Added Optimizer configuration that supports optimizer type, learning rate, momentum, and weight decay configurations. #3094
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
Summary: Updated the `ParameterConstraints` in the TorchRec benchmarking script to include pooling factors, number of poolings, and batch sizes. This enhancement allows for more detailed configuration of embedding tables, improving the flexibility and precision of sharding strategies in distributed training scenarios. Differential Revision: D76440004
…ctionSparseNN models. Summary: Refactored the training benchmarking by moving generative helper functinos into separate util file and added a model configuration that supports SparseNN, TowerSparseNN, TowerCollectionSparseNN models. Future commits will add support for DeepFM and DLRM models. Differential Revision: D76539867
facebook-github-bot
added
the
CLA Signed
|
This pull request was exported from Phabricator. Differential Revision: D76559261 |
…rate, momentum, and weight decay configurations. (pytorch#3094) Summary: Pull Request resolved: pytorch#3094 This commit introduces enhancements to the optimizer configuration in TorchRec. It now supports specifying the optimizer type, learning rate, momentum, and weight decay. These changes provide more flexibility and control over the training process, allowing users to fine-tune their models with different optimization strategies and hyperparameters. Differential Revision: D76559261
|
This pull request was exported from Phabricator. Differential Revision: D76559261 |
SSYernar
force-pushed
the
export-D76559261
branch
from
1273789 to
26f6058
Compare
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Outdated suggestions cannot be applied.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: This commit introduces enhancements to the optimizer configuration in TorchRec. It now supports specifying the optimizer type, learning rate, momentum, and weight decay. These changes provide more flexibility and control over the training process, allowing users to fine-tune their models with different optimization strategies and hyperparameters.
Differential Revision: D76559261