1a010ccffb1c80997260b9fe7cf3b7a3887b13ae,autokeras/net_combinator.py,,pad_filter,#Any#Any#Any#,36

Before Change

def pad_filter(weight, old_size, new_size):
    return np.pad(weight,
                  map(lambda x: (x, x), tuple(np.subtract(np.array(new_size), np.array(old_size)) / 2)),
                  "constant",
                  constant_values=0)


def combine_conv_weights(layer1, layer2, filter_size, n_input_channel):
    weight1, bias1 = layer1.get_weights()

After Change

def pad_filter(weight, old_size, new_size):
    pad_width = tuple(map(lambda x: (int(x), int(x)), np.subtract(np.array(new_size), np.array(old_size)) / 2))
    pad_width += ((0, 0), (0, 0))
    return np.pad(weight,
                  pad_width,
                  "constant",
                  constant_values=0)

Instances