39 Commits

Author SHA1 Message Date
086d146f6f Update ruff linter for PEP585 (#147540)
This turns on PEP585 enforcement in RUFF.

- Updates the target python version
- Stops ignoring UP006 warnings (PEP585)
- Fixes a few issues which crept into the tree in the last day

Pull Request resolved: https://github.com/pytorch/pytorch/pull/147540
Approved by: https://github.com/justinchuby, https://github.com/Skylion007
2025-02-22 04:45:17 +00:00
d8c8ba2440 Fix unused Python variables in test/[e-z]* (#136964)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/136964
Approved by: https://github.com/justinchuby, https://github.com/albanD
2024-12-18 23:02:30 +00:00
ccc0aa69ce [ONNX] Remove torch.onnx._export (#133824)
- Remove the deprecated torch.onnx._export function
- Remove test/onnx/test_export_modes.py because export modes are no longer supported
Pull Request resolved: https://github.com/pytorch/pytorch/pull/133824
Approved by: https://github.com/titaiwangms
2024-08-20 20:54:48 +00:00
fbe6f42dcf [BE][Easy][8/19] enforce style for empty lines in import segments in test/[k-p]*/ (#129759)
See https://github.com/pytorch/pytorch/pull/129751#issue-2380881501. Most changes are auto-generated by linter.

You can review these PRs via:

```bash
git diff --ignore-all-space --ignore-blank-lines HEAD~1
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/129759
Approved by: https://github.com/justinchuby, https://github.com/ezyang
2024-07-31 02:09:20 +00:00
93e249969b [BE] enable ruff rule RSE and remove useless parentheses in raise statements (#124261)
Remove useless parentheses in `raise` statements if the exception type is raised with no argument.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/124261
Approved by: https://github.com/albanD
2024-04-17 19:29:34 +00:00
a5364b12bb Revert "[ONNX] Remove the depreacated function _export (#109763)"
This reverts commit d7c05bb2e8de24386664c01e887357ff50a09842.

Reverted https://github.com/pytorch/pytorch/pull/109763 on behalf of https://github.com/facebook-github-bot due to Diff reverted internally ([comment](https://github.com/pytorch/pytorch/pull/109763#issuecomment-1734201053))
2023-09-25 17:47:21 +00:00
d7c05bb2e8 [ONNX] Remove the depreacated function _export (#109763)
`_export` API was depreacated and should be removed after 2.0.

See: https://github.com/pytorch/pytorch/pull/107208

Pull Request resolved: https://github.com/pytorch/pytorch/pull/109763
Approved by: https://github.com/thiagocrepaldi
2023-09-22 07:14:13 +00:00
cd31c170c9 Revert "[ONNX] Remove deprecated functions (#107208)"
This reverts commit 263ca7d69bb9b3b58ae0f9b4d27864587611389c.

Reverted https://github.com/pytorch/pytorch/pull/107208 on behalf of https://github.com/facebook-github-bot due to Diff reverted internally ([comment](https://github.com/pytorch/pytorch/pull/107208#issuecomment-1726183104))
2023-09-19 17:26:48 +00:00
263ca7d69b [ONNX] Remove deprecated functions (#107208)
The usage of some functions is deprecated. This PR drop them.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/107208
Approved by: https://github.com/justinchuby, https://github.com/thiagocrepaldi
2023-09-14 19:09:56 +00:00
3e2ea32dab [BE]: Enable ruff rule TRY302 and apply fixes (#101874)
Removes useless try statements and unreachable code.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/101874
Approved by: https://github.com/malfet
2023-05-19 17:30:52 +00:00
18264432f7 [ONNX] replace all _C._flatten to torch.jit._flatten (#83598)
_C._flatten is exactly the same as torch.jit._flatten. Unifying them to reduce confusion.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/83598
Approved by: https://github.com/justinchuby, https://github.com/BowenBao
2022-09-01 00:31:28 +00:00
161e931156 [ONNX] Modernize python syntax (#77935)
