tf.sparse.fill_empty_rows | TensorFlow v2.16.1 (original) (raw)

tf.sparse.fill_empty_rows

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Fills empty rows in the input 2-D SparseTensor with a default value.

Compat aliases for migration

tf.sparse.fill_empty_rows(
    sp_input, default_value, name=None
)

This op adds entries with the specified default_value at index[row, 0] for any row in the input that does not already have a value.

For example, suppose sp_input has shape [5, 6] and non-empty values:

[0, 1]: a
[0, 3]: b
[2, 0]: c
[3, 1]: d

Rows 1 and 4 are empty, so the output will be of shape [5, 6] with values:

[0, 1]: a
[0, 3]: b
[1, 0]: default_value
[2, 0]: c
[3, 1]: d
[4, 0]: default_value

Note that the input may have empty columns at the end, with no effect on this op.

The output SparseTensor will be in row-major order and will have the same shape as the input.

This op also returns an indicator vector such that

empty_row_indicator[i] = True iff row i was an empty row.

Args
sp_input	A SparseTensor with shape [N, M].
default_value	The value to fill for empty rows, with the same type assp_input.
name	A name prefix for the returned tensors (optional)

Returns
sp_ordered_output	A SparseTensor with shape [N, M], and with all empty rows filled in with default_value.
empty_row_indicator	A bool vector of length N indicating whether each input row was empty.

Raises
TypeError	If sp_input is not a SparseTensor.