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OpenDAS
fairscale
Commits
3e36cd07
Unverified
Commit
3e36cd07
authored
Mar 09, 2022
by
tmarkstrum
Committed by
GitHub
Mar 09, 2022
Browse files
[chore] 0.4.6 release (#953)
* [chore] 0.4.6 release * added the third party libs removed by precommit
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CHANGELOG.md
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3e36cd07
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@@ -5,8 +5,14 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to
[
Semantic Versioning
](
https://semver.org/spec/v2.0.0.html
)
.
## [0.4.
6
] - TBD
## [0.4.
7
] - TBD
### Added
### Fixed
[0.4.6] - 2022-03-08
### Added
-
CosFace's LMCL is added to MEVO. This is a loss function that is suitable
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@@ -18,6 +24,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
if set, wraps the root module regardless of how many unwrapped params there were
left after children were wrapped. [#930]
-
FSDP: Add support for saving optimizer state when using expert replicas with FSDP.
-
OSS: Add a new arg "forced_broadcast_object" to OSS __init__ to apply "_broadcast_object"
for rebuilding the sharded optimizer. [#937]
-
FSDP: Add an arg disable_reshard_on_root for FSDP __init__ [#878]
### Fixed
-
FSDP: fixed handling of internal states with state_dict and load_state_dict
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README.md
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3e36cd07
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@@ -27,6 +27,8 @@ FairScale was designed with the following values in mind:
## What's New:
*
March 2022
[
fairscale 0.4.6 was released
](
https://github.com/facebookresearch/fairscale/releases/tag/v0.4.6
)
.
*
We have support for CosFace's LMCL in MEVO. This is a loss function that is suitable for large number of prediction target classes.
*
January 2022
[
fairscale 0.4.5 was released
](
https://github.com/facebookresearch/fairscale/releases/tag/v0.4.5
)
.
*
We have experimental support for layer wise gradient scaling.
*
We enabled reduce_scatter operation overlapping in FSDP backward propagation.
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