Huy Do
edf1868e67
Fix test_doc_template regex ( #81755 )
...
### The problem
This original regex abuses .* in combination with `re.DOTALL` and leads to a catastrophic backtracking perf issue when there is no match. When it happens, test_doc_template will run "forever" and timeout. Here is an example timeout test https://github.com/pytorch/pytorch/runs/7413337595
Another minor issue with this regex is that it won't matches concatenated doc string like `"""FOO""" + """BAR"""`, which is used for some API `_torch_docs.py`
### The fix
* Remove most of the match all .* usage. I have tested to make sure that the test finishes even when there is no match, i.e. it fails successfully
* Update the regex to match all the following cases before and after linting (You can also try it out on https://pythex.org ):
BEFORE
```
add_docstr(torch.abs, r"""
abs(input, *, out=None) -> Tensor
Computes the absolute value of each element in :attr:`input`.
.. math::
\text{out}_{i} = |\text{input}_{i}|
""" + r"""
Args:
{input}
Keyword args:
{out}
Example::
>>> torch.abs(torch.tensor([-1, -2, 3]))
tensor([ 1, 2, 3])
""".format(**common_args))
add_docstr(torch.absolute,
r"""
absolute(input, *, out=None) -> Tensor
Alias for :func:`torch.abs`
""")
```
AFTER
```
add_docstr(
torch.abs,
r"""
abs(input, *, out=None) -> Tensor
Computes the absolute value of each element in :attr:`input`.
.. math::
\text{out}_{i} = |\text{input}_{i}|
"""
+ r"""
Args:
{input}
Keyword args:
{out}
Example::
>>> torch.abs(torch.tensor([-1, -2, 3]))
tensor([ 1, 2, 3])
""".format(
**common_args
),
)
add_docstr(
torch.absolute,
r"""
absolute(input, *, out=None) -> Tensor
Alias for :func:`torch.abs`
""",
)
```
This will unblock https://github.com/pytorch/pytorch/pull/81643
Pull Request resolved: https://github.com/pytorch/pytorch/pull/81755
Approved by: https://github.com/atalman
2022-07-21 16:28:29 +00:00
Animesh Jain
1d90d6ee60
Setup for running PyTorch tests with TorchDynamo and skips for known failing tests ( #80106 )
...
@ezyang I am going to keep adding more skips in this PR for now. And once we have the CI running, I will replace with the appropriate decorators.
cc @mlazos , we should add those tests in test_ops.py in this PR as well
cc @jansel
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80106
Approved by: https://github.com/ezyang , https://github.com/jansel
2022-07-07 18:57:33 +00:00
Kurt Mohler
4c279994fd
Fix Module.share_memory error ( #80843 )
...
Fixes #80733
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80843
Approved by: https://github.com/malfet
2022-07-05 15:17:36 +00:00
PyTorch MergeBot
f668b7ecb0
Add integer support to index_reduce ( #80464 )
...
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80464
Approved by: https://github.com/cpuhrsch
2022-06-30 12:54:51 +00:00
PyTorch MergeBot
d7847ed23e
Add integer support to scatter_reduce ( #80324 )
...
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80324
Approved by: https://github.com/cpuhrsch
2022-06-29 21:10:26 +00:00
Alexander Grund
71d9592a72
Only sync CUDA if the operation is run on GPU ( #80328 )
...
This fixes test failures when PyTorch is build without CUDA
Fixes https://github.com/pytorch/pytorch/issues/58563
I used the same is_cuda check that is used in test_nn.py
CC @ailzhang after #58564
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80328
Approved by: https://github.com/mruberry
2022-06-27 14:49:39 +00:00
Alexander Grund
3b8589ac44
Copy Tensor for tests to avoid in-place transform modifying the original tensor ( #80331 )
...
Fixes #48591
CC @mruberry after #60256
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80331
Approved by: https://github.com/mruberry
2022-06-27 14:47:52 +00:00
lezcano
f54e7b4ad6
More forward AD formulas
...
This PR:
- Corrects the forward AD formula of `torch.sgn`.
- The reason why we can't use `auto_element_wise` for this operations is rather subtle. I left a comment.
- This, in turn, fixes a problem we had in forward-over-backward for `linalg.svd` and other spectral decompositions (and `norm`, `linalg.norm`, `linalg.matrix_norm`) that were using `torch.abs` (whose derivative is given by `torch.sgn`.
- Implement the formula for a number of missing operations `nansum`, `amax`, `amin`...
- Simplified a few formulas, most notably the forward AD for `div` and the derivative of `norm`, `linalg.norm` and `vector_norm` for `ord=+-inf`.
- Correct the formula for `mean`, `std_mean`, `var_mean` when `dim` is provided and equal to `()` (or `None`)
- A few minor improvements to `sum_backward`, `unsqueeze_multiple` and formulas depending on them
- Fix the derivatives of `std_mean` and `std_var` (complex support,
ASAN, forward AD...)
Fixes: https://github.com/pytorch/pytorch/issues/67539
Pull Request resolved: https://github.com/pytorch/pytorch/pull/80082
Approved by: https://github.com/zou3519
2022-06-23 01:31:08 +00:00
Alex Hedges
cb2b7b1e57
Fix code that triggers BytesWarning ( #79868 )
...
Fixes #74812 .
I have fixed the multiple instances in the repository that trigger
`BytesWarning`, and I have enabled the `-bb` option when tests are run
to prevent regressions.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/79868
Approved by: https://github.com/janeyx99
2022-06-21 01:12:21 +00:00
PyTorch MergeBot
e10cbe3880
Revert "Fix BytesWarning in torch.load() ( #74813 )"
...
This reverts commit 6c2e8119ddhttps://github.com/pytorch/pytorch/pull/74813 on behalf of https://github.com/janeyx99 due to Broke slow tests in cuda 10.2 https://github.com/pytorch/pytorch/runs/6944238177?check_suite_focus=true
2022-06-18 03:53:54 +00:00
Alex Hedges
6c2e8119dd
Fix BytesWarning in torch.load() ( #74813 )
...
Fixes #74812 .
I have enabled the `-bb` option when tests are run to prevent regressions. I don't think it will make CI run more slowly, but I'm not entirely sure.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74813
Approved by: https://github.com/kit1980
2022-06-17 22:56:43 +00:00
drisspg
bdcee8f995
update is_same_size to work with nested tensor dispatch
...
Pull Request resolved: https://github.com/pytorch/pytorch/pull/79297
Approved by: https://github.com/soulitzer
2022-06-11 00:07:27 +00:00
Brian Hirsh
7b3a0ff87a
Port index.Tensor to structured kernels.
...
Tracking issue: #55070
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69607
Approved by: https://github.com/bdhirsh
2022-06-10 17:27:47 +00:00
Peter Bell
7843a5e882
Move Tensor.grad back into C++
...
`Tensor.grad` was moved to python in #30531 to add a warning. However,
that warning has since been lowered into C++ so this wrapper is no
longer necessary.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76675
Approved by: https://github.com/albanD
2022-06-10 13:44:45 +00:00
PyTorch MergeBot
4b82ef7928
Revert "Port index.Tensor to structured kernels."
...
This reverts commit cfd84125bdhttps://github.com/pytorch/pytorch/pull/69607 on behalf of https://github.com/zengk95 due to This is breaking mac trunk tests cfd84125bd
2022-06-08 20:16:10 +00:00
Brian Hirsh
cfd84125bd
Port index.Tensor to structured kernels.
...
Tracking issue: #55070
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69607
Approved by: https://github.com/bdhirsh
2022-06-08 18:17:52 +00:00
Kshiteej K
497ae27050
[chalf] warn once on creating a chalf tensor ( #78245 )
...
`chalf` is experimental as the op coverage is low.
Following script raises 6 warnings if `set_warn_always(True)` else raises only 1 warning.
```python
import torch
torch.set_warn_always(True)
device='cpu'
t = torch.randn(3, dtype=torch.chalf, device=device)
y = torch.rand(3, dtype=torch.chalf, device=device)
# Allocates new tensor for result
t + y
device='cuda'
t = torch.randn(3, dtype=torch.chalf, device=device)
y = torch.rand(3, dtype=torch.chalf, device=device)
# Allocates new tensor for result
t + y
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/78245
Approved by: https://github.com/anjali411
2022-06-01 18:38:31 +00:00
yuguo68
efdb4192bc
set data permits requires_grad=True on integer tensor
...
Pull Request resolved: https://github.com/pytorch/pytorch/pull/78436
Approved by: https://github.com/albanD , https://github.com/soulitzer
2022-06-01 15:56:32 +00:00
PyTorch MergeBot
fca1f495c2
Revert "Port index.Tensor to structured kernels."
...
This reverts commit 9fe6f1baf5https://github.com/pytorch/pytorch/pull/69607 on behalf of https://github.com/suo due to this broke master, see: 9fe6f1baf5
2022-06-01 00:12:15 +00:00
Brian Hirsh
9fe6f1baf5
Port index.Tensor to structured kernels.
...
Tracking issue: #55070
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69607
Approved by: https://github.com/bdhirsh
2022-05-31 22:15:20 +00:00
Kurt Mohler
e9afb43676
Add meta device support to _UntypedStorage and _TypedStorage ( #78008 )
...
Fixes #77885
Pull Request resolved: https://github.com/pytorch/pytorch/pull/78008
Approved by: https://github.com/ezyang
2022-05-28 15:33:45 +00:00
Yu Guo
f69c990ecc
fix index_select when source tensor is empty
...
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77881
Approved by: https://github.com/ezyang
2022-05-26 03:10:47 +00:00
Kurt Mohler
cecb2ad95e
Restore old names for private funcs in legacy storages ( #77861 )
...
Followup from #75459
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77861
Approved by: https://github.com/ezyang
2022-05-20 02:03:34 +00:00
Eric Sauser
2d4291fb81
[torch] Fixed a few test for Windows & Linux GPUs ( #77531 )
...
Summary:
While running those tests on
- my local windows GPU machine
- a dev server
- an on-demand GPU
I noticed a few test failures and here's some tentative fixes
Test Plan:
Ran tests on:
- my local windows GPU machine
- a linux dev server w/o GPU
- an linux on-demand GPU server
Note that when using CUDA11, the tests crashes (segfaults) on calls to torch.nn.ConvTranspose3d. Fails on master, but works with CUDA10.
Differential Revision: D36377288
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77531
Approved by: https://github.com/ezyang
2022-05-19 14:04:13 +00:00
Kurt Mohler
aea6e2c396
Merge torch.cuda._UntypedStorage into torch._UntypedStorage ( #75459 )
...
Fixes #74933
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75459
Approved by: https://github.com/ezyang
2022-05-19 13:54:39 +00:00
Mikayla Gawarecki
841c65f499
Unprivate _index_reduce and add documentation
...
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76997
Approved by: https://github.com/cpuhrsch
2022-05-13 19:48:38 +00:00
Kulin Seth
e011a8e18b
Enable PyTorch operations on MPS Backend. ( #77343 )
...
Add PyTorch operations to MPS backend.
