Relax Conformer RNN-T numerical parity tests

[hwangjeff]

Increases numerical tolerance on Conformer RNN-T TorchScript consistency tests to resolve CI test failures.

[pytorch-bot]

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/audio/3525

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❌ 1 New Failure

As of commit 27052e9:

NEW FAILURE - The following job has failed:

• build (3.8) (gh)

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[facebook-github-bot]

@hwangjeff has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator.

[facebook-github-bot]

@hwangjeff merged this pull request in 72b0917.

[github-actions]

Hey @hwangjeff.
You merged this PR, but labels were not properly added. Please add a primary and secondary label (See https://github.com/pytorch/audio/blob/main/.github/process_commit.py).

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Some guidance:

Use 'module: ops' for operations under 'torchaudio/{transforms, functional}', and ML-related components under 'torchaudio/csrc' (e.g. RNN-T loss).

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• 'tutorial' is applicable to tutorials under the “examples/tutorials” folder
• 'example' is applicable to everything else (e.g. C++ examples)
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Regarding examples in code documentations, please also use 'module: docs'.

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* Drop support of Python 3.7.
* Add support of Python 3.X.
* Change the way a third party library is bound (so that user needs to install it separately).