tensorlayer/layers/recurrent.py
def retrieve_seq_length_op2(data):
    """An op to compute the length of a sequence, from input shape of [batch_size, n_step(max)],
    it can be used when the features of padding (on right hand side) are all zeros.

    Parameters
    -----------
    data : tensor
        [batch_size, n_step(max)] with zero padding on right hand side.

    Examples
    --------
    >>> data = [[1,2,0,0,0],
    ...         [1,2,3,0,0],
    ...         [1,2,6,1,0]]
    >>> o = retrieve_seq_length_op2(data)
    >>> sess = tf.InteractiveSession()
    >>> tl.layers.initialize_global_variables(sess)
    >>> print(o.eval())
    [2 3 4]

    """
    return tf.reduce_sum(tf.cast(tf.greater(data, tf.zeros_like(data)), tf.int32), 1)
def retrieve_seq_length_op2(data):
    """An op to compute the length of a sequence, from input shape of [batch_size, n_step(max)],
    it can be used when the features of padding (on right hand side) are all zeros.

    Parameters
    -----------
    data : tensor
        [batch_size, n_step(max)] with zero padding on right hand side.

    Examples
    --------
    >>> data = [[1,2,0,0,0],
    ...         [1,2,3,0,0],
    ...         [1,2,6,1,0]]
    >>> o = retrieve_seq_length_op2(data)
    >>> sess = tf.InteractiveSession()
    >>> tl.layers.initialize_global_variables(sess)
    >>> print(o.eval())
    [2 3 4]

    """
    return tf.reduce_sum(tf.cast(tf.greater(data, tf.zeros_like(data)), tf.int32), 1)
def retrieve_seq_length_op2 ( data ) : return tf . reduce_sum ( tf . cast ( tf . greater ( data , tf . zeros_like ( data ) ) , tf . int32 ) , 1 )
An op to compute the length of a sequence, from input shape of [batch_size, n_step(max)],
    it can be used when the features of padding (on right hand side) are all zeros.

    Parameters
    -----------
    data : tensor
        [batch_size, n_step(max)] with zero padding on right hand side.

    Examples
    --------
    >>> data = [[1,2,0,0,0],
    ...         [1,2,3,0,0],
    ...         [1,2,6,1,0]]
    >>> o = retrieve_seq_length_op2(data)
    >>> sess = tf.InteractiveSession()
    >>> tl.layers.initialize_global_variables(sess)
    >>> print(o.eval())
    [2 3 4]
An op to compute the length of a sequence from input shape of [ batch_size n_step ( max ) ] it can be used when the features of padding ( on right hand side ) are all zeros .