5f94aef6685289c5451f24bcfdb2ab24e2bc87df,tests/keras/layers/convolutional_test.py,,test_conv2d_transpose,#,168

Before Change

    num_row = 5
    num_col = 6

    for batch_size in [None, num_samples]:
        for padding in _convolution_paddings:
            for strides in [(1, 1), (2, 2)]:
                if padding == "same" and strides != (1, 1):
                    continue
                layer_test(convolutional.Deconvolution2D,
                           kwargs={"filters": filters,
                                   "kernel_size": 3,
                                   "padding": padding,
                                   "strides": strides,
                                   "data_format": "channels_last"},
                           input_shape=(num_samples, num_row, num_col, stack_size),
                           fixed_batch_size=True)

                layer_test(convolutional.Deconvolution2D,
                           kwargs={"filters": filters,
                                   "kernel_size": 3,
                                   "padding": padding,
                                   "data_format": "channels_first",
                                   "kernel_regularizer": "l2",
                                   "bias_regularizer": "l2",
                                   "activity_regularizer": "l2",
                                   "kernel_constraint": "max_norm",
                                   "bias_constraint": "max_norm",
                                   "strides": strides},
                           input_shape=(num_samples, stack_size, num_row, num_col),
                           fixed_batch_size=True)


@pytest.mark.skipif(K.backend() != "tensorflow", reason="Requires TF backend")
@keras_test
def test_separable_conv_2d():
    num_samples = 2

After Change

                       input_shape=(num_samples, num_row, num_col, stack_size),
                       fixed_batch_size=True)

    layer_test(convolutional.Deconvolution2D,
               kwargs={"filters": filters,
                       "kernel_size": 3,
                       "padding": padding,
                       "data_format": "channels_first",
                       "kernel_regularizer": "l2",
                       "bias_regularizer": "l2",
                       "activity_regularizer": "l2",
                       "kernel_constraint": "max_norm",
                       "bias_constraint": "max_norm",
                       "strides": strides},
               input_shape=(num_samples, stack_size, num_row, num_col),
               fixed_batch_size=True)


@pytest.mark.skipif(K.backend() != "tensorflow", reason="Requires TF backend")
@keras_test

Instances