github.com/pytorch/pytorch/pull/37984#discussion_r1059551749
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113178
Approved by: https://github.com/mingxzhao , https://github.com/albanD
2023-11-14 18:55:42 +00:00
77e8e8fd2d
Rewrite docs so that it is OK to use record_stream before uses ( #113282 )
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The previous documentation did not appear to accurately describe
the actual semantics in CUDA caching allocator.
When you record stream, we only record a stream use:
```
void recordStream(Block* block, cuda::CUDAStream stream) {
std::lock_guard<std::recursive_mutex> lock(mutex);
if (stream.stream() == block->stream) {
// ignore uses on the allocation stream, since those don't require any
// special synchronization
return;
}
block->stream_uses.insert(stream);
}
```
It is only at deallocation time when we actually install an event on
stream uses that we will subsequently query to determine if the block
can be reused or not.
Signed-off-by: Edward Z. Yang <ezyang@meta.com >
Pull Request resolved: https://github.com/pytorch/pytorch/pull/113282
Approved by: https://github.com/Skylion007 , https://github.com/albanD
2023-11-08 21:24:50 +00:00
09df6b771b
Add a note about performant record_stream use. ( #112526 )
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Signed-off-by: Edward Z. Yang <ezyang@meta.com >
Pull Request resolved: https://github.com/pytorch/pytorch/pull/112526
Approved by: https://github.com/albanD
2023-11-02 15:50:22 +00:00
fd209543d5
Add torch.utils.deterministic.fill_uninitialized_memory flag ( #111377 )
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Part of #109802
Pull Request resolved: https://github.com/pytorch/pytorch/pull/111377
Approved by: https://github.com/albanD , https://github.com/aaronenyeshi
2023-11-01 16:10:09 +00:00
ace2713d1e
Revert "Add torch.utils.deterministic.fill_uninitialized_memory flag ( #111377 )"
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This reverts commit f1785373c08b9e8383b7eec3391d57053209b525.
Reverted https://github.com/pytorch/pytorch/pull/111377 on behalf of https://github.com/facebook-github-bot due to Diff reverted internally ([comment](https://github.com/pytorch/pytorch/pull/111377#issuecomment-1784179040 ))
2023-10-29 17:41:55 +00:00
f1785373c0
Add torch.utils.deterministic.fill_uninitialized_memory flag ( #111377 )
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Part of #109802
Pull Request resolved: https://github.com/pytorch/pytorch/pull/111377
Approved by: https://github.com/albanD
2023-10-26 02:39:06 +00:00
09c598745c
Rename torch._C._TensorBase to TensorBase ( #109940 )
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I have gone ahead and implemented the renaming of the type `torch._C._TensorBase` to a non-private class name `TensorBase`.
The changes also include leaving `torch._C._TensorBase` as an alias to the new type: 70458768fb/torch/csrc/autograd/python_variable.cpp (L2196-L2197)70458768fb/torch/_C/__init__.pyi.in (L1522)Fixes #109438
Pull Request resolved: https://github.com/pytorch/pytorch/pull/109940
Approved by: https://github.com/ezyang
2023-09-25 19:10:22 +00:00
4b2c6282e0
Modify signature for tensor.tile in doc ( #106295 )
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Fixes #71476
Pull Request resolved: https://github.com/pytorch/pytorch/pull/106295
Approved by: https://github.com/soulitzer
2023-08-01 19:51:52 +00:00
c0c208516b
[Doc] Add Tensor.Shape ( #104750 )
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Summary:
Add `Tensor.Shape` doc.
Fix : #104038
Ref:
- https://github.com/pytorch/pytorch/issues/5544
- https://github.com/pytorch/pytorch/issues/1980
Differential Revision: D47278630
CC: @svekars @carljparker
Pull Request resolved: https://github.com/pytorch/pytorch/pull/104750
Approved by: https://github.com/mikaylagawarecki
2023-07-26 16:30:15 +00:00
0ccdbbe233
Add deterministic path for Tensor.resize_ ( #104300 )
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New elements added to a tensor by `torch.Tensor.resize_` are set to NaN/MAX_INT when deterministic mode is turned on.
When `torch.Tensor.resize_` is called on a quantized tensor and deterministic mode is turned on, a nondeterministic error is raised.
Part of #82004
Pull Request resolved: https://github.com/pytorch/pytorch/pull/104300
Approved by: https://github.com/albanD
2023-07-07 00:22:13 +00:00
4e204ff87b
Added is_xla ( #103100 )
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This change creates `is_xla` which is congruent with `is_cuda` and `is_cpu`. Useful in situations like: https://github.com/pytorch/pytorch/pull/102858
```
>>> x = torch.tensor([1], device=xm.xla_device())
>>> x.is_xla
True
>>> x.is_cpu
False
>>> x = torch.tensor([1])
>>> x.is_cpu
True
>>> x.is_xla
False
```
Attn: @albanD
Pull Request resolved: https://github.com/pytorch/pytorch/pull/103100
Approved by: https://github.com/albanD
2023-06-22 23:31:04 +00:00
2aa35e6cc1
Fix Tensor.uniform_ documentation to mention generator argument ( #99510 )
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Fixes #98202 , mentioning support for generator arguments while providing an example of the function's use.
Would be happy to iterate on this if there are any issues.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/99510
Approved by: https://github.com/soulitzer
2023-04-19 19:23:12 +00:00
c377a8590b
Add nonzero_static() op to pytorch to unblock export ( #97417 )
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Summary: Add new experimental python op (`torch.nonzero_static`) for export. There is NO cuda impl included in this PR
Example:
Say input tensor is `x = torch.tensor([[1, 0], [3, 2]])`
call regular `nonzero()` on x will give you a tensor `tensor([[0, 0], [1, 0], [1, 1])`
call `nonzero_static(x, size=4)` on x will give you a tensor `tensor([[0, 0], [1, 0], [1, 1], [fill_value, fill_value])` (padded)
call `nonzero_static(x, size=2)` on x will give you a tensor `tensor([[0, 0], [1, 0])` (truncated)
Test Plan:
**Unit Tests**
```
buck test @mode/dev-nosan //caffe2/test:test_dynamo -- 'caffe2/test:test_dynamo - test_export.py::ExportTests::test_export_with_nonzero_static' -- 'caffe2/test:test_dynamo - test_misc.py::MiscTests::test_nonzero_static'
```
**PT2 Export with `nonzero_static()`**
Example of `GraphModule` in the exported graph
```
def forward(self, x):
arg0, = fx_pytree.tree_flatten_spec(([x], {}), self._in_spec)
nonzero_static_default = torch.ops.aten.nonzero_static.default(arg0, size = 4); arg0 = None
return pytree.tree_unflatten([nonzero_static_default], self._out_spec)
```
Differential Revision: D44324808
Pull Request resolved: https://github.com/pytorch/pytorch/pull/97417
Approved by: https://github.com/ezyang
2023-04-11 05:13:36 +00:00
49c130256d
Clarify Tensor.is_sparse doc ( #98408 )
...
That it returns true only for COO matrix
Pull Request resolved: https://github.com/pytorch/pytorch/pull/98408
Approved by: https://github.com/cpuhrsch
2023-04-05 16:42:19 +00:00
555ab310dc
Add itemsize and nbytes properties to Tensor ( #98322 )
...
Adds properties for itemsize and nbytes to Tensor matching the properties in NumPy.
Fixes https://github.com/pytorch/pytorch/issues/12728
Pull Request resolved: https://github.com/pytorch/pytorch/pull/98322
Approved by: https://github.com/ezyang
2023-04-05 12:11:55 +00:00