Use pyupgrade(https://github.com/asottile/pyupgrade) and flynt to modernize python syntax

```sh
pyupgrade --py36-plus --keep-runtime-typing torch/onnx/**/*.py
pyupgrade --py36-plus --keep-runtime-typing test/onnx/**/*.py
flynt torch/onnx/ --line-length 120
```

- Use f-strings for string formatting
- Use the new `super()` syntax for class initialization
- Use dictionary / set comprehension
Pull Request resolved: https://github.com/pytorch/pytorch/pull/77935
Approved by: https://github.com/BowenBao
2022-05-24 22:52:37 +00:00
5dd1c67776 [ONNX] Format ONNX python with black
Format all onnx python code with black and isort with

```sh
isort torch/onnx/ test/onnx
black torch/onnx/ test/onnx
```

Updated lintrunner config to include these paths.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/76754
Approved by: https://github.com/suo, https://github.com/BowenBao
2022-05-05 00:19:22 +00:00
48c8de45b0 [ONNX] Remove the argument example_outpus of export() method entirely. (#67082) (#67809)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/67809

* remove the argument example_outpus of export() method entirely

[ONNX] Follow-up: Remove the argument example_outpus of export() method entirely. (#67629)

* Resolve CI failure

* remove test after removing example_outputs

[ONNX] Follow-up: Follow-up: Remove the argument example_outpus of export() method entirely (#67719)

Removing unused import, resolving flake error.

Test Plan: Imported from OSS

Reviewed By: msaroufim

Differential Revision: D32181305

Pulled By: malfet

fbshipit-source-id: ba00547b7cb455ace86606b1bda643c02bdcfa1b

Co-authored-by: hwangdeyu <dejack953@outlook.com>
2021-11-12 17:06:26 -08:00
0a6828a306 [ONNX] use consistent quoting for string literals (#57757) (#58695)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58695

As PEP8 says: "Pick a rule and stick to it." [1]

[1] https://www.python.org/dev/peps/pep-0008/#string-quotes

Test Plan: Imported from OSS

Reviewed By: driazati

Differential Revision: D28714811

Pulled By: SplitInfinity

fbshipit-source-id: c95103aceb1725c17c034dc6fc8216627f189548

Co-authored-by: Gary Miguel <garymiguel@microsoft.com>
2021-05-27 12:06:42 -07:00
0d5527de7a Back out "Back out "[ONNX] Process const folding progressively when converts to ONNX (#54569)"" (#58923)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58923

Original commit changeset: c54597b2048e
ghstack-source-id: 129842041

Test Plan: Sandcastle and OSS CI.

Reviewed By: snisarg

Differential Revision: D28432555

fbshipit-source-id: 2a9ec22cc004c7c6979f1cc8f3124b833cdc6634
2021-05-26 13:29:07 -07:00
c034bce979 Back out "[ONNX] Process const folding progressively when converts to ONNX (#54569)"
Summary: Original commit changeset: 833dac7c71f2

Test Plan:
```
buck test mode/dev //pytext/fb/assistant/lite/test:test -- --exact
'pytext/fb/assistant/lite/test:test - test_export_bytes_model_to_caffe2
(pytext.fb.assistant.lite.test.test.TestExport)'
```

Reviewed By: jeanm

Differential Revision: D28431840

fbshipit-source-id: 0f1d530034404421a5d51691173e1cc0ee16fdd6
2021-05-14 13:45:49 -07:00
bfe7728f18 [ONNX] Process const folding progressively when converts to ONNX (#54569) (#57601)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/57601

This PR automatically solves onnx const attribute issue in PR https://github.com/pytorch/pytorch/pull/53784.

Test Plan: Imported from OSS

Reviewed By: malfet

Differential Revision: D28393525

Pulled By: SplitInfinity

fbshipit-source-id: 833dac7c71f24a88af62d5dd2be0a702ed34d053

Co-authored-by: David <jiafa@microsoft.com>
2021-05-13 13:42:51 -07:00
57d1df071f [ONNX] Support inplace operations on inplace indexing (#52063) (#53306)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/53306

* [ONNX] Fix for sequence of mutations in blocks (#51577)

Fixes consecutive mutations in a tensor inside blocks.
