Batch API

class relational_transformers.RelationalBatch(node_idxs, f2p_nbr_idxs, col_name_idxs, table_name_idxs, is_padding, sem_types, is_targets, number_values, datetime_values, boolean_values, text_values, col_name_values)

A padded batch of relational cells.

This is the shared boundary used by PyTorch, Triton, ONNX, and RelativeDB. Integer tensors describe topology; value tensors contain already encoded model inputs. Boolean masks use True for padding/targets.

Parameters:

  • node_idxs (Tensor)

  • f2p_nbr_idxs (Tensor)

  • col_name_idxs (Tensor)

  • table_name_idxs (Tensor)

  • is_padding (Tensor)

  • sem_types (Tensor)

  • is_targets (Tensor)

  • number_values (Tensor)

  • datetime_values (Tensor)

  • boolean_values (Tensor)

  • text_values (Tensor)

  • col_name_values (Tensor)

ablate(cells)

Return a new batch with the same cell positions padded out.

Positions remain stable, so node and parent indices require no remap. Target cells may not be ablated.

Parameters:

cells (Sequence[int])

Return type:

RelationalBatch

classmethod from_text_cells(cells, *, target, node_idxs=None, parents=None, table_idxs=None)

Build one batch row from [column_embedding, value_embedding] cells.

cells has shape [S, 2*d_text]. This convenience path is useful for all-text examples; typed production callers should construct the full batch so scalar and datetime channels retain their semantics.

Parameters:

  • cells (ndarray | Tensor)

  • target (int | Sequence[int])

  • node_idxs (Sequence[int] | None)

  • parents (Mapping[int, Sequence[int]] | None)

  • table_idxs (Sequence[int] | None)

Return type:

RelationalBatch