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remove cache_precision parameter for infer TBE (pytorch#965)
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Summary:
Pull Request resolved: pytorch#965

The current inference TBE assumes cache precision to be the same as embedding precision. We thus remove this argument to avoid confusions.

Reviewed By: jasonjk-park

Differential Revision: D34635748

fbshipit-source-id: d52ada70a798b291fe5ebc4c116b120091dc799d
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jianyuh authored and facebook-github-bot committed Mar 5, 2022
1 parent 28be535 commit d399aee
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Original file line number Diff line number Diff line change
Expand Up @@ -1552,7 +1552,6 @@ def __init__(
cache_load_factor: float = 0.2,
cache_sets: int = 0,
cache_reserved_memory: float = 0.0,
cache_precision: SparseType = SparseType.FP32,
enforce_hbm: bool = False, # place all weights/momentums in HBM when using cache
record_cache_metrics: Optional[RecordCacheMetrics] = None,
) -> None: # noqa C901 # tuple of (rows, dims,)
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