Also, support append and pop in blocks.

* Support inplace operations + indexing

* Clean up old pass for remove mutations

* Add loop test

* Fixes for set attr in loops

* Removing the new jit API flag

* [ONNX] Redesign onnx pass to enable shape type dependent pattern conversion - cont (#51795)

With the introduction of ONNX shape inference, shape and type are inferred on the fly as operators get converted from ATen to ONNX when running symbolic function. This resolves the shape/type requirement for the symbolic functions. The pre-onnx passes however, can not be supported by shape inference, since at that stage the operators in the graph are still ATen operators.

This PR is to update the design of ONNX pass, to enable a mechanism of capturing subgraphs of ATen operators of certain patterns, and convert them later, when shape/type information of upstream operators are available.

The new design will require pre-onnx passes that need shape/type to be written in two parts, encapsulation and conversion.

    The encapsulation part will find the nodes of patterns, like how pre-onnx passes were written previously. But instead of converting the nodes, it will encapsulate them into a sub-block of a new placeholder node. This part is called before onnx pass, so it runs before calling symbolic functions.

    The conversion part will be called inside the onnx pass. In onnx pass, run_symbolic_func will be called for each node in topological order. When it reaches the placeholder node, the conversion part will be invoked. It will convert the nodes inside the sub-block based on pattern. By that time, it will have shape/type of upstream operators available. After the conversion is complete, the placeholder node will be removed, and nodes inside its sub-block converted. Run_symbolic_func will be called for these nodes, and they will be converted from ATen operator to ONNX operator.

This PR includes several other fixes, listed below.
* ~~replace helper.cpp with onnx_utils.cpp for holding utility functions.~~
* fix EraseNumberTypes on Bool type, the code was outdated that back then Bool type doesn't exist.
* ~~enable onnx shape inference in export with parameter/initializer data.~~
* other code clean ups.
* fix insertion of identity nodes for loop opset 13 sequence output.

~~PR depends on #51603~~

* Fix after merge

* clang

* Fix clang

* Fix clang

* Fix warning message.

* Fixes for non-model param attributes

* Fix for caffe2

* Additional test

* clang

* Skip test for lower opsets

* fix clang-tidy

* Update init.cpp

* Update remove_inplace_ops_for_onnx.cpp

* Update remove_inplace_ops_for_onnx.cpp

* Update remove_inplace_ops_for_onnx.cpp

* Fix for clang formatting

Test Plan: Imported from OSS

Reviewed By: pbelevich, malfet

Differential Revision: D26922416

Pulled By: SplitInfinity

fbshipit-source-id: e7108620b39b6404c594910786c4d275fee59d84

Co-authored-by: Bowen Bao <bowbao@microsoft.com>
2021-03-12 02:49:11 -08:00
e6779d4357 [*.py] Rename "Arguments:" to "Args:" (#49736)
Summary:
I've written custom parsers and emitters for everything from docstrings to classes and functions. However, I recently came across an issue when I was parsing/generating from the TensorFlow codebase: inconsistent use of `Args:` and `Arguments:` in its docstrings.

```sh
(pytorch#c348fae)$ for name in 'Args:' 'Arguments:'; do
    printf '%-10s %04d\n' "$name" "$(rg -IFtpy --count-matches "$name" | paste -s -d+ -- | bc)"; done
Args:      1095
Arguments: 0336
```

It is easy enough to extend my parsers to support both variants, however it looks like `Arguments:` is wrong anyway, as per:

  - https://google.github.io/styleguide/pyguide.html#doc-function-args @ [`ddccc0f`](https://github.com/google/styleguide/blob/ddccc0f/pyguide.md)

  - https://chromium.googlesource.com/chromiumos/docs/+/master/styleguide/python.md#describing-arguments-in-docstrings @ [`9fc0fc0`](https://chromium.googlesource.com/chromiumos/docs/+/9fc0fc0/styleguide/python.md)

  - https://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html @ [`c0ae8e3`](https://github.com/sphinx-contrib/napoleon/blob/c0ae8e3/docs/source/example_google.rst)

Therefore, only `Args:` is valid. This PR replaces them throughout the codebase.