- https://github.com/pytorch/pytorch/issues/77394
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77343
Approved by: https://github.com/albanD
2022-05-13 18:28:53 +00:00
Mikayla Gawarecki
1141b45e7a
Index reduction CUDA support
...
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76296
Approved by: https://github.com/cpuhrsch , https://github.com/ngimel
2022-05-13 14:47:52 +00:00
Christian Puhrsch
ce9a477fdf
Support torch.Tensor.to for CSR
...
Fixes #76379
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76400
Approved by: https://github.com/pearu , https://github.com/davidberard98
2022-05-05 21:59:50 +00:00
Natalia Gimelshein
ce76244200
fix where type promotion
...
Fixes #73298
I don't know whether `where` kernel actually supports type promotion, nor am I in the mood to find out, so it's manual type promotion.
Edit: nah, i can't tell TI to "promote to common dtype" because of bool condition, so manual type promotion is our only option.
I'll see what tests start failing and fix.
Uses some parts from #62084
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76691
Approved by: https://github.com/mruberry
2022-05-03 04:40:04 +00:00
kshitij12345
e36d25fbae
[complex32] support printing the tensor
...
Reference: #74537
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76614
Approved by: https://github.com/anjali411
2022-05-01 12:46:09 +00:00
Mikayla Gawarecki
676a4a3969
Prototype _index_reduce (CPU-only)
...
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75981
Approved by: https://github.com/cpuhrsch
2022-04-27 23:01:00 +00:00
kshitij12345
aa51704ce5
[complex32] add chalf alias for complex32 and chalf method
...
Reference: https://github.com/pytorch/pytorch/issues/74537
Adds chalf alias for complex32 and also adds method `chalf` similar to `cfloat, cdouble`
TODO:
* [x] Add docs
* [x] Add override
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75320
Approved by: https://github.com/anjali411
2022-04-20 23:44:47 +00:00
Edward Z. Yang
ee955b8bb9
Cannibalize noarch CI job into crossref CI job
...
crossref is a new strategy for performing tests when you want
to run a normal PyTorch API call, separately run some variation of
the API call (e.g., same thing but all the arguments are meta tensors)
and then cross-reference the results to see that they are consistent.
Any logic you add to CrossRefMode will get run on *every* PyTorch API
call that is called in the course of PyTorch's test suite. This can
be a good choice for correctness testing if OpInfo testing is not
exhaustive enough.
For now, the crossref test doesn't do anything except verify that
we can validly push a mode onto the torch function mode stack for all
functions.
Signed-off-by: Edward Z. Yang <ezyangfb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75988
Approved by: https://github.com/seemethere
2022-04-20 11:56:25 +00:00
Edward Z. Yang
30943d1610
Remove noarchTest decorator
...
These tests are cheap so it doesn't matter if we run them on all
configs. This is in preparation for removing the noarch build
configuration entirely.
Signed-off-by: Edward Z. Yang <ezyangfb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75985
Approved by: https://github.com/seemethere , https://github.com/cbalioglu
2022-04-19 00:48:49 +00:00
Beilei Zheng
332086c08d
Add BFloat16 support for multinomial and poisson on CPU
...
Add BFloat16 support for multinomial and poisson on CPU
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63215
Approved by: https://github.com/frank-wei , https://github.com/bigfootjon
2022-04-14 15:42:18 +00:00
Jagadish Krishnamoorthy
26ba7a9297
ROCm: Enable test_masked_scatter_large_tensor
...
#68487 fixes the issue #60190 for ROCm >= 5.0 release.
Signed-off-by: Jagadish Krishnamoorthy <jagdish.krishna@gmail.com>
Fixes #60190
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75455
Approved by: https://github.com/ezyang
2022-04-08 15:59:40 +00:00
Nikita Karetnikov
936a65056e
Use the same checks in all grid_sampler functions
...
Fixes #73187 .
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75164
Approved by: https://github.com/albanD
2022-04-04 15:21:44 +00:00
Alban Desmaison
0ce02ea52d
Revert D35284563: Use the same checks in all grid_sampler functions
...
Test Plan: revert-hammer
Differential Revision:
D35284563 (835cc66e5d835cc66e5d
2022-04-01 16:45:46 +00:00
kshitij12345
65b65af236
[complex32] cat, fill_(partial), item
...
Reference : #74537
`cat_backwards` (on CUDA) requires support for `fill`, have added support for `fill`. (Also `fill` requires `item` support)
Now `fill` backward requires `sum` (will add it in later PR).
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75010
Approved by: https://github.com/anjali411
2022-04-01 15:19:05 +00:00
Nikita Karetnikov
835cc66e5d
Use the same checks in all grid_sampler functions ( #74635 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74635
Fixes #73187 .
Test Plan: Imported from OSS
Reviewed By: bdhirsh
Differential Revision: D35284563
Pulled By: albanD
fbshipit-source-id: 1477c506b8755d864ca902ee140bee7bdb0069b0
(cherry picked from commit dcbd5242baaae11f9e323d99a9596e5b88e86bd7)
2022-04-01 14:26:16 +00:00
Mikayla Gawarecki
2bfa018462
[BC-breaking] Use ScatterGatherKernel for scatter_reduce (CPU-only) ( #74226 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74226
Update signature of `scatter_reduce_` to match `scatter_/scatter_add_`
`Tensor.scatter_reduce_(int64 dim, Tensor index, Tensor src, str reduce)`
- Add new reduction options in ScatterGatherKernel.cpp and update `scatter_reduce` to call into the cpu kernel for `scatter.reduce`
- `scatter_reduce` now has the same shape constraints as `scatter_` and `scatter_add_`
- Migrate `test/test_torch.py:test_scatter_reduce` to `test/test_scatter_gather_ops.py`
Test Plan: Imported from OSS
Reviewed By: ngimel
Differential Revision: D35222842
Pulled By: mikaylagawarecki
fbshipit-source-id: 84930add2ad30baf872c495251373313cb7428bd
(cherry picked from commit 1b45139482e22eb0dc8b6aec2a7b25a4b58e31df)
2022-04-01 05:57:45 +00:00
Nikita Shulga
bfac65dfe5
[testing] Update dispatch macros ( #74977 )
...
This PR is reland of #74289
Co-authored-by: Khushi Agrawal <khushiagrawal411@gmail.com>
2022-03-30 14:13:21 -07:00
PyTorch MergeBot
2e4152b118
Revert "[testing] Update dispatch macros"
...
This reverts commit eed19a0f38https://github.com/pytorch/pytorch/pull/74289 on behalf of https://github.com/malfet
2022-03-30 19:52:37 +00:00
Khushi Agrawal
eed19a0f38
[testing] Update dispatch macros
...
Hi,
This PR is the follow-up PR of #71561 . (the previous PR had a couple of merge conflicts and was reverted, this PR resolves that).
Please take a look. Thanks!
cc: @pmeier @mruberry @kshitij12345
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74289
Approved by: https://github.com/pmeier , https://github.com/mruberry
2022-03-30 16:10:16 +00:00
Edward Z. Yang
51e7a3406c
Fix formatting of scalar tensors (don't call item)
...
Signed-off-by: Edward Z. Yang <ezyangfb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74376
Approved by: https://github.com/bdhirsh
2022-03-25 02:22:25 +00:00
Jane Xu
3f9115dc7a
Decorate test_pdist_large for requiring large memory ( #74574 )
...
Summary:
Fixes https://github.com/pytorch/pytorch/issues/74154
Pull Request resolved: https://github.com/pytorch/pytorch/pull/74574
Reviewed By: george-qi
Differential Revision: D35100229
Pulled By: janeyx99
fbshipit-source-id: d7df377318e45c7f5447c034aa025b1422fcc06e
(cherry picked from commit 335a76d9f2a721b30e1b9e1c869bfbe431f01a2a)
2022-03-24 17:25:37 +00:00
kshitij12345
f7ee308dfb
[complex-half] support casting (by updating copy_)
...
Reference https://github.com/pytorch/pytorch/issues/71680
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73847
Approved by: https://github.com/anjali411
2022-03-23 21:42:59 +00:00
Kurt Mohler
79ddc72b85
Virtualize <type>Storage classes ( #66970 )
...
Summary:
Fixes https://github.com/pytorch/pytorch/issues/66228
cc ezyang bhosmer smessmer ljk53 bdhirsh
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66970
Reviewed By: bdhirsh
Differential Revision: D33245612
Pulled By: ezyang
fbshipit-source-id: 4c61c2cb029e2b94b0e68927c377d3e1c358dd7c
(cherry picked from commit d29fcdfb4bc2cc17b1795d4349e4b56fa0d1cf12)
2022-03-22 23:44:48 +00:00
Saketh Are
46a88036af
Refactor error input tests in test_torch.py to OpInfos ( #73981 )
...
Summary:
This PR ports several tests in `test/test_torch.py` over to OpInfo ErrorInputs.
Some tests commented "convert to ErrorInputs" still remain in `test_torch.py`. They fall under two categories:
- Memory overlap tests which specifically test the in-place version of an operator (e.g. [this test](424a054d53/test/test_torch.py (L3788)424a054d53/test/test_torch.py (L4948)https://github.com/pytorch/pytorch/pull/73981
Reviewed By: qihqi
Differential Revision: D35016669
Pulled By: saketh-are
fbshipit-source-id: bc0016d2b2bfb566a9dfef81ecf44e0adb9e4b14
(cherry picked from commit 99bcbdb05f2c10a717a269b0010aa3a3e24fe5c0)
2022-03-21 22:31:37 +00:00
Nikita Shulga
ef066f0832
Revert D34856571: [pytorch][PR] Replace get_all_ type macros with the ATen dispatch macros.
...
Test Plan: revert-hammer
Differential Revision:
D34856571 (3ded7b1da33ded7b1da3
2022-03-15 22:07:11 +00:00
Khushi Agrawal
3ded7b1da3
Replace get_all_ type macros with the ATen dispatch macros. ( #71561 )
...
Summary:
Hi, Team!
The PR is motivated from https://github.com/pytorch/pytorch/pull/71153#discussion_r782446738 . It aims to replace `get_all` type macros with the ATen dispatch macros.
The files it iterates over are: (Thanks, Lezcano, for the idea!!)
