tf.compat.v1.reverse_sequence

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Reverses variable length slices. (deprecated arguments) (deprecated arguments)

tf.compat.v1.reverse_sequence(
    input, seq_lengths, seq_axis=None, batch_axis=None, name=None, seq_dim=None,
    batch_dim=None
)

Warning: SOME ARGUMENTS ARE DEPRECATED: (seq_dim). They will be removed in a future version. Instructions for updating: seq_dim is deprecated, use seq_axis instead

Warning: SOME ARGUMENTS ARE DEPRECATED: (batch_dim). They will be removed in a future version. Instructions for updating: batch_dim is deprecated, use batch_axis instead

This op first slices input along the dimension batch_axis, and for each slice i, reverses the first seq_lengths[i] elements along the dimension seq_axis.

The elements of seq_lengths must obey seq_lengths[i] <= input.dims[seq_dim], and seq_lengths must be a vector of length input.dims[batch_dim].

The output slice i along dimension batch_axis is then given by input slice i, with the first seq_lengths[i] slices along dimension seq_axis reversed.

Example usage:

>>> seq_lengths = [7, 2, 3, 5]
>>> input = [[1, 2, 3, 4, 5, 0, 0, 0], [1, 2, 0, 0, 0, 0, 0, 0],
...          [1, 2, 3, 4, 0, 0, 0, 0], [1, 2, 3, 4, 5, 6, 7, 8]]
>>> output = tf.reverse_sequence(input, seq_lengths, seq_axis=1, batch_axis=0)
>>> output
<tf.Tensor: shape=(4, 8), dtype=int32, numpy=
array([[0, 0, 5, 4, 3, 2, 1, 0],
       [2, 1, 0, 0, 0, 0, 0, 0],
       [3, 2, 1, 4, 0, 0, 0, 0],
       [5, 4, 3, 2, 1, 6, 7, 8]], dtype=int32)>

Args:

input: A Tensor. The input to reverse. seq_lengths: A Tensor. Must be one of the following types: int32, int64. 1-D with length input.dims(batch_dim) and max(seq_lengths) <= input.dims(seq_dim) seq_axis: An int. The dimension which is partially reversed. batch_axis: An optional int. Defaults to 0. The dimension along which reversal is performed. name: A name for the operation (optional).

Returns:

A Tensor. Has the same type as input.