PS: For related PRs, see tensorflow/tensorflow/pull/45420

PPS: The trackbacks automatically appearing below are sending the same changes to other repositories in the [PyTorch](https://github.com/pytorch) organisation.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/49736

Reviewed By: albanD

Differential Revision: D25710534

Pulled By: soumith

fbshipit-source-id: 61e8ff01abb433e9f78185c2d1d0cbd7c22c1619
2020-12-28 09:34:47 -08:00
93719440b8 Replace map(lambda constructs (#46462)
Summary:
Follow-up of https://github.com/pytorch/pytorch/issues/46461 with a similar goal

Makes them more readable and possibly faster. Care has to be taken because `map` applies the function immediately while `(x for x in xs)` is a generator expression which gets evaluated later. This is a benefit in some cases where it is not required to actually create the list of values in memory (e.g. when passing to `tuple` or `extend` or `join`)

Pull Request resolved: https://github.com/pytorch/pytorch/pull/46462

Reviewed By: zou3519

Differential Revision: D24422343

Pulled By: ezyang

fbshipit-source-id: 252e33499c92ac0b15238f2df32681dbbda2b237
2020-10-22 09:50:22 -07:00
5b0f400488 Replace list(map(...)) constructs by list comprehensions (#46461)
Summary:
As discussed in https://github.com/pytorch/pytorch/issues/46392 this makes the code more readable and possibly more performant.

It also fixes a bug detected by this where the argument order of `map` was confused: 030a24906e (diff-5bb26bd3a23ee3bb540aeadcc0385df2a4e48de39f87ed9ea76b21990738fe98L1537-R1537)

Fixes https://github.com/pytorch/pytorch/issues/46392

Pull Request resolved: https://github.com/pytorch/pytorch/pull/46461

Reviewed By: ailzhang

Differential Revision: D24367015

Pulled By: ezyang

fbshipit-source-id: d55a67933cc22346b00544c9671f09982ad920e7
2020-10-19 18:42:49 -07:00
3d7c22a2ce [ONNX] Enable new scripting passes for functionalization and remove_mutation (#43791)
Summary:
Duplicate of https://github.com/pytorch/pytorch/issues/41413
This PR initiates the process of updating the torchsciprt backend interface used by ONNX exporter.

Replace jit lower graph pass by freeze module pass

Enable ScriptModule tests for ONNX operator tests (ORT backend) and model tests by default.

Replace jit remove_inplace_ops pass with remove_mutation and consolidation all passes for handling inplace ops.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/43791

Reviewed By: houseroad

Differential Revision: D23421872

Pulled By: bzinodev

fbshipit-source-id: a98710c45ee905748ec58385e2a232de2486331b
2020-09-04 15:21:45 -07:00
b7b99ab0c8 [ONNX] Remove Aten ops from ONNX export (#37239)
Summary:
This PR adds a new operator export type to exporter: ONNX_FALLTHROUGH
This new type allows ops that are not supported to pass through.