<details>
<summary>
`test/test_autograd.py`</summary>
<p>
```python
43:from torch.testing._internal.common_dtype import get_all_dtypes
8506: floating_dt = [dt for dt in get_all_dtypes() if dt.is_floating_point]
```
</p>
</details>
<details>
<summary>
`test/test_binary_ufuncs.py`</summary>
<p>
```python
26: all_types_and_complex_and, integral_types_and, get_all_dtypes, get_all_int_dtypes, get_all_math_dtypes,
27: get_all_complex_dtypes, get_all_fp_dtypes,
935: dtypes(*get_all_dtypes(include_bool=False, include_complex=False))
1035: dtypes(*get_all_dtypes(
1488: dtypes(*(get_all_dtypes(include_bool=False, include_bfloat16=False)))
1879: dtypes(*product(get_all_dtypes(include_complex=False), get_all_dtypes(include_complex=False)))
1887: dtypes(*(get_all_int_dtypes() + [torch.bool]))
1913: dtypes(*(get_all_fp_dtypes()))
1941: dtypes(*(get_all_fp_dtypes()))
1977: dtypes(*product(get_all_complex_dtypes(), get_all_dtypes()))
2019: dtypes(*product(get_all_fp_dtypes(), get_all_fp_dtypes()))
2048: dtypes(*get_all_dtypes())
2110: dtypes(*product(get_all_dtypes(include_complex=False),
2111: get_all_dtypes(include_complex=False)))
2128: types = [torch.bool, torch.bfloat16] + get_all_int_dtypes()
2173: if dtypes[1] in get_all_fp_dtypes():
2178: dtypes(*product(get_all_fp_dtypes(),
2179: get_all_fp_dtypes()))
2260: dtypesIfCUDA(*set(get_all_math_dtypes('cuda')) - {torch.complex64, torch.complex128})
2261: dtypes(*set(get_all_math_dtypes('cpu')) - {torch.complex64, torch.complex128})
2273: dtypesIfCUDA(*set(get_all_math_dtypes('cuda')) - {torch.complex64, torch.complex128})
2274: dtypes(*set(get_all_math_dtypes('cpu')) - {torch.complex64, torch.complex128})
2307: dtypes(*get_all_math_dtypes('cpu'))
2319: dtypes(*get_all_fp_dtypes(include_bfloat16=False))
2331: dtypes(*get_all_int_dtypes())
2356: dtypes(*get_all_dtypes(include_bfloat16=False, include_bool=False, include_complex=False))
2393: if dtype in get_all_int_dtypes():
2614: dtypes(*get_all_dtypes())
2624: dtypes(*tuple(itertools.combinations_with_replacement(get_all_dtypes(), 2)))
2806: dtypes(*list(product(get_all_dtypes(include_complex=False),
2807: get_all_dtypes(include_complex=False))))
2866: dtypes(*list(product(get_all_complex_dtypes(),
2867: get_all_complex_dtypes())))
2902: dtypes(*product(get_all_dtypes(), get_all_dtypes()))
2906: dtypes(*product(get_all_dtypes(), get_all_dtypes()))
2910: dtypes(*product(get_all_dtypes(), get_all_dtypes()))
3019: dtypes = [torch.float, torch.double] + get_all_complex_dtypes()
3221: dtypes(*get_all_dtypes(include_complex=False))
3407: dtypes(*list(product(get_all_dtypes(include_bool=False),
3408: get_all_dtypes(include_bool=False))))
3504: dtypes(*product(get_all_dtypes(include_complex=False, include_bfloat16=False),
3505: get_all_dtypes(include_complex=False, include_bfloat16=False)))
3516: if x.dtype in get_all_int_dtypes() + [torch.bool]:
3643: dtypes(*product(get_all_dtypes(include_complex=False,
3645: get_all_dtypes(include_complex=False,
```
</p>
</details>
<details>
<summary>
`test/test_complex.py`</summary>
<p>
```python
6:from torch.testing._internal.common_dtype import get_all_complex_dtypes
11: dtypes(*get_all_complex_dtypes())
```
</p>
</details>
<details>
<summary>
`test/test_foreach.py`</summary>
<p>
```python
18: get_all_dtypes, get_all_int_dtypes, get_all_complex_dtypes, get_all_fp_dtypes,
142: if dtype in get_all_int_dtypes():
179: disable_fastpath = op.ref == torch.div and dtype in get_all_int_dtypes() + [torch.bool]
201: disable_fastpath = op.ref == torch.div and dtype in get_all_int_dtypes() + [torch.bool]
205: disable_fastpath |= dtype in get_all_int_dtypes() + [torch.bool]
211: disable_fastpath |= dtype not in get_all_complex_dtypes()
241: bool_int_div = op.ref == torch.div and dtype in get_all_int_dtypes() + [torch.bool]
246: disable_fastpath |= dtype in get_all_int_dtypes() + [torch.bool]
248: disable_fastpath |= dtype not in get_all_complex_dtypes()
250: disable_fastpath |= True and dtype not in get_all_complex_dtypes()
307: disable_fastpath = dtype in get_all_int_dtypes() + [torch.bool]
365: if opinfo.name == "_foreach_abs" and dtype in get_all_complex_dtypes():
376: ops(foreach_unary_op_db, dtypes=get_all_dtypes())
393: dtypes=get_all_dtypes(include_half=True, include_bfloat16=True, include_complex=False))
401: ops(foreach_minmax_op_db, dtypes=get_all_fp_dtypes(include_bfloat16=True, include_half=True))
426: if ord in (1, 2) and dtype in torch.testing.get_all_fp_dtypes():
439: dtypes(*get_all_dtypes())
449: ops(foreach_binary_op_db, dtypes=get_all_dtypes())
481: ops(foreach_binary_op_db, dtypes=get_all_dtypes())
536: if dtype in get_all_int_dtypes() + [torch.bool] and foreach_op == torch._foreach_div:
545: ops(foreach_binary_op_db, dtypes=get_all_dtypes())
637: ops(foreach_pointwise_op_db, allowed_dtypes=get_all_fp_dtypes(include_half=False, include_bfloat16=False))
```
</p>
</details>
<details>
<summary>
`test/test_linalg.py`</summary>
<p>
```python
29: all_types, floating_types, floating_and_complex_types, get_all_dtypes, get_all_int_dtypes, get_all_complex_dtypes,
30: get_all_fp_dtypes,
111: dtypes(*(get_all_dtypes()))
794: float_and_complex_dtypes = get_all_fp_dtypes() + get_all_complex_dtypes()
807: dtypes(*(get_all_int_dtypes()))
828: dtypes(*(get_all_fp_dtypes() + get_all_complex_dtypes()))
841: if dtype in get_all_complex_dtypes():
844: dtypes(*itertools.product(get_all_dtypes(),
845: get_all_dtypes()))
855: for dtypes0, dtypes1, dtypes2 in product(get_all_dtypes(), repeat=3):
5607: *get_all_fp_dtypes(include_half=not CUDA9, include_bfloat16=(CUDA11OrLater and SM53OrLater)))
5608: dtypes(*(set(get_all_dtypes()) - {torch.half, torch.bool}))
5644: dtypes(*(get_all_complex_dtypes() + get_all_fp_dtypes()))
6255: dtypesIfCUDA(*get_all_complex_dtypes(),
6256: *get_all_fp_dtypes(include_bfloat16=(TEST_WITH_ROCM or (CUDA11OrLater and SM53OrLater)),
6292: dtypesIfCUDA(*get_all_fp_dtypes(include_bfloat16=(TEST_WITH_ROCM or (CUDA11OrLater and SM53OrLater))))
6323: dtypesIfCUDA(*get_all_complex_dtypes(),
6324: *get_all_fp_dtypes(include_bfloat16=(TEST_WITH_ROCM or (CUDA11OrLater and SM53OrLater))))
6325: dtypes(*get_all_complex_dtypes(), *get_all_fp_dtypes())
6358: dtypesIfCUDA(*([torch.float, torch.double] + get_all_complex_dtypes()))
6556: dtypes(*get_all_fp_dtypes(), *get_all_complex_dtypes())
6668: dtypes(*get_all_fp_dtypes(), *get_all_complex_dtypes())
6741: dtypes(*get_all_fp_dtypes(), *get_all_complex_dtypes())
```
</p>
</details>
<details>
<summary>
`test/test_nn.py`</summary>
<p>
```python
37:from torch.testing._internal.common_dtype import integral_types, get_all_fp_dtypes, get_all_math_dtypes
50: onlyNativeDeviceTypes, deviceCountAtLeast, largeTensorTest, expectedFailureMeta, skipMeta, get_all_device_types, \
8862: for device in get_all_device_types():
9629: for dt1 in get_all_math_dtypes(device):
9630: for dt2 in get_all_math_dtypes(device):
9631: for dt3 in get_all_math_dtypes(device):
9648: for input_dtype in get_all_math_dtypes(device):
9664: for input_dtype in get_all_math_dtypes(device):
13015: dtypes(*get_all_fp_dtypes(include_bfloat16=AMPERE_OR_ROCM))
13034: dtypes(*get_all_fp_dtypes(include_bfloat16=AMPERE_OR_ROCM))
13159: dtypes(*get_all_fp_dtypes(include_bfloat16=AMPERE_OR_ROCM))
17400: dtypesIfCUDA(*get_all_fp_dtypes(include_bfloat16=AMPERE_OR_ROCM))
17768: dtypesIfCUDA(*get_all_fp_dtypes())
17773: dtypesIfCUDA(*get_all_fp_dtypes())
17778: dtypesIfCUDA(*get_all_fp_dtypes())
17783: dtypesIfCUDA(*get_all_fp_dtypes())
17788: dtypesIfCUDA(*get_all_fp_dtypes())
17793: dtypesIfCUDA(*get_all_fp_dtypes())
17798: dtypesIfCUDA(*get_all_fp_dtypes())
17963: dtypesIfCUDA(*get_all_fp_dtypes())
17977: dtypesIfCUDA(*get_all_fp_dtypes())
18684: def test_cross_entropy_loss_prob_target_all_reductions(self, device):
```
</p>
</details>
<details>
<summary>
`test/test_numpy_interop.py`</summary>
<p>
```python
12:from torch.testing._internal.common_dtype import get_all_dtypes
399: dtypes(*get_all_dtypes())
```
</p>
</details>
<details>
<summary>
`test/test_ops.py`</summary>
<p>
```python
12:from torch.testing._internal.common_dtype import floating_and_complex_types_and, get_all_dtypes
86: for dtype in get_all_dtypes():
```
</p>
</details>
<details>
<summary>
`test/test_reductions.py`</summary>
<p>
```python
16: get_all_dtypes, get_all_math_dtypes, get_all_int_dtypes, get_all_complex_dtypes, get_all_fp_dtypes,
360: allowed_dtypes=get_all_dtypes(include_bfloat16=False))
366: allowed_dtypes=get_all_dtypes(include_bfloat16=False))
394: allowed_dtypes=get_all_dtypes(include_bfloat16=False))
750: for dtype in [dtype for dtype in get_all_math_dtypes('cpu') if dtype != torch.float16]:
1404: dtypes(*get_all_dtypes(include_bool=False, include_complex=False))
1457: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes(include_bfloat16=False) +
1458: get_all_complex_dtypes()))
1465: return dtype in get_all_int_dtypes()
1494: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes(include_bfloat16=False)))
1501: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes(include_bfloat16=False)))
1507: dtypes(*(get_all_complex_dtypes()))
1514: dtypes = list(get_all_int_dtypes() + get_all_fp_dtypes(include_bfloat16=False))
1523: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes(include_bfloat16=False)))
