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