This PR also removes all aten ops in ONNX operator export type mode.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/37239

Reviewed By: hl475

Differential Revision: D21440509

Pulled By: houseroad

fbshipit-source-id: 38b826677cf3431ea44868efebefe1ff51c9aa75
2020-05-29 21:20:14 -07:00
728c7dcea3 ONNX Update training ops and training amenable export API (#35567)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/35567

Reviewed By: hl475

Differential Revision: D20715339

Pulled By: houseroad

fbshipit-source-id: ad88097e76b169035ab5814b769dc1bed54c6008
2020-03-29 23:14:25 -07:00
45e1be9762 Revert D19710370: [pytorch][PR] ONNX Update training ops and training amenable export API
Test Plan: revert-hammer

Differential Revision:
D19710370

Original commit changeset: e5e79d385529

fbshipit-source-id: d0114dc561a3415869805d3fbf43b92730bbcf54
2020-03-27 06:51:05 -07:00
025a0abe5a ONNX Update training ops and training amenable export API (#32950)
Summary:
- Update Dropout and Batchnorm in opset 12 : https://github.com/onnx/onnx/pull/2568
- Update api logic for exporting to ONNX training amenable models
Pull Request resolved: https://github.com/pytorch/pytorch/pull/32950

Reviewed By: hl475

Differential Revision: D19710370

Pulled By: houseroad

fbshipit-source-id: e5e79d38552936966662c41d39ddf33be1ba3e35
2020-03-27 00:39:39 -07:00
512c2a2df5 Enable constant folding (#29834)
Summary:
Set default do_constant_folding = True
Pull Request resolved: https://github.com/pytorch/pytorch/pull/29834

Reviewed By: hl475

Differential Revision: D18588037

Pulled By: houseroad

fbshipit-source-id: b35c06161321629c886e177ea666eff31cebf06a
2019-11-27 08:34:20 -08:00
06db5ad707 Provide names for operator nodes in ONNX exported graph. (#27342)
Summary:
The PyTorch exporter does not add any name to the ONNX operators in the exported graph. A common request is to add names to op nodes by default. This helps the readability of the graph in visualization tools such a Netron, or when the ONNX graph is printed as a string. Also, it helps with the debuggability of the ONNX graph.

Therefore this PR adds name to operators in the exporters. The names follow a simple format, <op_type>_<index>. Expect files for tests in `test/onnx/test_operators.py` have been updated.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/27342

Reviewed By: hl475

Differential Revision: D17790979

Pulled By: houseroad

fbshipit-source-id: 1eaae88b5f51f152735a2ff96e22827837e34d9d
2019-11-26 06:53:53 -08:00
7583519b87 Provide argument in ONNX export to exclude intializers from graph inputs. (#23284)
Summary:
Starting ONNX IR version 4, the initializers in the ONNX graph do not have to be inputs of the graphs. This constraint, which existed in IR version 3 and earlier, was relaxed in IR version 4. This PR provides an API level argument to allow ONNX export with the relaxed constraint of IR version 4, i.e. provides the option to not include initializers as inputs. This allows backends/runtimes to do certain optimizations, such as constant folding, better.

*Edit*: After discussion with houseroad we have the following behavior. For any OperatorExportType, except OperatorExportTypes.ONNX, the current status of export is maintained in this PR by default. However, the user can override it by setting the `keep_initializers_as_inputs` argument to the export API.  But when exporting to ONNX, i.e. OperatorExportType is OperatorExportTypes.ONNX, the current status is changed in that by default the initializers are NOT part of the input. Again, the default can be overridden by setting the `keep_initializers_as_inputs` argument.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/23284

Differential Revision: D16459961

Pulled By: bddppq

fbshipit-source-id: b8f0270dfaba47cdb8e04bd4cc2d6294f1cb39cf
2019-08-12 14:17:25 -07:00
45c6fa0007 Refactor Tests for Multiple ONNX Opsets (#20036)
Summary:
Refactor tests for https://github.com/pytorch/pytorch/pull/19294.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/20036

Reviewed By: zrphercule

Differential Revision: D16016593

Pulled By: houseroad

fbshipit-source-id: eaae324e347679acf3d0ac1c14be03919f54496e
2019-06-26 17:06:57 -07:00
299ea84a70 Use latest stable flake8-bugbear in CI and fix B011 flake8 error. (#21944)
Summary:
- PyCQA/flake8-bugbear#53 has been fixed (but not yet closed on their side) and a new version of flake8-bugbear has been released on Mar 28, 2019. Switch CI to use the latest stable version.
- Fix the new B011 errors that flake8-bugbear catches in the current codebase.

 ---

B011: Do not call assert False since python -O removes these calls. Instead callers should raise AssertionError().
