test_convolutional.py 文件源码

def test_deconvolution_2d():
    nb_samples = 2
    nb_filter = 2
    stack_size = 3
    nb_row = 10
    nb_col = 6

    for border_mode in _convolution_border_modes:
        for subsample in [(1, 1), (2, 2)]:
            if border_mode == 'same' and subsample != (1, 1):
                continue

            rows = conv_input_length(nb_row, 3, border_mode, subsample[0])
            cols = conv_input_length(nb_col, 3, border_mode, subsample[1])
            layer_test(convolutional.Deconvolution2D,
                       kwargs={'nb_filter': nb_filter,
                               'nb_row': 3,
                               'nb_col': 3,
                               'output_shape': (nb_samples, nb_filter, rows, cols),
                               'border_mode': border_mode,
                               'subsample': subsample,
                               'dim_ordering': 'th'},
                       input_shape=(nb_samples, stack_size, nb_row, nb_col),
                       fixed_batch_size=True)

            layer_test(convolutional.Deconvolution2D,
                       kwargs={'nb_filter': nb_filter,
                               'nb_row': 3,
                               'nb_col': 3,
                               'output_shape': (nb_samples, nb_filter, rows, cols),
                               'border_mode': border_mode,
                               'dim_ordering': 'th',
                               'W_regularizer': 'l2',
                               'b_regularizer': 'l2',
                               'activity_regularizer': 'activity_l2',
                               'subsample': subsample},
                       input_shape=(nb_samples, stack_size, nb_row, nb_col),
                       fixed_batch_size=True)