tf.sequence

TensorFlow 1 version

View source on GitHub

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.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.

TensorFlow

tf

tf.audio

tf.autograph

tf.bitwise

tf.compat

tf.config

tf.data

tf.debugging

tf.distribute

tf.dtypes

tf.errors

tf.estimator

tf.experimental

tf.feature_column

tf.graph_util

tf.image

tf.initializers

tf.io

tf.keras

tf.linalg

tf.lite

tf.lookup

tf.losses

tf.math

tf.metrics

tf.nest

tf.nn

tf.optimizers

tf.quantization

tf.queue

tf.ragged

tf.random

tf.raw_ops

tf.saved_model

tf.sets

tf.signal

tf.sparse

tf.strings

tf.summary

tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

tf.xla

tf / sequence_mask

View aliases

Examples:

Args

Returns

Raises