Pull Request resolved: https://github.com/pytorch/pytorch/pull/21944

Differential Revision: D15974842

Pulled By: soumith

fbshipit-source-id: de5c2c07015f7f1c50cb3904c651914b8c83bf5c
2019-06-24 20:48:15 -07:00
28be521e39 Fix bug in exporting node with multiple outputs by scripting
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/20256

Differential Revision: D15422040

Pulled By: houseroad

fbshipit-source-id: 5de2a992d7d99a48905c39a1878eb0b3b68d6a3f
2019-05-22 16:29:36 -07:00
a64cce326f Add constant folding to ONNX graph during export (Resubmission) (#18698)
Summary:
Rewritten version of https://github.com/pytorch/pytorch/pull/17771 using graph C++ APIs.

This PR adds the ability to do constant folding on ONNX graphs during PT->ONNX export. This is done mainly to optimize the graph and make it leaner. The two attached snapshots show a multiple-node LSTM model before and after constant folding.
A couple of notes:
1. Constant folding is by default turned off for now. The goal is to turn it on by default once we have validated it through all the tests.
2. Support for folding in nested blocks is not in place, but will be added in the future, if needed.

**Original Model:**
![multiple_lstm_original](https://user-images.githubusercontent.com/23646532/53987630-6ac53980-40d6-11e9-9702-1ccfee124a83.JPG)
**Constant-folded model:**
![multiple_lstm_constant_folded](https://user-images.githubusercontent.com/23646532/53987632-6c8efd00-40d6-11e9-81c5-362c16f68861.JPG)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18698

Differential Revision: D14889768

Pulled By: houseroad

fbshipit-source-id: b6616b1011de9668f7c4317c880cb8ad4c7b631a
2019-04-18 00:10:04 -07:00
443a58e03d Export C10 operator in PyTorch Model (#18210)
Summary:
Almost there, feel free to review.

these c10 operators are exported to _caffe2 domain.

TODO:

- [x] let the onnx checker pass
- [x] test tensor list as argument
- [x] test caffe2 backend and converter
- [x] check the c10 schema can be exported to onnx
- [x] refactor the test case to share some code
- [x] fix the problem in ONNX_ATEN_FALLBACK
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18210

Reviewed By: zrphercule

Differential Revision: D14600916

Pulled By: houseroad

fbshipit-source-id: 2592a75f21098fb6ceb38c5d00ee40e9e01cd144
2019-04-08 16:06:00 -07:00
ba81074c40 Fix B902 lint error: invalid first argument. (#18181)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/18181
ghimport-source-id: 9c23551584a1a1b0b7ac246367f3a7ae1c50b315

Stack from [ghstack](https://github.com/ezyang/ghstack):
* #18184 Fix B903 lint: save memory for data classes with slots/namedtuple
* **#18181 Fix B902 lint error: invalid first argument.**
* #18178 Fix B006 lint errors: using mutable structure in default argument.
* #18177 Fix lstrip bug revealed by B005 lint

A variety of sins were committed:
- Some code was dead
- Some code was actually a staticmethod
- Some code just named it the wrong way
- Some code was purposely testing the omitted case

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Differential Revision: D14530876

fbshipit-source-id: 292a371d9a76ddc7bfcfd38b6f0da9165290a58e
2019-03-21 09:10:28 -07:00
97eb139a94 Turn atol to 1e-5 when comparing the end to end results (#17708)
Summary:
results smaller than 1e-5 don't make sense.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/17708

Differential Revision: D14348893

Pulled By: houseroad

fbshipit-source-id: 5e07c38e5b58b27b61fae63bfc3c21e2fe5629fe
2019-03-06 12:06:45 -08:00
f09003d95d A trivial typo fixed in onnx.verify.verify (#15871)
Summary:
A trivial typo fixing.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/15871

Differential Revision: D13709588

Pulled By: ezyang

fbshipit-source-id: 84460e53e30470bef72bc836c08fd149b4d725cf
2019-01-17 09:57:33 -08:00
141d81d095 Move ONNX integration tests from onnx-fb-universe to PyTorch repo (#7397)
* Move ONNX integration tests from onnx-fb-universe to PyTorch repo

* Switch to use torchvision

* Delete single rnn operator tests, they have been covered in e2e tests in test_caffe2.py

* Mirror the fix in onnx-fb-universe to bypass cuda check

667326d84b
2018-05-11 15:05:18 -07:00