ab0ff941fe4f6469730a8711d40eb32fbc9eacdf,unet3d/model.py,,compute_level_output_shape,#Any#Any#Any#Any#,81

Before Change

    if depth != 0:
        output_image_shape = np.divide(image_shape, np.multiply(pool_size, depth)).tolist()
    else:
        output_image_shape = image_shape
    return tuple([None, filters] + [int(x) for x in output_image_shape])


def get_upconv(depth, nb_filters, pool_size, image_shape, kernel_size=(2, 2, 2), strides=(2, 2, 2),

After Change

    :param depth: The number of levels down in the U-shaped model a given node is.
    :return: 5D vector of the shape of the output node 
    
    output_image_shape = np.asarray(np.divide(image_shape, np.power(pool_size, depth)), dtype=np.int32).tolist()
    return tuple([None, n_filters] + output_image_shape)


def get_up_convolution(depth, n_filters, pool_size, image_shape, kernel_size=(2, 2, 2), strides=(2, 2, 2),

Instances