5e797436c3defd2d863ac1ffab11c48dbd42588e,tests/keras/backend/backend_test.py,TestBackend,test_conv3d,#TestBackend#,845

Before Change

                                           data_format="channels_first")

        // test in data_format = channels_last
        input_shape = (1, 2, 2, 2, 1)
        kernel_shape = (2, 2, 2, 1, 1)
        check_two_tensor_operation("conv3d", input_shape, kernel_shape,
                                   BACKENDS, cntk_dynamicity=True,
                                   data_format="channels_last")

        xval = np.random.random(input_shape)
        kernel_val = np.random.random(kernel_shape) - 0.5
        // Test invalid use cases
        for k in BACKENDS:
            with pytest.raises(ValueError):

After Change

        // TF input shape: (samples, conv_dim1, conv_dim2, conv_dim3, input_depth)
        // TH kernel shape: (depth, input_depth, x, y, z)
        // TF kernel shape: (x, y, z, input_depth, depth)
        for (input_shape, kernel_shape, data_format) in [
                ((2, 3, 4, 5, 4), (2, 2, 2, 3, 4), "channels_first"),
                ((2, 3, 5, 4, 6), (3, 2, 4, 3, 4), "channels_first"),
                ((1, 2, 2, 2, 1), (2, 2, 2, 1, 1), "channels_last")]:
            check_two_tensor_operation("conv3d", input_shape, kernel_shape,
                                       BACKENDS, cntk_dynamicity=True,
                                       data_format=data_format)

    def test_separable_conv2d(self):
        for (input_shape, data_format) in [
                ((2, 3, 4, 5), "channels_first"),
                ((2, 3, 5, 6), "channels_first"),

Instances