test_convolutional.py 文件源码

def test_cropping_2d():
    nb_samples = 2
    stack_size = 2
    input_len_dim1 = 8
    input_len_dim2 = 8
    cropping = ((2, 2), (3, 3))
    dim_ordering = K.image_dim_ordering()

    if dim_ordering == 'th':
        input = np.random.rand(nb_samples, stack_size,
                               input_len_dim1, input_len_dim2)
    else:
        input = np.random.rand(nb_samples,
                               input_len_dim1, input_len_dim2,
                               stack_size)
    # basic test
    layer_test(convolutional.Cropping2D,
               kwargs={'cropping': cropping,
                       'dim_ordering': dim_ordering},
               input_shape=input.shape)
    # correctness test
    layer = convolutional.Cropping2D(cropping=cropping,
                                     dim_ordering=dim_ordering)
    layer.build(input.shape)
    output = layer(K.variable(input))
    np_output = K.eval(output)
    # compare with numpy
    if dim_ordering == 'th':
        expected_out = input[:,
                             :,
                             cropping[0][0]: -cropping[0][1],
                             cropping[1][0]: -cropping[1][1]]
    else:
        expected_out = input[:,
                             cropping[0][0]: -cropping[0][1],
                             cropping[1][0]: -cropping[1][1],
                             :]
    assert_allclose(np_output, expected_out)