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⚡️ Speed up method ClapTextEmbeddings.create_position_ids_from_input_ids by 22% #871

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⚡️ Speed up method ClapTextEmbeddings.create_position_ids_from_input_ids by 22% #871

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7 changes: 5 additions & 2 deletions src/transformers/models/clap/modeling_clap.py
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Expand Up @@ -1043,8 +1043,11 @@ def create_position_ids_from_input_ids(input_ids, padding_idx, past_key_values_l
Returns: torch.Tensor
"""
# The series of casts and type-conversions here are carefully balanced to both work with ONNX export and XLA.
mask = input_ids.ne(padding_idx).int()
incremental_indices = (torch.cumsum(mask, dim=1).type_as(mask) + past_key_values_length) * mask
mask = input_ids.ne(padding_idx)
incremental_indices = torch.cumsum(mask, dim=1)
if past_key_values_length != 0:
incremental_indices = incremental_indices + past_key_values_length
incremental_indices = incremental_indices * mask
return incremental_indices.long() + padding_idx


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