9aed521e6650384533f69d7b46c0210b45ae9391,keras/backend/tensorflow_backend.py,,spatial_3d_padding,#Any#Any#Any#,2250

Before Change

    assert len(padding[2]) == 2
    data_format = normalize_data_format(data_format)

    if data_format == "channels_first":
        pattern = [
            [0, 0],
            [0, 0],
            [padding[0][0], padding[0][1]],
            [padding[1][0], padding[1][1]],
            [padding[2][0], padding[2][1]]
        ]
    else:
        pattern = [
            [0, 0],
            [padding[0][0], padding[0][1]],
            [padding[1][0], padding[1][1]],
            [padding[2][0], padding[2][1]],
            [0, 0]
        ]
    return tf.pad(x, pattern)


def stack(x, axis=0):

After Change

    assert len(padding[2]) == 2
    data_format = normalize_data_format(data_format)

    pattern = [
        [0, 0],
        [padding[0][0], padding[0][1]],
        [padding[1][0], padding[1][1]],
        [padding[2][0], padding[2][1]],
        [0, 0]
    ]
    pattern = transpose_shape(pattern, data_format, spatial_axes=(1, 2, 3))

    return tf.pad(x, pattern)

Instances