[Edited] Add docstring to improve documentation #147119
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* [CI] Release only changes for 2.1 release * include circle script * release only changes for test-infra * More test-infra related
ghstack-source-id: 613c4f3 Pull Request resolved: pytorch#108060
…ch#108139) For test_conv_bn_fuse dynamic case, we always fuse bn with convolution and there only a external convolution call, not loops, so it will failed when we do a dynamic loop vars check. This PR will skip this case. Pull Request resolved: pytorch#108113 Approved by: https://github.com/huydhn
…8075) (pytorch#108177) It should be `${{ inputs.build_environment }}`, although I wonder why not just clean up the artifacts directory for all build instead of just `aarch64` Pull Request resolved: pytorch#108075 Approved by: https://github.com/atalman, https://github.com/seemethere
…ytorch#108200) There are more issues that I expect at the beginning: * Triton was uploaded on `main` instead of `nightly` and release branch * The environment `conda-aws-upload` wasn't used correctly in both wheel and conda upload * Conda update wasn't run in a separate ephemeral runner * Duplicated upload logic, should have just use `bash .circleci/scripts/binary_upload.sh` instead * Handle `CONDA_PYTORCHBOT_TOKEN` and `CONDA_PYTORCHBOT_TOKEN_TEST` tokens in a similar way as pytorch/test-infra#4530 Part of pytorch#108154
main PR already merged: pytorch#108137
…de (pytorch#108203) (pytorch#108251) This is the follow-up of pytorch#108187 to set the correct release version without commit hash for triton wheel and conda binaries when building them in release mode. ### Testing * With commit hash (nightly): https://github.com/pytorch/pytorch/actions/runs/6019021716 * Without commit hash https://github.com/pytorch/pytorch/actions/runs/6019378616 (by adding `--release` into the PR) Pull Request resolved: pytorch#108203 Approved by: https://github.com/atalman
This should be nightly for nightly and test for release candidates. There are 2 bugs: * The shell needs to set to `bash` explicitly, otherwise, GHA uses `sh` which doesn't recognized `[[` as shown in https://github.com/pytorch/pytorch/actions/runs/6030476858/job/16362717792#step:6:10 *`${GITHUB_REF_NAME}` is un-quoted. This is basically https://www.shellcheck.net/wiki/SC2248 but this wasn't captured by actionlint, and shellcheck doesn't work with workflow YAML file. I will think about how to add a lint rule for this later then. ### Testing https://github.com/pytorch/pytorch/actions/runs/6031330411 to confirm that setting the channel is performed correctly. Pull Request resolved: pytorch#108291 Approved by: https://github.com/osalpekar, https://github.com/atalman
…h#95271) (pytorch#108216) ### Motivation - Add channels_last3d support for mkldnn conv and mkldnn deconv. - Use `ideep::convolution_transpose_forward::compute_v3` instead of `ideep::convolution_transpose_forward::compute`. compute_v3 uses `is_channels_last` to notify ideep whether to go CL or not to align with the memory format check of PyTorch. ### Testing 1 socket (28 cores): - memory format: torch.contiguous_format module | shape | forward / ms | backward / ms -- | -- | -- | -- conv3d | input size: (32, 32, 10, 100, 100), weight size: (32, 32, 3, 3, 3) | 64.56885 | 150.1796 conv3d | input size: (32, 16, 10, 200, 200), weight size: (16, 16, 3, 3, 3) | 100.6754 | 231.8883 conv3d | input size: (16, 4, 5, 300, 300), weight size: (4, 4, 3, 3, 3) | 19.31751 | 68.31131 module | shape | forward / ms | backward / ms -- | -- | -- | -- ConvTranspose3d | input size: (32, 32, 10, 100, 100), weight size: (32, 32, 3, 3, 3) | 122.7646 | 207.5125 ConvTranspose3d | input size: (32, 16, 10, 200, 200), weight size: (16, 16, 3, 3, 3) | 202.4542 | 368.5492 ConvTranspose3d | input size: (16, 4, 5, 300, 300), weight size: (4, 4, 3, 3, 3) | 122.959 | 84.62577 - memory format: torch.channels_last_3d module | shape | forward / ms | backward / ms -- | -- | -- | -- conv3d | input size: (32, 32, 10, 100, 100), weight size: (32, 32, 3, 3, 3) | 40.06993 | 114.317 conv3d | input size: (32, 16, 10, 200, 200), weight size: (16, 16, 3, 3, 3 | 49.08249 | 133.4079 conv3d | input size: (16, 4, 5, 300, 300), weight size: (4, 4, 3, 3, 3) | 5.873911 | 17.58647 module | shape | forward / ms | backward / ms -- | -- | -- | -- ConvTranspose3d | input size: (32, 32, 10, 100, 100), weight size: (32, 32, 3, 3, 3) | 88.4246 | 208.2269 ConvTranspose3d | input size: (32, 16, 10, 200, 200), weight size: (16, 16, 3, 3, 3 | 140.0725 | 270.4172 ConvTranspose3d | input size: (16, 4, 5, 300, 300), weight size: (4, 4, 3, 3, 3) | 23.0223 | 37.16972 Pull Request resolved: pytorch#95271 Approved by: https://github.com/jgong5, https://github.com/cpuhrsch
…ytorch#108385) Addresses [issue pytorch#106085](pytorch#106085). In `torch/nn/modules/rnn.py`: - Adds documentation string to RNNBase class. - Adds parameters to __init__ methods for RNN, LSTM, and GRU, classes. - Adds type annotations to __init__ methods for RNN, LSTM, and GRU. In `torch/ao/nn/quantized/dynamic/modules/rnn.py`: - Adds type specifications to `_FLOAT_MODULE` attributes in RNNBase, RNN, LSTM, and GRU classes. > This resolves a `mypy` assignment error `Incompatible types in assignment (expression has type "Type[LSTM]", base class "RNNBase" defined the type as "Type[RNNBase]")` that seemed to be a result of fully specified type annotations in `torch/nn/modules/rnn.py`). Pull Request resolved: pytorch#106222 Approved by: https://github.com/mikaylagawarecki
…8410) By refactoring `_local_scalar_dense_mps` to use `_empty_like` to allocate CPU tensor. Also, print a more reasonable error message when dst dim is less than src in mps_copy_ This fixes regression introduced by pytorch#105617 and adds regression test. <!-- copilot:poem --> ### <samp>🤖 Generated by Copilot at abd06e6</samp> > _Sing, O Muse, of the valiant deeds of the PyTorch developers_ > _Who strive to improve the performance and usability of tensors_ > _And who, with skill and wisdom, fixed a bug in the MPS backend_ > _That caused confusion and dismay to many a user of `item()`_ Fixes pytorch#107867 Pull Request resolved: pytorch#107913 Approved by: https://github.com/albanD Co-authored-by: Nikita Shulga <nikita.shulga@gmail.com>
…S, and changed the error message (pytorch#107758) (pytorch#108365) New message when invalid option is provided <img width="1551" alt="image" src="https://github.com/pytorch/pytorch/assets/6355099/8b61534a-ee55-431e-94fe-2ffa25b7fd5c"> TORCH_LOGS="help" <img width="1558" alt="image" src="https://github.com/pytorch/pytorch/assets/6355099/72e8939c-92fa-4141-8114-79db71451d42"> TORCH_LOGS="+help" <img width="1551" alt="image" src="https://github.com/pytorch/pytorch/assets/6355099/2cdc94ac-505a-478c-aa58-0175526075d2"> Pull Request resolved: pytorch#107758 Approved by: https://github.com/ezyang, https://github.com/mlazos ghstack dependencies: pytorch#106192
…n set as an installation requirement yet (pytorch#108424) (pytorch#108471) The dependency was added twice before in CUDA and ROCm binaries, one as an installation dependency from builder and the later as an extra dependency for dynamo, for example: ``` Requires-Python: >=3.8.0 Description-Content-Type: text/markdown License-File: LICENSE License-File: NOTICE Requires-Dist: filelock Requires-Dist: typing-extensions Requires-Dist: sympy Requires-Dist: networkx Requires-Dist: jinja2 Requires-Dist: fsspec Requires-Dist: pytorch-triton (==2.1.0+e6216047b8) Provides-Extra: dynamo Requires-Dist: pytorch-triton (==2.1.0+e6216047b8) ; extra == 'dynamo' Requires-Dist: jinja2 ; extra == 'dynamo' Provides-Extra: opt-einsum Requires-Dist: opt-einsum (>=3.3) ; extra == 'opt-einsum' ``` In the previous release, we needed to remove this part from `setup.py` to build release binaries pytorch#96010. With this, that step isn't needed anymore because the dependency will come from builder. ### Testing Using the draft pytorch#108374 for testing and manually inspect the wheels artifact at https://github.com/pytorch/pytorch/actions/runs/6045878399 (don't want to go through all `ciflow/binaries` again) * torch-2.1.0.dev20230901+cu121-cp39-cp39-linux_x86_64 ``` Requires-Python: >=3.8.0 Description-Content-Type: text/markdown Requires-Dist: filelock Requires-Dist: typing-extensions Requires-Dist: sympy Requires-Dist: networkx Requires-Dist: jinja2 Requires-Dist: fsspec Requires-Dist: pytorch-triton (==2.1.0+e6216047b8) <-- This will be 2.1.0 on the release branch after pytorch/builder#1515 Provides-Extra: dynamo Requires-Dist: jinja2 ; extra == 'dynamo' Provides-Extra: opt-einsum Requires-Dist: opt-einsum (>=3.3) ; extra == 'opt-einsum' ``` * torch-2.1.0.dev20230901+cu121.with.pypi.cudnn-cp39-cp39-linux_x86_64 ``` Requires-Python: >=3.8.0 Description-Content-Type: text/markdown Requires-Dist: filelock Requires-Dist: typing-extensions Requires-Dist: sympy Requires-Dist: networkx Requires-Dist: jinja2 Requires-Dist: fsspec Requires-Dist: pytorch-triton (==2.1.0+e6216047b8) Requires-Dist: nvidia-cuda-nvrtc-cu12 (==12.1.105) ; platform_system == "Linux" and platform_machine == "x86_64" Requires-Dist: nvidia-cuda-runtime-cu12 (==12.1.105) ; platform_system == "Linux" and platform_machine == "x86_64" Requires-Dist: nvidia-cuda-cupti-cu12 (==12.1.105) ; platform_system == "Linux" and platform_machine == "x86_64" Requires-Dist: nvidia-cudnn-cu12 (==8.9.2.26) ; platform_system == "Linux" and platform_machine == "x86_64" Requires-Dist: nvidia-cublas-cu12 (==12.1.3.1) ; platform_system == "Linux" and platform_machine == "x86_64" Requires-Dist: nvidia-cufft-cu12 (==11.0.2.54) ; platform_system == "Linux" and platform_machine == "x86_64" Requires-Dist: nvidia-curand-cu12 (==10.3.2.106) ; platform_system == "Linux" and platform_machine == "x86_64" Requires-Dist: nvidia-cusolver-cu12 (==11.4.5.107) ; platform_system == "Linux" and platform_machine == "x86_64" Requires-Dist: nvidia-cusparse-cu12 (==12.1.0.106) ; platform_system == "Linux" and platform_machine == "x86_64" Requires-Dist: nvidia-nccl-cu12 (==2.18.1) ; platform_system == "Linux" and platform_machine == "x86_64" Requires-Dist: nvidia-nvtx-cu12 (==12.1.105) ; platform_system == "Linux" and platform_machine == "x86_64" Requires-Dist: triton (==2.1.0) ; platform_system == "Linux" and platform_machine == "x86_64" <--This is 2.1.0 because it already has pytorch#108423, but the package doesn't exist yet atm Provides-Extra: dynamo Requires-Dist: jinja2 ; extra == 'dynamo' Provides-Extra: opt-einsum Requires-Dist: opt-einsum (>=3.3) ; extra == 'opt-einsum' ``` * torch-2.1.0.dev20230901+rocm5.6-cp38-cp38-linux_x86_64 ``` Requires-Python: >=3.8.0 Description-Content-Type: text/markdown Requires-Dist: filelock Requires-Dist: typing-extensions Requires-Dist: sympy Requires-Dist: networkx Requires-Dist: jinja2 Requires-Dist: fsspec Requires-Dist: pytorch-triton-rocm (==2.1.0+34f8189eae) <-- This will be 2.1.0 on the release branch after pytorch/builder#1515 Provides-Extra: dynamo Requires-Dist: jinja2 ; extra == 'dynamo' Provides-Extra: opt-einsum Requires-Dist: opt-einsum (>=3.3) ; extra == 'opt-einsum' ``` Pull Request resolved: pytorch#108424 Approved by: https://github.com/atalman
Release branch cherrypick of pytorch#108096
ghstack-source-id: 5d421f7 Pull Request resolved: pytorch#107722
…ytorch#108523) * When byteorder record is missing load as little endian by default Fixes pytorch#101688 * Add test for warning Also change warning type from DeprecationWarning to UserWarning to make it visible by default.
