9d15c9611570bd3ecab52ed924c69a60ac3b2784,tests/keras/layers/test_convolutional.py,,test_upsampling_2d,#,185

Before Change

    input_nb_row = 11
    input_nb_col = 12

    input = np.ones((nb_samples, stack_size, input_nb_row, input_nb_col))

    for length_row in [2, 3, 9]:
        for length_col in [2, 3, 9]:

After Change

    for dim_ordering in ["th", "tf"]:
        if dim_ordering == "th":
            input = np.random.rand(nb_samples, stack_size, input_nb_row,
                                   input_nb_col)
        else:  // tf
            input = np.random.rand(nb_samples, input_nb_row, input_nb_col,
                                   stack_size)

Instances