def add_edge_padding()

in tfops.py [0:0]

• 30 lines of code
• 7 McCabe index (conditional complexity)

def add_edge_padding(x, filter_size):
    assert filter_size[0] % 2 == 1
    if filter_size[0] == 1 and filter_size[1] == 1:
        return x
    a = (filter_size[0] - 1) // 2  # vertical padding size
    b = (filter_size[1] - 1) // 2  # horizontal padding size
    if True:
        x = tf.pad(x, [[0, 0], [a, a], [b, b], [0, 0]])
        name = "_".join([str(dim) for dim in [a, b, *int_shape(x)[1:3]]])
        pads = tf.get_collection(name)
        if not pads:
            if hvd.rank() == 0:
                print("Creating pad", name)
            pad = np.zeros([1] + int_shape(x)[1:3] + [1], dtype='float32')
            pad[:, :a, :, 0] = 1.
            pad[:, -a:, :, 0] = 1.
            pad[:, :, :b, 0] = 1.
            pad[:, :, -b:, 0] = 1.
            pad = tf.convert_to_tensor(pad)
            tf.add_to_collection(name, pad)
        else:
            pad = pads[0]
        pad = tf.tile(pad, [tf.shape(x)[0], 1, 1, 1])
        x = tf.concat([x, pad], axis=3)
    else:
        pad = tf.pad(tf.zeros_like(x[:, :, :, :1]) - 1,
                     [[0, 0], [a, a], [b, b], [0, 0]]) + 1
        x = tf.pad(x, [[0, 0], [a, a], [b, b], [0, 0]])
        x = tf.concat([x, pad], axis=3)
    return x