Read the equation
In _get_unpad_data, this statement defines or updates seqlens_in_batch. The reduction aggregates values along the explicit source axis; preserving the axis and keep-dimension setting matters for the later broadcast.
Terms & definitions
The recovered passage does not supply a separate symbol table. Read the source context for the notation used in this version; familiar letters may carry different meanings in other builds.
How it works
Read seqlens_in_batch as the quantity being defined or updated by this relation.
Substitute the source-defined variables or recorded values and follow the displayed arithmetic and indexing exactly.
Use this version’s variable definitions and update order. The same symbol may be assigned a different meaning in another build.
Assumptions & limits
Source recovery establishes that the expression appears in this record. Its mathematical validity, implementation behavior, and interpretation must be assessed separately. See the linked source and research notes for the checks available for this version.
Original context
Read the surrounding source passage
def _get_unpad_data(attention_mask):
seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32)
indices = torch.nonzero(attention_mask.flatten(), as_tuple=False).flatten()
max_seqlen_in_batch = seqlens_in_batch.max().item()
cu_seqlens = F.pad(Exact original notation
seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32)
Related builds
Sources & provenance
seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32)
seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32)