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binaries/README.md

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Note: `--nightly` option puts the *.whl files in a subfolder named 'nightly' in the specified bucket
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```
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python s3_binary_upload.py --s3-bucket <s3_bucket> --s3-backup-bucket <s3_backup_bucket> --nightly
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```
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```
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## Uploading packages to production torchserve account
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As a first step binaries and docker containers need to be available in some staging environment. In that scenario the binaries can just be `wget`'d and then uploaded using the instructions below and the docker staging environment just needs a 1 line code change in https://github.com/pytorch/serve/blob/master/docker/promote-docker.sh#L8
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### pypi
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Binaries should show up here: https://pypi.org/project/torchserve/
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You need to be on the list of maintainers to run the below.
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`twine upload <path/to.wheel>`
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### conda
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Binaries should show up here: https://anaconda.org/pytorch/torchserve
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```
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# Authenticate with pytorchbot credentials
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anaconda login
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# Upload binaries
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anaconda upload -u pytorch <path/to/.bz2>
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```
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## docker
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Binaries should show up here: https://hub.docker.com/r/pytorch/torchserve
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Change the staging org to your personal docker or test docker account https://github.com/pytorch/serve/blob/master/docker/promote-docker.sh#L8
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```
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# authenticate to docker with pytorchbot credentials
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docker login
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# upload docker image
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./docker/promote-docker.sh
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```
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If everything looks good make sure to `export $DRY_RUN=disabled` or remove that line from the code

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