change from first element to a random element for cache missing items #4955
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…pytorch#4955) Summary: X-link: facebookresearch/FBGEMM#1974 In inference zch backend, we cannot use initializer to randomized init value for cache missing items, as the intializer does not work in parallel read and write mode. The current behavior is to always get the first item in hash map, but that has less randmization. This diff added a randmization for cache missing ids, also add a log to show the missing ids in every batch. Reviewed By: EddyLXJ Differential Revision: D83612329
…pytorch#4955) Summary: X-link: facebookresearch/FBGEMM#1974 In inference zch backend, we cannot use initializer to randomized init value for cache missing items, as the intializer does not work in parallel read and write mode. The current behavior is to always get the first item in hash map, but that has less randmization. This diff added a randmization for cache missing ids, also add a log to show the missing ids in every batch. Reviewed By: EddyLXJ Differential Revision: D83612329
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Summary:
X-link: https://github.com/facebookresearch/FBGEMM/pull/1974
In inference zch backend, we cannot use initializer to randomized init value for cache missing items, as the intializer does not work in parallel read and write mode.
The current behavior is to always get the first item in hash map, but that has less randmization.
This diff added a randmization for cache missing ids, also add a log to show the missing ids in every batch.
Differential Revision: D83612329