Simplify fqns_to_feature_names in Delta Tracker #3081
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Summary: Pull Request resolved: pytorch#3059 # This Diff Added implementation for fqn_to_feature_names method along with initial testing framework and UTs for fqn_to_feature_names # ModelDeltaTracker Context ModelDeltaTracker is a utility for tracking and retrieving unique IDs and their corresponding embeddings or states from embedding modules in model using Torchrec. It's particularly useful for: 1. Identifying which embedding rows were accessed during model execution 2. Retrieving the latest delta or unique rows for a model 3. Computing top-k changed embeddings 4. Supporting streaming updated embeddings between systems during online training Differential Revision: D75908963 Reviewed By: TroyGarden
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This pull request was exported from Phabricator. Differential Revision: D76432354 |
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This pull request was exported from Phabricator. Differential Revision: D76432354 |
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Summary: Pull Request resolved: pytorch#3081 Each table in collection will have FQN. We can simplify the logic with this assumption to avoid two iterations. Existing tests passed with this logic. Differential Revision: D76432354
Summary: Pull Request resolved: pytorch#3081 Each table in collection will have FQN. We can simplify the logic with this assumption to avoid two iterations. Existing tests passed with this logic. Differential Revision: D76432354
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This pull request was exported from Phabricator. Differential Revision: D76432354 |
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Summary:
Each table in collection will have FQN. We can simplify the logic with this assumption to avoid two iterations.
Existing tests passed with this logic.
Differential Revision: D76432354