tensorlayer/prepro.py
def sequences_get_mask(sequences, pad_val=0):
    """Return mask for sequences.

    Parameters
    -----------
    sequences : list of list of int
        All sequences where each row is a sequence.
    pad_val : int
        The pad value.

    Returns
    ----------
    list of list of int
        The mask.

    Examples
    ---------
    >>> sentences_ids = [[4, 0, 5, 3, 0, 0],
    ...                  [5, 3, 9, 4, 9, 0]]
    >>> mask = sequences_get_mask(sentences_ids, pad_val=0)
    [[1 1 1 1 0 0]
     [1 1 1 1 1 0]]

    """
    mask = np.ones_like(sequences)
    for i, seq in enumerate(sequences):
        for i_w in reversed(range(len(seq))):
            if seq[i_w] == pad_val:
                mask[i, i_w] = 0
            else:
                break  # <-- exit the for loop, prepcess next sequence
    return mask
def sequences_get_mask(sequences, pad_val=0):
    """Return mask for sequences.

    Parameters
    -----------
    sequences : list of list of int
        All sequences where each row is a sequence.
    pad_val : int
        The pad value.

    Returns
    ----------
    list of list of int
        The mask.

    Examples
    ---------
    >>> sentences_ids = [[4, 0, 5, 3, 0, 0],
    ...                  [5, 3, 9, 4, 9, 0]]
    >>> mask = sequences_get_mask(sentences_ids, pad_val=0)
    [[1 1 1 1 0 0]
     [1 1 1 1 1 0]]

    """
    mask = np.ones_like(sequences)
    for i, seq in enumerate(sequences):
        for i_w in reversed(range(len(seq))):
            if seq[i_w] == pad_val:
                mask[i, i_w] = 0
            else:
                break  # <-- exit the for loop, prepcess next sequence
    return mask
def sequences_get_mask ( sequences , pad_val = 0 ) : mask = np . ones_like ( sequences ) for i , seq in enumerate ( sequences ) : for i_w in reversed ( range ( len ( seq ) ) ) : if seq [ i_w ] == pad_val : mask [ i , i_w ] = 0 else : break # <-- exit the for loop, prepcess next sequence return mask
Return mask for sequences.

    Parameters
    -----------
    sequences : list of list of int
        All sequences where each row is a sequence.
    pad_val : int
        The pad value.

    Returns
    ----------
    list of list of int
        The mask.

    Examples
    ---------
    >>> sentences_ids = [[4, 0, 5, 3, 0, 0],
    ...                  [5, 3, 9, 4, 9, 0]]
    >>> mask = sequences_get_mask(sentences_ids, pad_val=0)
    [[1 1 1 1 0 0]
     [1 1 1 1 1 0]]
Return mask for sequences .