tf.sequence_mask
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. |