tf.sequence_mask

Returns a mask tensor representing the first N positions of each cell.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.sequence_mask, `tf.compat.v2.sequence_mask`

tf.sequence_mask(
    lengths, maxlen=None, dtype=tf.dtypes.bool, name=None
)

If lengths has shape [d_1, d_2, ..., d_n] the resulting tensor mask has dtype dtype and shape [d_1, d_2, ..., d_n, maxlen], with

mask[i_1, i_2, ..., i_n, j] = (j < lengths[i_1, i_2, ..., i_n])

Examples:

tf.sequence_mask([1, 3, 2], 5)  # [[True, False, False, False, False],
                                #  [True, True, True, False, False],
                                #  [True, True, False, False, False]]

tf.sequence_mask([[1, 3],[2,0]])  # [[[True, False, False],
                                  #   [True, True, True]],
                                  #  [[True, True, False],
                                  #   [False, False, False]]]

Args
lengths	integer tensor, all its values <= maxlen.
maxlen	scalar integer tensor, size of last dimension of returned tensor. Default is the maximum value in lengths.
dtype	output type of the resulting tensor.
name	name of the op.

Returns
A mask tensor of shape lengths.shape + (maxlen,), cast to specified dtype.

Raises
ValueError	if maxlen is not a scalar.