1531: if dtype in get_all_fp_dtypes():
1608: dtypes(*(get_all_dtypes(include_half=True, include_bfloat16=False,
1837: dtypes(*get_all_dtypes(include_bool=False, include_complex=False))
1855: dtypes(*(set(get_all_dtypes(include_bool=False, include_complex=False)) - {torch.uint8}))
3219: for dtype in get_all_dtypes(include_half=True, include_bfloat16=False,
```
</p>
</details>
<details>
<summary>
`test/test_serialization.py`</summary>
<p>
```python
26:from torch.testing._internal.common_dtype import get_all_dtypes
586: for device, dtype in product(devices, get_all_dtypes()):
589: for other_dtype in get_all_dtypes():
```
</p>
</details>
<details>
<summary>
`test/test_shape_ops.py`</summary>
<p>
```python
18:from torch.testing._internal.common_dtype import get_all_dtypes
230: dtypes(*get_all_dtypes(include_complex=False, include_bool=False, include_half=False,
232: dtypesIfCUDA(*get_all_dtypes(include_complex=False, include_bool=False, include_bfloat16=False))
344: dtypes(*get_all_dtypes())
443: dtypes(*get_all_dtypes())
461: dtypes(*get_all_dtypes())
570: dtypes(*get_all_dtypes(include_complex=False))
```
</p>
</details>
<details>
<summary>
`test/test_sort_and_select.py`</summary>
<p>
```python
12: all_types, all_types_and, floating_types_and, get_all_dtypes, get_all_int_dtypes, get_all_fp_dtypes,
136: dtypes(*set(get_all_dtypes()) - {torch.bool, torch.complex64, torch.complex128})
231: dtypes(*set(get_all_dtypes()) - {torch.bool, torch.complex64, torch.complex128})
296: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes()))
647: dtypesIfCUDA(*get_all_fp_dtypes())
678: dtypesIfCUDA(*(get_all_dtypes(include_complex=False,
682: dtypes(*(get_all_dtypes(include_complex=False, include_bool=False, include_half=False, include_bfloat16=False)))
739: dtypesIfCPU(*set(get_all_dtypes()) - {torch.complex64, torch.complex128})
740: dtypes(*set(get_all_dtypes()) - {torch.bfloat16, torch.complex64, torch.complex128})
799: dtypesIfCPU(*set(get_all_dtypes()) - {torch.complex64, torch.complex128})
800: dtypes(*set(get_all_dtypes()) - {torch.bfloat16, torch.complex64, torch.complex128})
```
</p>
</details>
<details>
<summary>
`test/test_sparse.py`</summary>
<p>
```python
20:from torch.testing import get_all_complex_dtypes, get_all_fp_dtypes
29: floating_and_complex_types, floating_and_complex_types_and, get_all_dtypes, get_all_int_dtypes,
1963: return dtype in get_all_int_dtypes()
1994: dtypes(*get_all_dtypes(include_bool=False, include_half=False,
2103: return dtype in get_all_int_dtypes()
2138: dtypes(*get_all_dtypes(include_bool=False, include_half=False,
2626: all_sparse_dtypes = get_all_dtypes(include_complex=True)
2633: all_sparse_dtypes = get_all_dtypes(include_complex=True)
3230: dtypes(*get_all_complex_dtypes(),
3231: *get_all_fp_dtypes(include_half=False, include_bfloat16=False))
3234: *get_all_fp_dtypes(
```
</p>
</details>
<details>
<summary>
`test/test_sparse_csr.py`</summary>
<p>
```python
7:from torch.testing import get_all_complex_dtypes, get_all_fp_dtypes, floating_and_complex_types, make_tensor
17:from torch.testing._internal.common_dtype import floating_types, get_all_dtypes
120: dtypes(*get_all_dtypes())
133: dtypes(*get_all_dtypes())
150: dtypes(*get_all_dtypes())
180: dtypes(*get_all_dtypes())
201: dtypes(*get_all_dtypes())
210: dtypes(*get_all_dtypes())
225: dtypes(*get_all_dtypes())
244: dtypes(*get_all_dtypes())
263: dtypes(*get_all_dtypes())
285: dtypes(*get_all_dtypes())
411: dtypes(*get_all_dtypes())
482: dtypes(*get_all_dtypes())
502: dtypes(*get_all_dtypes())
562: dtypes(*get_all_dtypes())
588: dtypesIfCUDA(*get_all_complex_dtypes(),
589: *get_all_fp_dtypes(include_half=SM53OrLater, include_bfloat16=SM80OrLater))
745: dtypesIfCUDA(*get_all_complex_dtypes(),
746: *get_all_fp_dtypes(include_half=SM53OrLater and TEST_CUSPARSE_GENERIC,
765: dtypesIfCUDA(*get_all_complex_dtypes(),
766: *get_all_fp_dtypes(include_half=SM53OrLater and TEST_CUSPARSE_GENERIC,
801: *torch.testing.get_all_fp_dtypes(include_bfloat16=SM80OrLater,
841: *torch.testing.get_all_fp_dtypes(include_bfloat16=SM80OrLater,
1182: dtypes(*get_all_dtypes())
1276: dtypes(*get_all_dtypes(include_bool=False, include_half=False, include_bfloat16=False))
1286: dtypes(*get_all_dtypes())
```
</p>
</details>
<details>
<summary>
`test/test_tensor_creation_ops.py`</summary>
<p>
```python
21: onlyCUDA, skipCPUIf, dtypesIfCUDA, skipMeta, get_all_device_types)
23: get_all_dtypes, get_all_math_dtypes, get_all_int_dtypes, get_all_fp_dtypes, get_all_complex_dtypes
150: for dt in get_all_dtypes():
160: for dt in get_all_dtypes():
314: dtypes = [dtype for dtype in get_all_dtypes() if dtype != torch.bfloat16]
1012: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes(include_bfloat16=False) +
1013: get_all_complex_dtypes()))
1032: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes(include_bfloat16=False) +
1033: get_all_complex_dtypes()))
1050: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes(include_bfloat16=False) +
1051: get_all_complex_dtypes()))
1745: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes()))
1779: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes()))
1868: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes()))
1926: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes()))
1954: do_test_empty_full(self, get_all_math_dtypes('cpu'), torch.strided, torch_device)
1956: do_test_empty_full(self, get_all_math_dtypes('cpu'), torch.strided, None)
1957: do_test_empty_full(self, get_all_math_dtypes('cpu'), torch.strided, torch_device)
2538: for device in get_all_device_types():
2645: for dtype in get_all_dtypes():
2678: dtypes(*(get_all_fp_dtypes(include_half=False, include_bfloat16=False) +
2679: get_all_complex_dtypes()))
2716: dtypes(*get_all_fp_dtypes(include_half=False, include_bfloat16=False))
2827: for dt in get_all_dtypes():
2913: dtypes(*get_all_dtypes(include_bool=False, include_half=False))
2914: dtypesIfCUDA(*get_all_dtypes(include_bool=False, include_half=True))
3028: dtypes(*(get_all_fp_dtypes() + get_all_complex_dtypes()))
3033: dtypes(*(get_all_fp_dtypes() + get_all_complex_dtypes()))
3074: dtypes(*get_all_dtypes(include_bool=False, include_half=False, include_complex=False))
3075: dtypesIfCUDA(*((get_all_int_dtypes() + [torch.float32, torch.float16, torch.bfloat16])
3077: else get_all_dtypes(include_bool=False, include_half=True, include_complex=False)))
3873: dtypes(*get_all_dtypes())
3884: dtypes(*get_all_dtypes(include_bool=False))
3916: for other in get_all_dtypes():
3922: dtypes(*get_all_dtypes())
3932: dtypes(*get_all_dtypes(include_bool=False))
3955: dtypes(*get_all_dtypes(include_bool=False))
3961: dtypes(*get_all_dtypes(include_bool=False))
3965: dtypes(*get_all_dtypes())
```
</p>
</details>
<details>
<summary>
`test/test_testing.py`</summary>
<p>
```python
25:from torch.testing._internal.common_dtype import get_all_dtypes
31: dtypes(*(get_all_dtypes(include_half=True, include_bfloat16=False,
```
</p>
</details>
<details>
<summary>
`test/test_torch.py`</summary>
<p>
```python
51: expectedAlertNondeterministic, get_all_device_types, skipXLA)
57: get_all_fp_dtypes, get_all_int_dtypes, get_all_math_dtypes, get_all_dtypes, get_all_complex_dtypes
296: for d in get_all_device_types():
323: for device in get_all_device_types():
324: for dt1 in get_all_dtypes():
325: for dt2 in get_all_dtypes():
343: all_dtypes = get_all_dtypes()
350: all_dtypes = get_all_dtypes()
781: for dtype in get_all_dtypes():
986: for device in get_all_device_types():
1017: for device in get_all_device_types():
1018: for dtype in get_all_math_dtypes(device):
2792: for device in get_all_device_types():
3186: dtypes(*get_all_dtypes())
3195: for error_dtype in get_all_dtypes():
3203: dtypes(*get_all_dtypes())
3212: for error_dtype in get_all_dtypes():
4539: dtypes(*get_all_fp_dtypes())
4545: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes()))
4577: dtypes(*get_all_fp_dtypes(include_half=False, include_bfloat16=False))
4578: dtypesIfCPU(*(get_all_fp_dtypes(include_half=False, include_bfloat16=True)))
4579: dtypesIfCUDA(*(get_all_fp_dtypes(include_bfloat16=False)))
4599: dtypes(*(get_all_fp_dtypes(include_half=False, include_bfloat16=False)))
4600: dtypesIfCPU(*(get_all_dtypes(include_half=False, include_bfloat16=False, include_complex=False)))
4601: dtypesIfCUDA(*(get_all_dtypes(include_bfloat16=False, include_complex=False)))
4613: for p_dtype in get_all_fp_dtypes(include_half=device.startswith('cuda'), include_bfloat16=False):
4628: dtypes(*(get_all_fp_dtypes(include_half=False, include_bfloat16=False)))
4629: dtypesIfCUDA(*(get_all_fp_dtypes(include_bfloat16=False)))
4640: dtypes(*get_all_fp_dtypes())
4723: dtypes(*get_all_fp_dtypes())
4735: dtypes(*get_all_fp_dtypes(include_bfloat16=False))
4736: dtypesIfCUDA(*get_all_fp_dtypes())
4747: dtypes(*get_all_fp_dtypes())
4761: dtypes(*get_all_fp_dtypes())
4771: dtypes(*get_all_fp_dtypes())
4792: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes()))
5302: dtypes(*get_all_dtypes(include_bfloat16=False))
5322: dtypes(*get_all_dtypes(include_half=False, include_bfloat16=False))
5323: dtypesIfCPU(*get_all_dtypes(include_bfloat16=False))
5324: dtypesIfCUDA(*get_all_dtypes(include_bfloat16=False))
5591: for dt in get_all_dtypes():
5611: for dt in get_all_dtypes():
