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@chongkong chongkong commented Oct 5, 2020

Assuming each project follows the semantic versioning, stable projects (version>=1.0.0) guarantees backward compatibility across the same major versions, so we might cap the max version to the next major version for safety.

Also curious there's a special reason for having numpy<1.19.0 constraints. If 1.19.0 was a problematic version we might want to exclude culprit versions only, not an upper cap.

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Assuming each project follows the semantic versioning, stable projects (version>=1.0.0) guarantees backward compatibility across the same major versions, so we might cap the max version to the next major version for safety.

Also curious there's a special reason for having numpy<1.19.0 constraints. If 1.19.0 was a problematic version we might want to exclude culprit versions only, not an upper cap.
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Reviewed 1 of 1 files at r1.
Reviewable status: :shipit: complete! 1 of 1 approvals obtained

@pyu10055 pyu10055 merged commit f899442 into tensorflow:master Oct 5, 2020
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