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@fduwjj fduwjj commented Apr 6, 2022

Stack from ghstack (oldest at bottom):

Our previous logic does not fully all corner cases when it comes to imbalance sharding. For example, one is 16 another one is 9. (This cannot be chunk sharding) because the total length is 25 and if it's chunk sharding, it should be 13 and 12. So we need to get the total length first and calculated the expected chunk length to ensure it's indeed a chunk sharding case.

Also added more test cases in unit test.

Differential Revision: D35417257

… be inferred as chunkshardingspec

Our previous logic does not fully all corner cases when it comes to imbalance sharding. For example, one is 16 another one is 9. (This cannot be chunk sharding) because the total length is 25 and if it's chunk sharding, it should be 13 and 12. So we need to get the total length first and calculated the expected chunk length to ensure it's indeed a chunk sharding case.

Also added more test cases in unit test.

Differential Revision: [D35417257](https://our.internmc.facebook.com/intern/diff/D35417257/)

[ghstack-poisoned]
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@facebook-github-bot facebook-github-bot added the oncall: distributed Add this issue/PR to distributed oncall triage queue label Apr 6, 2022
fduwjj added a commit that referenced this pull request Apr 6, 2022
… be inferred as chunkshardingspec

Our previous logic does not fully all corner cases when it comes to imbalance sharding. For example, one is 16 another one is 9. (This cannot be chunk sharding) because the total length is 25 and if it's chunk sharding, it should be 13 and 12. So we need to get the total length first and calculated the expected chunk length to ensure it's indeed a chunk sharding case.

Also added more test cases in unit test.

Differential Revision: [D35417257](https://our.internmc.facebook.com/intern/diff/D35417257/)

ghstack-source-id: 153136085
Pull Request resolved: #75296
@fduwjj fduwjj requested review from fegin and wanchaol April 6, 2022 00:42
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Thanks for the fix!

…sharding to be inferred as chunkshardingspec"

Our previous logic does not fully all corner cases when it comes to imbalance sharding. For example, one is 16 another one is 9. (This cannot be chunk sharding) because the total length is 25 and if it's chunk sharding, it should be 13 and 12. So we need to get the total length first and calculated the expected chunk length to ensure it's indeed a chunk sharding case.

Also added more test cases in unit test.

Differential Revision: [D35417257](https://our.internmc.facebook.com/intern/diff/D35417257/)

[ghstack-poisoned]
fduwjj added a commit that referenced this pull request Apr 6, 2022
… be inferred as chunkshardingspec

Pull Request resolved: #75296

Our previous logic does not fully all corner cases when it comes to imbalance sharding. For example, one is 16 another one is 9. (This cannot be chunk sharding) because the total length is 25 and if it's chunk sharding, it should be 13 and 12. So we need to get the total length first and calculated the expected chunk length to ensure it's indeed a chunk sharding case.

Also added more test cases in unit test.
ghstack-source-id: 153190671

Differential Revision: [D35417257](https://our.internmc.facebook.com/intern/diff/D35417257/)
facebook-github-bot pushed a commit that referenced this pull request Apr 6, 2022
… be inferred as chunkshardingspec (#75296)

Summary:
Pull Request resolved: #75296

Our previous logic does not fully all corner cases when it comes to imbalance sharding. For example, one is 16 another one is 9. (This cannot be chunk sharding) because the total length is 25 and if it's chunk sharding, it should be 13 and 12. So we need to get the total length first and calculated the expected chunk length to ensure it's indeed a chunk sharding case.

Also added more test cases in unit test.
ghstack-source-id: 153190671

Test Plan: CI

Reviewed By: fegin

Differential Revision: D35417257

fbshipit-source-id: a7df2183f9747c765498eb460678709b76cdf7b4
@malfet malfet closed this in 782fd74 Apr 6, 2022
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github-actions bot commented Apr 6, 2022

Hey @fduwjj.
You've committed this PR, but it does not have both a 'release notes: ...' and 'topics: ...' label. Please add one of each to the PR. The 'release notes: ...' label should represent the part of PyTorch that this PR changes (fx, autograd, distributed, etc) and the 'topics: ...' label should represent the kind of PR it is (not user facing, new feature, bug fix, perf improvement, etc). The list of valid labels can be found here for the 'release notes: ...' and here for the 'topics: ...'.
For changes that are 'topic: not user facing' there is no need for a release notes label.

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4 participants