5678: for dt in get_all_dtypes():
5696: dtypesIfCUDA(*set(get_all_math_dtypes('cuda')))
5697: dtypes(*set(get_all_math_dtypes('cpu')))
5746: dtypes(*get_all_dtypes())
5780: dtypes(*get_all_dtypes())
5885: dtypes(*get_all_dtypes())
5902: dtypes(*get_all_dtypes())
5945: dtypes(*get_all_dtypes())
5979: dtypes(*get_all_dtypes(include_bool=False))
6049: dtypes(*get_all_dtypes(include_bool=False))
6092: dtypes(*(get_all_fp_dtypes(include_bfloat16=False, include_half=False) +
6093: get_all_complex_dtypes()))
6094: dtypesIfCPU(*get_all_dtypes())
6095: dtypesIfCUDA(*get_all_dtypes())
6122: dtypes(*(get_all_fp_dtypes(include_bfloat16=False, include_half=False) +
6123: get_all_complex_dtypes()))
6124: dtypesIfCPU(*get_all_dtypes())
6125: dtypesIfCUDA(*get_all_dtypes())
6163: dtypes(*(get_all_fp_dtypes(include_bfloat16=False, include_half=False) +
6164: get_all_complex_dtypes()))
6165: dtypesIfCPU(*get_all_dtypes())
6166: dtypesIfCUDA(*get_all_dtypes())
6190: dtypes(*(get_all_complex_dtypes() +
6191: get_all_int_dtypes()))
6238: dtypes(*get_all_dtypes())
6323: dtypes(*get_all_dtypes())
6389: dtypes(*product(get_all_dtypes(), (torch.uint8, torch.bool)))
6699: dtypesIfCUDA(*set(get_all_math_dtypes('cuda')))
6700: dtypes(*set(get_all_math_dtypes('cpu')))
7452: dtypes(*get_all_dtypes(include_bool=False))
7461: dtypes(*get_all_dtypes(include_bool=False))
7477: dtypes(*get_all_dtypes(include_bool=False))
7496: dtypes(*get_all_dtypes(include_bool=False))
7538: dtypes(*get_all_dtypes(include_bool=False))
8162: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes() +
8163: get_all_complex_dtypes()))
8175: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes() +
8176: get_all_complex_dtypes()))
```
</p>
</details>
<details>
<summary>
`test/test_type_promotion.py`</summary>
<p>
```python
14: get_all_dtypes, get_all_math_dtypes, get_all_int_dtypes, get_all_fp_dtypes
187: for dtype in get_all_dtypes():
262: dtypes1 = get_all_math_dtypes('cuda')
263: dtypes2 = get_all_math_dtypes(device)
339: dtypes(*itertools.product(get_all_dtypes(), get_all_dtypes()))
468: for dt1 in get_all_math_dtypes(device):
469: for dt2 in get_all_math_dtypes(device):
519: for dt1 in get_all_math_dtypes(device):
520: for dt2 in get_all_math_dtypes(device):
528: for dt in get_all_math_dtypes(device):
561: for dtype in get_all_dtypes():
766: dtypes=get_all_math_dtypes(device))
771: dtypes=get_all_math_dtypes(device))
782: dtypes=get_all_math_dtypes(device))
879: dtypes = get_all_dtypes(include_bfloat16=False)
898: dtypes = get_all_dtypes(include_bfloat16=False, include_bool=False)
965: dtypesIfCUDA(*itertools.product(get_all_dtypes(include_bfloat16=False, include_complex=False),
966: get_all_dtypes(include_bfloat16=False, include_complex=False)))
967: dtypes(*itertools.product(get_all_dtypes(include_half=False, include_bfloat16=False,
969: get_all_dtypes(include_half=False, include_bfloat16=False,
976: return dtype in get_all_int_dtypes() + [torch.bool]
979: return dtype in get_all_fp_dtypes(include_half=True, include_bfloat16=False)
```
</p>
</details>
<details>
<summary>
`test/test_unary_ufuncs.py`</summary>
<p>
```python
24: floating_types_and, all_types_and_complex_and, floating_and_complex_types_and, get_all_dtypes, get_all_math_dtypes,
25: get_all_int_dtypes, get_all_fp_dtypes, get_all_complex_dtypes
517: dtypes(*(get_all_int_dtypes() + [torch.bool] +
518: get_all_fp_dtypes(include_bfloat16=False)))
596: dtypes(*get_all_fp_dtypes(include_half=True, include_bfloat16=False))
611: invalid_input_dtypes = get_all_int_dtypes() + \
612: get_all_complex_dtypes() + \
619: for dtype in get_all_fp_dtypes(include_half=True, include_bfloat16=False):
1048: dtypes(*get_all_math_dtypes('cpu'))
1182: dtypesIfCUDA(*get_all_fp_dtypes())
1190: dtypesIfCUDA(*get_all_fp_dtypes())
1205: dtypesIfCUDA(*get_all_fp_dtypes())
1215: dtypesIfCUDA(*get_all_fp_dtypes())
1307: dtypes(*(get_all_dtypes(include_bool=False)))
1349: dtypes(*(get_all_fp_dtypes(include_half=False) +
1350: get_all_complex_dtypes()))
1351: dtypesIfCUDA(*(get_all_fp_dtypes(include_half=True) +
1352: get_all_complex_dtypes()))
```
</p>
</details>
<details>
<summary>
`test/test_view_ops.py`</summary>
<p>
```python
19: get_all_dtypes, get_all_int_dtypes, get_all_fp_dtypes, get_all_complex_dtypes
124: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes()))
131: dtypes(*get_all_dtypes(include_bfloat16=False))
213: for view_dtype in [*get_all_fp_dtypes(), *get_all_complex_dtypes()]:
220: dtypes(*get_all_dtypes())
224: for view_dtype in get_all_dtypes():
305: dtypes(*get_all_complex_dtypes(include_complex32=True))
343: dtypes(*get_all_dtypes())
354: dtypes(*get_all_dtypes())
364: dtypes(*get_all_dtypes())
374: dtypes(*get_all_dtypes())
384: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes()))
395: dtypes(*get_all_complex_dtypes())
426: dtypes(*get_all_complex_dtypes())
451: dtypes(*product(get_all_complex_dtypes(), get_all_dtypes()))
1263: dtypes(*(torch.testing.get_all_dtypes()))
1279: dtypes(*(torch.testing.get_all_dtypes()))
1405: dtypes(*(get_all_int_dtypes() + get_all_fp_dtypes(include_bfloat16=False) +
1406: get_all_complex_dtypes()))
1471: dtypes(*get_all_dtypes(include_bfloat16=False))
1574: dtypes(*get_all_dtypes())
1601: dtypes(*get_all_dtypes(include_bfloat16=False))
1632: dtypes(*get_all_dtypes(include_bfloat16=False))
1711: for dt in get_all_dtypes():
1717: for dt in get_all_dtypes():
1724: for dt in get_all_dtypes():
```
</p>
</details>
I'm looking forward to your viewpoints. Thanks :)
cc: mruberry kshitij12345 anjali411
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71561
Reviewed By: samdow
Differential Revision: D34856571
Pulled By: mruberry
fbshipit-source-id: 0dca038bcad5cf69906245c496d2e61ac3876335
(cherry picked from commit b058f67b4313143efa714ab105f36e74083131b9)
2022-03-15 20:31:41 +00:00
Natalia Gimelshein
967606124a
port torch cov tests to error inputs ( #73977 )
...
Summary:
Per title
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73977
Reviewed By: malfet
Differential Revision: D34779552
Pulled By: ngimel
fbshipit-source-id: b4191101a029981eb27c75e1b56d739db046f819
(cherry picked from commit 2c2af726ffdba68f358a4ff0ee07580609bccc34)
2022-03-10 19:04:44 +00:00
Natalia Gimelshein
e47a5a64bb
Back out "Revert D34524207: [pytorch][PR] remove _s_where" ( #73579 )
...
Summary:
Original commit changeset: 87b1220d851c
Original Phabricator Diff: D34524207 (4eb24825684eb2482568https://github.com/pytorch/pytorch/pull/73579
Test Plan:
OSS tests
tested with canary https://www.internalfb.com/intern/ads/canary/441912928798660873
Reviewed By: ezyang
Differential Revision: D34688237
Pulled By: ngimel
fbshipit-source-id: 32f3a0046053ef52e95ab45a26bfc1de17e7e061
(cherry picked from commit d1c0acbe3e0ff884c429072923a468ee1d3d447d)
2022-03-08 19:15:30 +00:00
anjali411
37e0d2e361
Fix segfault while real and imaginary attributes are set to a number ( #73867 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73867
Fixes https://github.com/pytorch/pytorch/issues/72947
Test Plan: Imported from OSS
Reviewed By: davidberard98
Differential Revision: D34695956
Pulled By: anjali411
fbshipit-source-id: 2f3eda272a5214335eae506bd387ce8da4d81b8c
(cherry picked from commit fdb07354cac22c30aa047e65fbac9840608db811)
2022-03-08 18:58:26 +00:00
Natalia Gimelshein
55525632ab
Revert D34554432: Back out "Revert D34524207: [pytorch][PR] remove _s_where"
...
Test Plan: revert-hammer
Differential Revision:
D34554432 (9c03c6163f9c03c6163f
2022-03-04 20:32:39 +00:00
Natalia Gimelshein
9c03c6163f
Back out "Revert D34524207: [pytorch][PR] remove _s_where" ( #73579 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73579
Original commit changeset: 87b1220d851c
Original Phabricator Diff: D34524207 (4eb2482568
2022-03-04 19:35:41 +00:00
Nikita Karetnikov
eb0d370f14
Write explicit meta-kernels for normal ( #70089 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/70089
See #69386 .
Test Plan: Imported from OSS
Reviewed By: ejguan
Differential Revision: D34089964
Pulled By: bdhirsh
fbshipit-source-id: eb88eb7c4830545d3d43c82b6f3abb98617cee8e
(cherry picked from commit 89c9c02a0fb1c780495fee6370961104f4b1dcd1)
2022-03-01 23:28:14 +00:00
Nikita Shulga
dd9517cc4a
Revert D34524207: [pytorch][PR] remove _s_where
...
Test Plan: revert-hammer
Differential Revision:
D34524207 (4eb24825684eb2482568
2022-03-01 17:43:16 +00:00
Natalia Gimelshein
4eb2482568
remove _s_where ( #73468 )
...
Summary:
Per title
Fixes https://github.com/pytorch/pytorch/issues/73135
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73468
Reviewed By: albanD
Differential Revision: D34524207
Pulled By: ngimel
fbshipit-source-id: bc71e27b6d3fa50de6737533c92375266d9eadc5
(cherry picked from commit 047b925849370e6e4cbe9e3a722db52bb1e965b9)
2022-03-01 07:30:34 +00:00
Philip Meier
0973c5a1cc
align signature of make_tensor with other creation ops ( #72702 )
...
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/72702
Test Plan: Imported from OSS
Reviewed By: mrshenli
Differential Revision: D34457729
Pulled By: mruberry
fbshipit-source-id: 83d580c4201eef946dc9cf4b9e28a3d36be55609
(cherry picked from commit aa4cf20fbeb4b795595729b8ac2e6ba7707d8283)
2022-02-25 06:30:31 +00:00
Nikita Shulga
cfb6c942fe
scatter_reduce documentation (#73125 )
...
