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Add method to fetch if a feature is weighted #2727

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Add method to fetch if a feature is weighted #2727

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6 changes: 6 additions & 0 deletions torchrec/distributed/embedding_types.py
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Original file line number Diff line number Diff line change
Expand Up @@ -274,6 +274,12 @@ def embedding_shard_metadata(self) -> List[Optional[ShardMetadata]]:
embedding_shard_metadata.append(table.local_metadata)
return embedding_shard_metadata

def features_weighted(self) -> List[bool]:
is_weighted = []
for table in self.embedding_tables:
is_weighted.extend([table.is_weighted] * table.num_features())
return is_weighted


F = TypeVar("F", bound=Multistreamable)
T = TypeVar("T")
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9 changes: 9 additions & 0 deletions torchrec/distributed/sharding/tw_sharding.py
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Expand Up @@ -264,6 +264,15 @@ def features_per_rank(self) -> List[int]:
features_per_rank.append(num_features)
return features_per_rank

def is_weighted_per_rank(self) -> List[List[bool]]:
is_weighted = []
for grouped_embedding_configs in self._grouped_embedding_configs_per_rank:
is_weighted_per_rank = []
for grouped_config in grouped_embedding_configs:
is_weighted_per_rank.extend(grouped_config.features_weighted())
is_weighted.append(is_weighted_per_rank)
return is_weighted


class TwSparseFeaturesDist(BaseSparseFeaturesDist[KeyedJaggedTensor]):
"""
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