More aggressive memory freeing from TrainPipelineContext #1967
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
facebook-github-bot
added
the
CLA Signed
|
This pull request was exported from Phabricator. Differential Revision: D57123339 |
dstaay-fb
added a commit
to dstaay-fb/torchrec
that referenced
this pull request
May 8, 2024
…h#1967) Summary: As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount) relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext. Differential Revision: D57123339 Privacy Context Container: 1203980333745195
dstaay-fb
force-pushed
the
export-D57123339
branch
from
48623f7 to
287c942
Compare
|
This pull request was exported from Phabricator. Differential Revision: D57123339 |
dstaay-fb
added a commit
to dstaay-fb/torchrec
that referenced
this pull request
May 8, 2024
…h#1967) Summary: As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount) relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext. broader internal discusion: https://fb.workplace.com/groups/970281557043698/permalink/1664528510952329/ Differential Revision: D57123339 Privacy Context Container: 1203980333745195
dstaay-fb
force-pushed
the
export-D57123339
branch
from
287c942 to
33f349c
Compare
dstaay-fb
added a commit
to dstaay-fb/recipes
that referenced
this pull request
May 8, 2024
Summary: X-link: meta-pytorch/torchrec#1967 As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount) relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext. broader internal discusion: https://fb.workplace.com/groups/970281557043698/permalink/1664528510952329/ Differential Revision: D57123339 Privacy Context Container: 1203980333745195
|
This pull request was exported from Phabricator. Differential Revision: D57123339 |
…h#1967) Summary: X-link: facebookresearch/recipes#43 As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount) relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext. broader internal discusion: https://fb.workplace.com/groups/970281557043698/permalink/1664528510952329/ Differential Revision: D57123339 Privacy Context Container: 1203980333745195
dstaay-fb
added a commit
to dstaay-fb/recipes
that referenced
this pull request
May 9, 2024
Summary: X-link: meta-pytorch/torchrec#1967 As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount) relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext. broader internal discusion: https://fb.workplace.com/groups/970281557043698/permalink/1664528510952329/ Differential Revision: D57123339 Privacy Context Container: 1203980333745195
dstaay-fb
force-pushed
the
export-D57123339
branch
from
33f349c to
915606b
Compare
|
This pull request was exported from Phabricator. Differential Revision: D57123339 |
dstaay-fb
added a commit
to dstaay-fb/torchrec
that referenced
this pull request
May 9, 2024
…h#1967) Summary: X-link: facebookresearch/recipes#43 As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount) relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext. broader internal discusion: https://fb.workplace.com/groups/970281557043698/permalink/1664528510952329/ Differential Revision: D57123339 Privacy Context Container: 1203980333745195
dstaay-fb
added a commit
to dstaay-fb/torchrec
that referenced
this pull request
May 9, 2024
…h#1967) Summary: X-link: facebookresearch/recipes#43 As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount) relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext. broader internal discusion: https://fb.workplace.com/groups/970281557043698/permalink/1664528510952329/ Reviewed By: joshuadeng Differential Revision: D57123339 Privacy Context Container: 1203980333745195
henrylhtsang
pushed a commit
to henrylhtsang/torchrec
that referenced
this pull request
May 9, 2024
…h#1967) Summary: X-link: facebookresearch/recipes#43 Pull Request resolved: meta-pytorch#1967 As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount) relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext. broader internal discusion: https://fb.workplace.com/groups/970281557043698/permalink/1664528510952329/ Differential Revision: D57123339 Privacy Context Container: 1203980333745195
henrylhtsang
pushed a commit
to henrylhtsang/torchrec
that referenced
this pull request
May 9, 2024
…h#1967) Summary: X-link: facebookresearch/recipes#43 Pull Request resolved: meta-pytorch#1967 As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount) relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext. broader internal discusion: https://fb.workplace.com/groups/970281557043698/permalink/1664528510952329/ Differential Revision: D57123339 Privacy Context Container: 1203980333745195
dstaay-fb
added a commit
to dstaay-fb/torchrec
that referenced
this pull request
May 9, 2024
…h#1967) Summary: X-link: facebookresearch/recipes#43 As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount) relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext. broader internal discusion: https://fb.workplace.com/groups/970281557043698/permalink/1664528510952329/ Reviewed By: joshuadeng, henrylhtsang Differential Revision: D57123339 Privacy Context Container: 1203980333745195
facebook-github-bot
pushed a commit
to facebookresearch/recipes
that referenced
this pull request
May 10, 2024
Summary: Pull Request resolved: #43 X-link: meta-pytorch/torchrec#1967 As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount) relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext. broader internal discusion: https://fb.workplace.com/groups/970281557043698/permalink/1664528510952329/ Reviewed By: joshuadeng, henrylhtsang Differential Revision: D57123339 Privacy Context Container: 1203980333745195 fbshipit-source-id: e2bd0c95d59619786168b31745c3b79a52fd5969
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Summary:
As users highlighted, TrainPipeline refactoring introduced memory regression ~2% due to more context management for code readability. This results in higher peak memory (takes longer for a context to drop out of refcount)
relatively easy to get a lot more aggressive about releasing memory stored in TrainPipelineContext.
Differential Revision:
D57123339
Privacy Context Container: 1203980333745195