Summary:
Reland of https://github.com/pytorch/pytorch/issues/68580 (which were milestoned for 1.11) plus partial revert of https://github.com/pytorch/pytorch/pull/72543
Pull Request resolved: https://github.com/pytorch/pytorch/pull/73125
Reviewed By: bdhirsh
Differential Revision: D34355217
Pulled By: malfet
fbshipit-source-id: 325ecdeaf53183d653b44ee5e6e8839ceefd9200
(cherry picked from commit 71db31748a
2022-02-22 19:33:46 +00:00
Philip Meier
1f74e082e2
only compare attributes for meta tensors ( #72508 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72508
Todo:
- [x] document this behavior
- [x] add tests
Test Plan: Imported from OSS
Reviewed By: zou3519
Differential Revision: D34262452
Pulled By: ezyang
fbshipit-source-id: bc5c9653d5c3ad5c6efccc9c8e0efc0d28e15104
(cherry picked from commit 233142c88e
2022-02-17 02:33:08 +00:00
Brian Hirsh
f87f753bb9
avoiding adding some functions to the public python API before 1.11 release ( #72543 )
...
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/72543
Test Plan: Imported from OSS
Reviewed By: ejguan
Differential Revision: D34085724
Pulled By: bdhirsh
fbshipit-source-id: 941d5a90a6fa5328268d623e0e2b01577e4132ca
(cherry picked from commit 6676a0c79a
2022-02-14 19:49:01 +00:00
Kurt Mohler
47c6993355
Update from_dlpack tests and documentation ( #70543 )
...
Summary:
Part of https://github.com/pytorch/pytorch/issues/58742
Pull Request resolved: https://github.com/pytorch/pytorch/pull/70543
Reviewed By: soulitzer
Differential Revision: D34172475
Pulled By: mruberry
fbshipit-source-id: d498764b8651a8b7a19181b3421aeebf28a5db2b
(cherry picked from commit 05332f164c
2022-02-14 03:35:17 +00:00
anjali411
f607af126e
Set correct device id on efficientzerotensors ( #71611 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71611
Fixes https://github.com/pytorch/pytorch/issues/71160 https://github.com/pytorch/pytorch/issues/69925 #69913
Test Plan: Imported from OSS
Reviewed By: VitalyFedyunin
Differential Revision: D33897543
Pulled By: anjali411
fbshipit-source-id: f1d8608c351876b8c2619da5ef891f74bad30ab5
(cherry picked from commit 643e666ea3
2022-02-02 21:51:32 +00:00
Anjali Chourdia
1e4aefaa2f
Revert D33834916: Set correct device id on efficientzerotensors
...
Test Plan: revert-hammer
Differential Revision:
D33834916 (a18cfb790da18cfb790deba41aa646
2022-01-31 03:49:56 +00:00
anjali411
a18cfb790d
Set correct device id on efficientzerotensors ( #71611 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71611
Fixes https://github.com/pytorch/pytorch/issues/71160 https://github.com/pytorch/pytorch/issues/69925
Test Plan: Imported from OSS
Reviewed By: george-qi
Differential Revision: D33834916
Pulled By: anjali411
fbshipit-source-id: 11cec343e95e2ee188ab7576f26f64aa19317891
(cherry picked from commit f6e86f8a6b
2022-01-30 20:53:15 +00:00
Mikayla Gawarecki
09c417ae65
Add new reduce options and autograd support for scatter_reduce ( #71788 )
...
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/71788
Test Plan: Imported from OSS
Reviewed By: mikaylagawarecki
Differential Revision: D33778525
Pulled By: cpuhrsch
fbshipit-source-id: 47b8544e29df3075bc6ede894c59499a7ffec876
(cherry picked from commit ddcddac726
2022-01-27 17:38:50 +00:00
Mikayla Gawarecki
fdec94504f
Rename _scatter_reduce to scatter_reduce and make it unstructured ( #71787 )
...
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/71787
Test Plan: Imported from OSS
Reviewed By: mikaylagawarecki
Differential Revision: D33778524
Pulled By: cpuhrsch
fbshipit-source-id: 55a330e1c2227c0eaaa1c0d2f9205a4dee24a11b
(cherry picked from commit 6e4a8a91da
2022-01-27 16:29:13 +00:00
Mike Ruberry
0891c908bb
Revert D33768645: Set correct device id on efficientzerotensors
...
Test Plan: revert-hammer
Differential Revision:
D33768645 (5dd6cd55ba5dd6cd55ba8ca385b1d8
2022-01-26 17:01:32 +00:00
anjali411
5dd6cd55ba
Set correct device id on efficientzerotensors ( #71611 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71611
Fixes https://github.com/pytorch/pytorch/issues/71160
Test Plan: Imported from OSS
Reviewed By: pbelevich, ngimel
Differential Revision: D33768645
Pulled By: anjali411
fbshipit-source-id: 66ce9907630b65a12c0775077147a7e72ff4cee4
(cherry picked from commit 3af98a4d70
2022-01-25 23:32:11 +00:00
Jonathan Colen
33403f4848
edge_order check in torch.gradient only applies to dim argument ( #67926 )
...
Summary:
Fixes https://github.com/pytorch/pytorch/issues/67919
The compatibility check on `edge_order` in `pre_check_gradient` now looks only at dim argument if it is present, otherwise it checks all dimensions.
Previously, it would check all dimensions regardless of the dim argument and throw unnecessary errors.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67926
Reviewed By: albanD
Differential Revision: D33760621
Pulled By: mruberry
fbshipit-source-id: d490cd8610c68ff3787e670fc947de3cbf2db062
(cherry picked from commit 45bc56de9e
2022-01-25 21:29:31 +00:00
Mike Ruberry
e0d829a266
Kill the test_torch.py mixin and creates test_scatter_gather_ops ( #71691 )
...
Summary:
Per title.
Also annotates test_torch.py with additional cleanup tasks and adds empty sample inputs to elementwise unary and binary OpInfos.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71691
Reviewed By: ngimel
Differential Revision: D33735126
Pulled By: mruberry
fbshipit-source-id: 8cc097a7581a8b620540c95b2a5889c1165ecf23
(cherry picked from commit 5c6a245a3f
2022-01-24 09:32:32 +00:00
Mike Ruberry
7680a0ae9d
Deprecates _aminmax ( #71576 )
...
Summary:
Replaces https://github.com/pytorch/pytorch/pull/62432 . Existing callsites are updated.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/71576
Reviewed By: ngimel
Differential Revision: D33689960
Pulled By: mruberry
fbshipit-source-id: fad1ba78347ecec7fd48f21862c3eb606662b8f4
(cherry picked from commit 6cd438e9a1
2022-01-21 09:23:29 +00:00
Peter Bell
17bb68618f
Copy: Fix CPU transpose path ignoring neg and conj bits ( #69026 )
...
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/69026
Test Plan: Imported from OSS
Reviewed By: ngimel
Differential Revision: D33064533
Pulled By: anjali411
fbshipit-source-id: 98c25586a1707ac2324f69f652ce5a14dd59c0ad
2022-01-14 10:13:33 -08:00
Emilio Castillo
8dfff8b2e2
Fix scatter for empty indexes ( #70662 )
...
Summary:
This PR fixes an issue with `scatter` where the output is garbage for zero-sized indexes.
```py
import torch
null_index = torch.zeros((0, 4), dtype=torch.int64)
null_arr = torch.zeros((0, 4))
zeros_arr = torch.zeros((1, 4))
result = zeros_arr.scatter(0, null_index, null_arr)
print(null_index)
print(null_arr)
print(zeros_arr)
print(result)
```
```
tensor([], size=(0, 4), dtype=torch.int64)
tensor([], size=(0, 4))
tensor([[0., 0., 0., 0.]])
tensor([[1.7036e+19, 2.9965e+32, 3.9133e-14, 1.3585e-19]])
```
the out array is never filled if `index` arg has 0 elements.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/70662
Reviewed By: dagitses
Differential Revision: D33476807
Pulled By: albanD
fbshipit-source-id: 97dbdd9c0133899e58828c43ecba81838807b8af
2022-01-07 09:20:43 -08:00
Peter Bell
917d56a7e4
Copy: Fix conj bit being ignored on type mismatch ( #68963 )
...
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/68963
Test Plan: Imported from OSS
Reviewed By: ngimel
Differential Revision: D33064492
Pulled By: anjali411
fbshipit-source-id: 043f927d6bfff46bf5f8ea6fce9409f250bf8ff8
2022-01-05 17:59:32 -08:00
Brian Hirsh
457ba1dd3e
Porting index_add to structured kernels, add an out variant ( #65993 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65993
This PR attempts to port `index_add` to structured kernels, but does more than that:
* Adds an `out=` variant to `index_add`
* Revises `native_functions.yaml` registrations, to not have multiple entries and instead pass default value to `alpha`.
* Changes in `derivatives.yaml` file for autograd functioning
* Revises error messages, please see: https://github.com/pytorch/pytorch/pull/65993#issuecomment-945441615
Follow-up PRs in near future will attempt to refactor the OpInfo test, and will give another look at tests in `test/test_torch.py` for this function. (hence the use of ghstack for this)
~This is WIP because there are tests failing for `Dimname` variant on mobile/android builds, and I'm working on fixing them.~
Issue tracker: https://github.com/pytorch/pytorch/issues/55070
Test Plan: Imported from OSS
Reviewed By: ejguan
Differential Revision: D32646426
fbshipit-source-id: b035ecf843a9a27d4d1e18b202b035adc2a49ab5
2021-12-14 11:57:13 -08:00
kshitij12345
5b2586fe09
[testing] Ignore expected_regex in assertRaisesRegex for non-native device ( #68723 )
...
Summary:
Fixes https://github.com/pytorch/pytorch/issues/29719
Pull Request resolved: https://github.com/pytorch/pytorch/pull/68723
Reviewed By: zou3519
Differential Revision: D32797061
Pulled By: mruberry
fbshipit-source-id: 3bcae6d3d62d180059dbe39be520b0e7f9aea19f
2021-12-02 14:52:27 -08:00
Emilio Castillo
533e72e0a4
Fix DLPack CUDA stream convention ( #67618 )
...
Summary:
Apparently for the array API, cuda default stream and per thread stream should be 1 and 2 instead of 0 and 1:
https://data-apis.org/array-api/latest/API_specification/array_object.html?dlpack-self-stream-none#dlpack-self-stream-none .
This caused a problem in the interop with CuPy https://github.com/cupy/cupy/pull/5970#discussion_r739912926 .
cc rgommers leofang mruberry
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67618
Reviewed By: albanD
Differential Revision: D32521805
Pulled By: mruberry
fbshipit-source-id: 95777e4014e5edf1f88ba10adc03c6e34c13248d
2021-11-18 08:36:05 -08:00
kshitij12345
d5d2096dab
[testing] make @dtypes mandatory when using @dtypesIf ( #68186 )
...
Summary:
Fixes https://github.com/pytorch/pytorch/issues/53647
With this if a test forgets to add `dtypes` while using `dtypesIf`, following error is raised
```
AssertionError: dtypes is mandatory when using dtypesIf however 'test_exponential_no_zero' didn't specify it
```
**Tested Locally**
Pull Request resolved: https://github.com/pytorch/pytorch/pull/68186
Reviewed By: VitalyFedyunin
Differential Revision: D32468581
Pulled By: mruberry
fbshipit-source-id: 805e0855f988b77a5d8d4cd52b31426c04c2200b
2021-11-18 08:29:31 -08:00
rusty1s
9807787135
scatter_reduce (#68115 )
...
