[ONNX] Opset 17 STFT support

[justinchuby]

Stack from ghstack (oldest at bottom):

• -> [ONNX] Opset 17 STFT support #83944

#81075

TODO:

• Split complex input into real
• Test

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❌ 1 New Failures, 1 Base Failures

As of commit f304c53 (more details on the Dr. CI page):

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• 1/2 failures introduced in this PR
• 1/2 broken upstream at merge base 7e38684 on Aug 23 from 9:38am to 2:13pm

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🕵️ 1 new failure recognized by patterns

The following CI failures do not appear to be due to upstream breakages

Lint / lintrunner (1/1)

Step: "Run lintrunner on all files" (full log | diagnosis details)

2022-08-23T22:25:50.6679450Z ##[error]Process completed with exit code 1.

2022-08-23T22:25:50.6666182Z         �[2m24�[0m  |import torch
2022-08-23T22:25:50.6666529Z         �[2m25�[0m  |from torch import _C
2022-08-23T22:25:50.6666847Z     >>> �[2m26�[0m  |�[33mfrom torch._C import _onnx as _C_onnx
2022-08-23T22:25:50.6667211Z �[0m        �[2m27�[0m  |from torch.onnx import _type_utils, symbolic_helper
2022-08-23T22:25:50.6667476Z         �[2m28�[0m  |
2022-08-23T22:25:50.6667691Z         �[2m29�[0m  |
2022-08-23T22:25:50.6667801Z 
2022-08-23T22:25:50.6667807Z 
2022-08-23T22:25:50.6668034Z �[1m�[36mYou can reproduce these results locally by using `lintrunner`.�[0m
2022-08-23T22:25:50.6668489Z �[1m�[36mSee https://github.com/pytorch/pytorch/wiki/lintrunner for setup instructions.�[0m
2022-08-23T22:25:50.6679450Z ##[error]Process completed with exit code 1.
2022-08-23T22:25:50.6714581Z ##[group]Run # Use jq to massage the JSON lint output into GitHub Actions workflow commands.
2022-08-23T22:25:50.6715042Z �[36;1m# Use jq to massage the JSON lint output into GitHub Actions workflow commands.�[0m
2022-08-23T22:25:50.6715381Z �[36;1mjq --raw-output \�[0m
2022-08-23T22:25:50.6715885Z �[36;1m  '"::\(if .severity == "advice" or .severity == "disabled" then "warning" else .severity end) file=\(.path),line=\(.line),col=\(.char),title=\(.code) \(.name)::" + (.description | gsub("\\n"; "%0A"))' \�[0m
2022-08-23T22:25:50.6716265Z �[36;1m  lint.json�[0m
2022-08-23T22:25:50.6762627Z shell: /usr/bin/bash -e {0}
2022-08-23T22:25:50.6762958Z env:
2022-08-23T22:25:50.6763234Z   pythonLocation: /opt/hostedtoolcache/Python/3.8.13/x64
2022-08-23T22:25:50.6763601Z   LD_LIBRARY_PATH: /opt/hostedtoolcache/Python/3.8.13/x64/lib
2022-08-23T22:25:50.6763897Z ##[endgroup]

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🚧 1 fixed upstream failure:

These were probably caused by upstream breakages that were already fixed.

Please rebase on the viable/strict branch (expand for instructions)

If your commit is older than viable/strict, run these commands:

git fetch https://github.com/pytorch/pytorch viable/strict
git rebase FETCH_HEAD

• pull / linux-bionic-py3.7-clang9 / test (dynamo, 2, 2, linux.2xlarge) on Aug 23 from 9:38am to 2:13pm (7e38684 - bbe803c)

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[nateanl]

Hi @justinchuby, thanks for working on the STFT support. Is the PR ready for review?

[justinchuby]

@nateanl thanks for asking! The PR is not ready yet. I started it and got distracted.

[mravanelli]

Thank you @justinchuby. Is there any news? It would be really great to have in in the next version of pytorch. This is something we actually need for SpeechBrain because we need the feature extraction pipeline to be ONN-exportable.

[justinchuby]

@mravanelli A more realistic issue I realized is ONNX doesn't have the appropriate ops to handle complex <-> real matrix conversion. Since the STFT op in python operates on complex numbers and onnx STFT operates on real numbers, I will need to think harder about how this is possible.

Assuming onnx does support the operator, you can always implement and register a custom symbolic function (https://pytorch.org/docs/stable/onnx.html#adding-support-for-operators) and not have to worry about pytorch release cycles.

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