Add option to upload Nova artifacts to S3 directly #5668
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Summary: This uses the new `use-s3` input from pytorch/test-infra#5668 to upload exported models and Android artifacts directly to S3. iOS artifacts need to be built on GH runner with Xcode, so they will still need to go through GH before being uploaded to S3. This helps address scaling issue when upload large files to GitHub, for example: * Timing out https://github.com/pytorch/executorch/actions/runs/10858058150/job/30136354800 * or just fail in the middle of the upload https://github.com/pytorch/executorch/actions/runs/10856291106/job/30132545832 Pull Request resolved: #5375 Reviewed By: kirklandsign Differential Revision: D62680104 Pulled By: huydhn fbshipit-source-id: 4f82317526770b49c0ad2a555638ddb5dfa6316b
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For the context, Nova jobs upload the artifacts to GitHub because this works on all runners including non-AWS ones like GitHub runners. However, there is a scale issue when trying to upload large artifacts (GB in size) to GitHub that the files are too big, so the upload could either: * Timing out https://github.com/pytorch/executorch/actions/runs/10858058150/job/30136354800 * or just fail in the middle of the upload https://github.com/pytorch/executorch/actions/runs/10856291106/job/30132545832 To address this, I add the option to upload to S3 gha-artifacts bucket here which is direct and more efficient.
kit1980
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For the context, Nova jobs upload the artifacts to GitHub because this works on all runners including non-AWS ones like GitHub runners. However, there is a scale issue when trying to upload large artifacts (GB in size) to GitHub that the files are too big, so the upload could either: * Timing out https://github.com/pytorch/executorch/actions/runs/10858058150/job/30136354800 * or just fail in the middle of the upload https://github.com/pytorch/executorch/actions/runs/10856291106/job/30132545832 To address this, I add the option to upload to S3 gha-artifacts bucket here which is direct and more efficient.
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For the context, Nova jobs upload the artifacts to GitHub because this works on all runners including non-AWS ones like GitHub runners. However, there is a scale issue when trying to upload large artifacts (GB in size) to GitHub that the files are too big, so the upload could either:
To address this, I add the option to upload to S3 gha-artifacts bucket here which is direct and more efficient.