Summary:
Fixes https://github.com/pytorch/pytorch/issues/63780
Basic functionality of a `scatter_reduce` algorithm with `reduce="sum"`:
* `scatter_reduce` is named as `scatter_reduce2` due to compiling issues
* It currently re-uses functionality from `scatter_add`
* Tests are missing: WIP
The error when the `scatter_reduce` naming is used:
```
In file included from aten/src/ATen/core/TensorBody.h:3,
from ../aten/src/ATen/core/Tensor.h:3,
from ../aten/src/ATen/DeviceGuard.h:4,
from ../aten/src/ATen/ATen.h:11,
from aten/src/ATen/native/cpu/CopyKernel.cpp.DEFAULT.cpp:1:
aten/src/ATen/Operators.h:13949:18: error: redefinition of ‘struct at::_ops::scatter_reduce’
13949 | struct TORCH_API scatter_reduce {
| ^~~~~~~~~~~~~~
aten/src/ATen/Operators.h:13817:18: note: previous definition of ‘struct at::_ops::scatter_reduce’
13817 | struct TORCH_API scatter_reduce {
| ^~~~~~~~~~~~~~
aten/src/ATen/Operators.h:13960:18: error: redefinition of ‘struct at::_ops::scatter_reduce_out’
13960 | struct TORCH_API scatter_reduce_out {
| ^~~~~~~~~~~~~~~~~~
aten/src/ATen/Operators.h:13839:18: note: previous definition of ‘struct at::_ops::scatter_reduce_out’
13839 | struct TORCH_API scatter_reduce_out {
| ^~~~~~~~~~~~~~~~~~
In file included from ../aten/src/ATen/core/Tensor.h:3,
from ../aten/src/ATen/DeviceGuard.h:4,
from ../aten/src/ATen/ATen.h:11,
from aten/src/ATen/native/cpu/CopyKernel.cpp.DEFAULT.cpp:1:
aten/src/ATen/core/TensorBody.h: In member function ‘at::Tensor at::Tensor::scatter_reduce(int64_t, const at::Tensor&, c10::string_view, c10::optional<long int>) const’:
aten/src/ATen/core/TensorBody.h:3976:83: error: cannot convert ‘c10::string_view’ {aka ‘c10::basic_string_view<char>’} to ‘const at::Tensor&’
3976 | return at::_ops::scatter_reduce::call(const_cast<Tensor&>(*this), dim, index, reduce, output_size);
| ^~~~~~
| |
| c10::string_view {aka c10::basic_string_view<char>}
In file included from aten/src/ATen/core/TensorBody.h:3,
from ../aten/src/ATen/core/Tensor.h:3,
from ../aten/src/ATen/DeviceGuard.h:4,
from ../aten/src/ATen/ATen.h:11,
from aten/src/ATen/native/cpu/CopyKernel.cpp.DEFAULT.cpp:1:
aten/src/ATen/Operators.h:13824:109: note: initializing argument 4 of ‘static at::Tensor at::_ops::scatter_reduce::call(const at::Tensor&, int64_t, const at::Tensor&, const at::Tensor&, c10::string_view)’
13824 | static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce);
| ~~~~~~~~~~~~~~~~~~~^~~
In file included from ../aten/src/ATen/ATen.h:15,
from aten/src/ATen/native/cpu/CopyKernel.cpp.DEFAULT.cpp:1:
aten/src/ATen/Functions.h: In function ‘at::Tensor at::scatter_reduce(const at::Tensor&, int64_t, const at::Tensor&, c10::string_view, c10::optional<long int>)’:
aten/src/ATen/Functions.h:7119:61: error: cannot convert ‘c10::string_view’ {aka ‘c10::basic_string_view<char>’} to ‘const at::Tensor&’
7119 | return at::_ops::scatter_reduce::call(self, dim, index, reduce, output_size);
| ^~~~~~
| |
| c10::string_view {aka c10::basic_string_view<char>}
In file included from aten/src/ATen/core/TensorBody.h:3,
from ../aten/src/ATen/core/Tensor.h:3,
from ../aten/src/ATen/DeviceGuard.h:4,
from ../aten/src/ATen/ATen.h:11,
from aten/src/ATen/native/cpu/CopyKernel.cpp.DEFAULT.cpp:1:
aten/src/ATen/Operators.h:13824:109: note: initializing argument 4 of ‘static at::Tensor at::_ops::scatter_reduce::call(const at::Tensor&, int64_t, const at::Tensor&, const at::Tensor&, c10::string_view)’
13824 | static at::Tensor call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce);
| ~~~~~~~~~~~~~~~~~~~^~~
In file included from ../aten/src/ATen/ATen.h:15,
from aten/src/ATen/native/cpu/CopyKernel.cpp.DEFAULT.cpp:1:
aten/src/ATen/Functions.h: In function ‘at::Tensor& at::scatter_reduce_out(at::Tensor&, const at::Tensor&, int64_t, const at::Tensor&, c10::string_view, c10::optional<long int>)’:
aten/src/ATen/Functions.h:7124:65: error: cannot convert ‘c10::string_view’ {aka ‘c10::basic_string_view<char>’} to ‘const at::Tensor&’
7124 | return at::_ops::scatter_reduce_out::call(self, dim, index, reduce, output_size, out);
| ^~~~~~
| |
| c10::string_view {aka c10::basic_string_view<char>}
In file included from aten/src/ATen/core/TensorBody.h:3,
from ../aten/src/ATen/core/Tensor.h:3,
from ../aten/src/ATen/DeviceGuard.h:4,
from ../aten/src/ATen/ATen.h:11,
from aten/src/ATen/native/cpu/CopyKernel.cpp.DEFAULT.cpp:1:
aten/src/ATen/Operators.h:13846:111: note: initializing argument 4 of ‘static at::Tensor& at::_ops::scatter_reduce_out::call(const at::Tensor&, int64_t, const at::Tensor&, const at::Tensor&, c10::string_view, at::Tensor&)’
13846 | static at::Tensor & call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, at::Tensor & out);
| ~~~~~~~~~~~~~~~~~~~^~~
In file included from ../aten/src/ATen/ATen.h:15,
from aten/src/ATen/native/cpu/CopyKernel.cpp.DEFAULT.cpp:1:
aten/src/ATen/Functions.h: In function ‘at::Tensor& at::scatter_reduce_outf(const at::Tensor&, int64_t, const at::Tensor&, c10::string_view, c10::optional<long int>, at::Tensor&)’:
aten/src/ATen/Functions.h:7129:65: error: cannot convert ‘c10::string_view’ {aka ‘c10::basic_string_view<char>’} to ‘const at::Tensor&’
7129 | return at::_ops::scatter_reduce_out::call(self, dim, index, reduce, output_size, out);
| ^~~~~~
| |
| c10::string_view {aka c10::basic_string_view<char>}
In file included from aten/src/ATen/core/TensorBody.h:3,
from ../aten/src/ATen/core/Tensor.h:3,
from ../aten/src/ATen/DeviceGuard.h:4,
from ../aten/src/ATen/ATen.h:11,
from aten/src/ATen/native/cpu/CopyKernel.cpp.DEFAULT.cpp:1:
aten/src/ATen/Operators.h:13846:111: note: initializing argument 4 of ‘static at::Tensor& at::_ops::scatter_reduce_out::call(const at::Tensor&, int64_t, const at::Tensor&, const at::Tensor&, c10::string_view, at::Tensor&)’
13846 | static at::Tensor & call(const at::Tensor & self, int64_t dim, const at::Tensor & index, const at::Tensor & src, c10::string_view reduce, at::Tensor & out);
| ~~~~~~~~~~~~~~~~~~~^~~
In file included from aten/src/ATen/NativeFunctions.h:6,
from ../aten/src/ATen/TensorIndexing.h:12,
from ../aten/src/ATen/ATen.h:20,
from aten/src/ATen/native/cpu/CopyKernel.cpp.DEFAULT.cpp:1:
aten/src/ATen/NativeMetaFunctions.h: At global scope:
aten/src/ATen/NativeMetaFunctions.h:496:18: error: redefinition of ‘struct at::meta::structured_scatter_reduce’
496 | struct TORCH_API structured_scatter_reduce : public at::impl::MetaBase {
| ^~~~~~~~~~~~~~~~~~~~~~~~~
aten/src/ATen/NativeMetaFunctions.h:481:18: note: previous definition of ‘struct at::meta::structured_scatter_reduce’
481 | struct TORCH_API structured_scatter_reduce : public at::impl::MetaBase {
| ^~~~~~~~~~~~~~~~~~~~~~~~~
ninja: build stopped: subcommand failed.
```
Pull Request resolved: https://github.com/pytorch/pytorch/pull/68115
Reviewed By: albanD
Differential Revision: D32488450
Pulled By: cpuhrsch
fbshipit-source-id: 65e79c6d0555c0d5715535bb52aade8d5fcd9722
2021-11-17 19:53:12 -08:00
Mikayla Gawarecki
cac3cd1433
add torch.diff support for n greater than 1 ( #67260 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67260
Addressing 54853
Test Plan: Imported from OSS
Reviewed By: mruberry
Differential Revision: D31930294
Pulled By: mikaylagawarecki
fbshipit-source-id: 97c7a27e9200c6688242680ff96b73dfff828479
2021-11-17 09:16:33 -08:00
Nick Anderson
f9ea41f257
Fixes spelling error writeable to writable, improves warning, and documentation ( #67664 )
...
Summary:
Fixes https://github.com/pytorch/pytorch/issues/46741
pytorchbot
contributors: nickleus27, yanivsagy, and khanhthien123
SmrutiSikha this is mostly your work. We just did very minor clean up.
cc mruberry
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67664
Reviewed By: gchanan
Differential Revision: D32311838
Pulled By: mruberry
fbshipit-source-id: 0e5d4d888caeccb0fd7c80e6ff11b1b1fa8e00d6
2021-11-11 13:05:00 -08:00
Kurt Mohler
db014b8529
Add set_deterministic_debug_mode and get_deterministic_debug_mode ( #67778 )
...
Summary:
Fixes https://github.com/pytorch/pytorch/issues/67386
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67778
Reviewed By: ngimel
Differential Revision: D32310661
Pulled By: mruberry
fbshipit-source-id: 300129e96ca51c22fa711182ce6a9f4d4d2ce57f
2021-11-11 12:48:29 -08:00
Thomas Viehmann
33b7790907
Fix conv_transpose3d backward with non-contiguous grad_out ( #67829 )
...
Summary:
Many thanks to Forest Yang (meowmix) from the forum for reporting it with a minimal reproduction.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67829
Reviewed By: malfet
Differential Revision: D32184786
Pulled By: albanD
fbshipit-source-id: b63dbd3148b5def2109deb2f4612c08f55f59dfb
2021-11-05 08:34:21 -07:00
soulitzer
83e8612d11
Clean up test autograd ( #67413 )
...