…8143) (pytorch#108258) Pull Request resolved: pytorch#108143 Approved by: https://github.com/andrewor14 Co-authored-by: Tugsbayasgalan Manlaibaatar <tmanlaibaatar@fb.com>
) (pytorch#108255) Summary: This commit adds a public facing `torch.ao.quantization.move_model_to_eval` util function for QAT users. Instead of calling model.eval() on an exported model (which doesn't work, see pytorch#103681), the user would call this new util function instead. This ensures special ops such as dropout and batchnorm (not supported yet) will have the right behavior when the graph is later used for inference. Note: Support for an equivalent `move_model_to_train` will be added in the future. This is difficult to do for dropout currently because the eval pattern of dropout is simply a clone op, which we cannot just match and replace with a dropout op. Test Plan: python test/test_quantization.py TestQuantizePT2E.test_move_model_to_eval Reviewers: jerryzh168, kimishpatel Subscribers: jerryzh168, kimishpatel, supriyar Differential Revision: [D48814735](https://our.internmc.facebook.com/intern/diff/D48814735) Pull Request resolved: pytorch#108184 Approved by: https://github.com/jerryzh168
…h#108593) Building docker in trunk is failing atm https://github.com/pytorch/pytorch/actions/runs/6033657019/job/16370683676 with the following error: ``` + conda_reinstall numpy=1.24.4 + as_jenkins conda install -q -n py_3.10 -y --force-reinstall numpy=1.24.4 + sudo -E -H -u jenkins env -u SUDO_UID -u SUDO_GID -u SUDO_COMMAND -u SUDO_USER env PATH=/opt/conda/envs/py_3.10/bin:/opt/conda/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 conda install -q -n py_3.10 -y --force-reinstall numpy=1.24.4 Collecting package metadata (current_repodata.json): ...working... done Solving environment: ...working... unsuccessful initial attempt using frozen solve. Retrying with flexible solve. Collecting package metadata (repodata.json): ...working... done Solving environment: ...working... unsuccessful initial attempt using frozen solve. Retrying with flexible solve. PackagesNotFoundError: The following packages are not available from current channels: - numpy=1.24.4 Current channels: - https://repo.anaconda.com/pkgs/main/linux-64 - https://repo.anaconda.com/pkgs/main/noarch - https://repo.anaconda.com/pkgs/r/linux-64 - https://repo.anaconda.com/pkgs/r/noarch ``` This was pulled in by pandas 2.1.0 released yesterday https://pypi.org/project/pandas/2.1.0 Pull Request resolved: pytorch#108355 Approved by: https://github.com/kit1980, https://github.com/atalman, https://github.com/malfet
…ytorch#108141) (pytorch#108327) A previous PR pytorch#106274 decomposes `aten.dropout` and would create a `clone()` when `eval()` or `p=0`. This makes many SDPA-related models fail to match fused_attention pattern matchers. This PR adds new fused_attention pattern matchers with an additional clone to re-enable the SDPA op matching. Pull Request resolved: pytorch#108141 Approved by: https://github.com/jgong5, https://github.com/eellison
…rch#108596) Fixes pytorch#103142 Pull Request resolved: pytorch#108292 Approved by: https://github.com/albanD Co-authored-by: Kurt Mohler <kmohler@quansight.com>
…torch#108628) Doc Preview: https://docs-preview.pytorch.org/pytorch/pytorch/108130/torch.compiler_faq.html#torch-func-works-with-torch-compile-for-grad-and-vmap-transforms Will also cherry-pick this for release branch. Pull Request resolved: pytorch#108130 Approved by: https://github.com/zou3519
This PR fixes the new_empty_strided op to become replicate from sharding when necessary, this is a quick fix to resolve pytorch#107661 We'll need to think more about the behavior of this op when it comes to sharding, one possibility is to follow the input sharding, but given the output shape of this op might not be the same as the input, it's hard to say we should follow the input sharding, further improvement needed once we figure out the op syntax Pull Request resolved: pytorch#107835 Approved by: https://github.com/fduwjj
MayureshMore
requested review from
a team,
albanD,
angelayi,
jbschlosser,
jeffdaily,
jerryzh168,
justinchuby,
kulinseth,
malfet,
shubhambhokare1,
titaiwangms,
tugsbayasgalan,
wschin,
ydwu4 and
zhxchen17
as code owners
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/147119
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit f4c686b with merge base 138e289 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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Looks like the PR brought in a lot of old diffs, which is likely a mistake that subscribed a bunch of people. Closing this PR--please open a new clean one with only your intended changes accompanied by a descriptive PR body. |
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Changes made in branch: MayureshMore:2.1-dynamic-doc
[Edited] Add docstring to improve documentation
cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @EikanWang @jgong5 @wenzhe-nrv @sanchitintel @jeffdaily @sunway513 @jithunnair-amd @pruthvistony @ROCmSupport @dllehr-amd @jataylo @hongxiayang @naromero77amd @mingfeima @XiaobingSuper @ashokei @jingxu10 @gujinghui @PenghuiCheng @jianyuh @min-jean-cho @yanbing-j @Guobing-Chen @Xia-Weiwen @snadampal @ezyang @SherlockNoMad @voznesenskym @penguinwu @zhuhaozhe @blzheng @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov @StrongerXi