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handle empty (keys) sparse features case #1883

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handle empty (keys) sparse features case #1883

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2 changes: 1 addition & 1 deletion torchrec/sparse/jagged_tensor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -786,7 +786,7 @@ def _maybe_compute_length_per_key(
values: Optional[torch.Tensor],
) -> List[int]:
if length_per_key is None:
if values is not None and values.is_meta:
if len(keys) and values is not None and values.is_meta:
# create dummy lengths per key when on meta device
total_length = values.numel()
_length = [total_length // len(keys)] * len(keys)
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7 changes: 7 additions & 0 deletions torchrec/sparse/tests/test_jagged_tensor.py
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Expand Up @@ -1836,6 +1836,13 @@ def test_meta_device_compatibility(self) -> None:
keys=keys, values=values, weights=weights, offsets=offsets
)

# test empty keys case
kjt = KeyedJaggedTensor.from_lengths_sync(
keys=[],
values=torch.tensor([], device=torch.device("meta")),
lengths=torch.tensor([], device=torch.device("meta")),
)


class TestKeyedJaggedTensorScripting(unittest.TestCase):
def test_scriptable_forward(self) -> None:
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