Summary:
Partially fixes https://github.com/pytorch/pytorch/issues/66066
This PR:
- cleans up op-specific testing from test_autograd. test_autograd should be reserved for testing generic autograd functionality
- tests related to an operator are better colocated
- see the tracker for details
What to think about when moving tests to their correct test suite:
- naming, make sure its not too generic
- how the test is parametrized, sometimes we need to add/remove a device/dtype parameter
- can this be merged with existing tests
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67413
Reviewed By: jbschlosser, albanD
Differential Revision: D32031480
Pulled By: soulitzer
fbshipit-source-id: 8e13da1e58a38d5cecbfdfd4fe2b4fe6f816897f
2021-11-03 15:26:09 -07:00
kshitij12345
885a8e53ba
replace onlyOnCPUAndCUDA with onlyNativeDeviceTypes ( #65201 )
...
Summary:
Reference https://github.com/pytorch/pytorch/issues/53849
Replace `onlyOnCPUandCUDA` with `onlyNativeDeviceTypes` which includes `cpu, cuda and meta`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/65201
Reviewed By: mrshenli
Differential Revision: D31299718
Pulled By: mruberry
fbshipit-source-id: 2d8356450c035d6a314209ab51b2c237583920fd
2021-11-01 09:22:34 -07:00
kshitij12345
c00806beda
Add skipXLA and expectedFailureXLA decorator ( #66857 )
...
Summary:
Add skipXLA and expectedFailureXLA decorator and relevant test.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66857
Reviewed By: ngimel
Differential Revision: D32039856
Pulled By: mruberry
fbshipit-source-id: 3c99d5e06c1c7684d1f798c11c783bd6ebea9899
2021-10-29 19:53:36 -07:00
jjsjann123
1ec732bc46
Add fp16/fp32 autocasting to JIT/TorchScript ( #63939 )
...
Summary:
Adds mixed precision autocasting support between fp32/fp16 to torchscript/JIT. More in depth descriptoin can be found at [torch/csrc/jit/JIT-AUTOCAST.md](https://github.com/pytorch/pytorch/pull/63939/files#diff-1f1772aaa508841c5bb58b74ab98f49a1e577612cd9ea5c386c8714a75db830b )
This PR implemented an autocast optimization pass that inserts casting ops per AMP rule (torch/csrc/jit/passes/autocast.cpp), that mimics the behavior of eager autocast. The pass also takes into consideration the context of `torch.cuda.amp.autocast` and only inserts casting ops within the enabled context manager, giving feature parity as with eager amp autocast.
We currently provide JIT AMP autocast as a prototyping feature, so it is default off and could be turned on via `torch._C._jit_set_autocast_mode(True)`
The JIT support for autocast is subject to different constraints compared to the eager mode implementation (mostly related to the fact that TorchScript is statically typed), restriction on the user facing python code is described in doc torch/csrc/jit/JIT-AUTOCAST.md
This is a prototype, there are also implementation limitation that's necessary to keep this PR small and get something functioning quickly on upstream, so we can iterate on designs.
Few limitation/challenge that is not properly resolved in this PR:
1. Autocast inserts cast operation, which would have impact on scalar type of output tensor feeding downstream operations. We are not currently propagating the updated scalar types, this would give issues/wrong results on operations in promotion rules.
2. Backward for autodiff in JIT misses the casting of dgrad to input scalar type, as what autograd does in eager. This forces us to explicitly mark the casting operation for certain operations (e.g. binary ops), otherwise, we might be feeding dgrad with mismatch scalar type to input. This could potentially break gradient function consuming dgrad. (e.g. gemm backwards, which assumes grad_output to be of same scalar type as input')
3. `torch.autocast` api has an optional argument `dtype` which is not currently supported in the JIT autocast and we require a static value.
Credit goes mostly to:
tlemo
kevinstephano
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63939
Reviewed By: navahgar
Differential Revision: D31093381
Pulled By: eellison
fbshipit-source-id: da6e26c668c38b01e296f304507048d6c1794314
2021-10-27 12:11:36 -07:00
Nikita Shulga
77beccaedb
Do not build PyTorch with caffe2 by default ( #66658 )
...
Summary:
CAFFE2 has been deprecated for a while, but still included in every PyTorch build.
We should stop building it by default, although CI should still validate that caffe2 code is buildable.
Build even fewer dependencies when compiling mobile builds without Caffe2
Introduce `TEST_CAFFE2` in torch.common.utils
Skip `TestQuantizedEmbeddingOps` and `TestJit.test_old_models_bc` is code is compiled without Caffe2
Should be landed after https://github.com/pytorch/builder/pull/864
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66658
Reviewed By: driazati, seemethere, janeyx99
Differential Revision: D31669156
Pulled By: malfet
fbshipit-source-id: 1cc45e2d402daf913a4685eb9f841cc3863e458d
2021-10-21 20:32:47 -07:00
Kurt Mohler
94f4e9a995
Enable warning tests for nondeterministic backward functions ( #66736 )
...
Summary:
Followup from https://github.com/pytorch/pytorch/issues/66233
Since https://github.com/pytorch/pytorch/issues/50209 was fixed, we can enable these warning tests now
cc mruberry kurtamohler
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66736
Reviewed By: zou3519
Differential Revision: D31723385
Pulled By: mruberry
fbshipit-source-id: dc1922a6d0c45cc80020db85710e755a89113861
2021-10-21 12:51:53 -07:00
Jane Xu
8a65047acc
[skip ci] Set test owners for everything considered with module: tests ( #66865 )
...
Summary:
Action following https://github.com/pytorch/pytorch/issues/66232
cc mruberry
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66865
Reviewed By: anjali411
Differential Revision: D31771147
Pulled By: janeyx99
fbshipit-source-id: 8bebe5ac2098364ef1ee93b590abb5f4455b0f89
2021-10-20 09:37:03 -07:00
lezcano
0974215c4d
Prefer mT and mH over transpose(-2, -1) and transpose(-2, -1).conj() ( #64181 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64181
This PR replaces all the calls to:
- `transpose(-2, -1)` or `transpose(-1, -2)` by `mT()` in C++ and `mT` in Python
- `conj().transpose(-2, -1)` or `transpose(-2, -1).conj()` or `conj().transpose(-1, -2)` or `transpose(-1, -2).conj()` by `mH()` in C++ and `mH` in Python.
It also simplifies two pieces of code, and fixes one bug where a pair
of parentheses were missing in the function `make_symmetric_matrices`.
Test Plan: Imported from OSS
Reviewed By: H-Huang
Differential Revision: D31692896
Pulled By: anjali411
fbshipit-source-id: e9112c42343663d442dc5bd53ff2b492094b434a
2021-10-18 13:02:25 -07:00
Kurt Mohler
a25648953c
Add warn_only kwarg to use_deterministic_algorithms ( #66233 )
...
Summary:
Fixes https://github.com/pytorch/pytorch/issues/64883
Adds a `warn_only` kwarg to `use_deterministic_algorithms`. When enabled, calling an operation that does not have a deterministic implementation will raise a warning, rather than an error.
`torch.testing._internal.common_device_type.expectedAlertNondeterministic` is also refactored and documented in this PR to make it easier to use and understand.
cc mruberry kurtamohler
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66233
Reviewed By: bdhirsh
Differential Revision: D31616481
Pulled By: mruberry
fbshipit-source-id: 059634a82d54407492b1d8df08f059c758d0a420
2021-10-15 13:54:59 -07:00
anjali411
a82fcd3560
Disable .numpy() and .tolist() for tensor subclasses subclasses and fix .tolist() for conjugated and negated tensors ( #66082 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/66082
Fixes https://github.com/pytorch/pytorch/issues/66024 #65779
cc ezyang anjali411 dylanbespalko mruberry Lezcano nikitaved albanD
Test Plan: Imported from OSS
Reviewed By: Gamrix, albanD
Differential Revision: D31615588
Pulled By: anjali411
fbshipit-source-id: c3e65ef0fe301630eb76732ccd7819683c09aa19
2021-10-13 13:57:51 -07:00
lezcano
82a216c45b
Add tensor.{adjoint(),H,mT,mH} methods and properties ( #64179 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/64179
This PR follows the discussion in https://github.com/pytorch/pytorch/issues/45063#issuecomment-904431478
Fixes https://github.com/pytorch/pytorch/issues/45063
cc ezyang anjali411 dylanbespalko mruberry Lezcano nikitaved rgommers pmeier asmeurer leofang AnirudhDagar asi1024 emcastillo kmaehashi heitorschueroff
Test Plan: Imported from OSS
Reviewed By: bertmaher
Differential Revision: D30730483
Pulled By: anjali411
fbshipit-source-id: 821d25083f5f682450f6812bf852dc96a1cdf9f2
2021-10-13 07:44:43 -07:00
Kurt Mohler
5883523c1d
Remove dtype from torch.Storage and use only torch.ByteStorage ( #62030 )
...
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/62030
Remove dtype tracking from Python Storage interface, remove all the different `<type>Storage` classes except for `ByteStorage`, and update serialization accordingly, while maintaining as much FC/BC as possible
Fixes https://github.com/pytorch/pytorch/issues/47442
* **THE SERIALIZATION FORMAT IS FULLY FC/BC.** We worked very hard to make sure this is the case. We will probably want to break FC at some point to make the serialization structure of tensors make more sense, but not today.
* There is now only a single torch.ByteStorage class. Methods like `Tensor.set_` no longer check that the dtype of storage is appropriate.
* As we no longer know what dtype of a storage is, we've **removed** the size method from Storage, replacing it with nbytes. This is to help catch otherwise silent errors where you confuse number of elements with number of bytes.
* `Storage._new_shared` takes a `nbytes` kwarg and will reject previous positional only calls. `Storage._new_with_file` and `_set_from_file` require explicit element size arguments.
* It's no longer possible to convert storages to different types using the float/double/etc methods. Instead, do the conversion using a tensor.
* It's no longer possible to allocate a typed storage directly using FloatStorage/DoubleStorage/etc constructors. Instead, construct a tensor and extract its storage. The classes still exist but they are used purely for unpickling.
* The preexisting serialization format stores dtype with storage, and in fact this dtype is used to determine the dtype of the tensor overall.
To accommodate this case, we introduce a new TypedStorage concept that exists only during unpickling time which is used to temporarily store the dtype so we can construct a tensor. **If you overrode the handling of pickling/unpickling, you MUST add handling for TypedStorage** or your serialization code will degrade to standard file-based serialization.
Original pull request: https://github.com/pytorch/pytorch/pull/59671
Reviewed By: soulitzer, ngimel
Differential Revision: D29466819
Pulled By: ezyang
fbshipit-source-id: 4a14e5d3c2b08e06e558683d97f7378a3180b00e
2021-10-05 13:50:34 -07:00
Philip Meier
aebde1bc2b
deprecate device getter from torch.testing namespace ( #63844 )
...
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63844
Test Plan: Imported from OSS
Reviewed By: H-Huang
Differential Revision: D31141433
Pulled By: mruberry
fbshipit-source-id: a29331278ab99a19e225e2cb357458e3db4f9732
2021-09-29 02:40:52 -07:00
