d6c1b86594ef9a97e9f503547ab6567f89508486,tests/integration_tests/test_experiment.py,,test_experiment_image_inputs,#Any#,177

Before Change

    run_experiment(input_features, output_features, rel_path)

    // Delete the temporary data created
    all_images = glob.glob(os.path.join(image_dest_folder, "*.jpg"))
    for im in all_images:
        os.remove(im)

    os.rmdir(image_dest_folder)


def test_experiment_tied_weights(csv_filename):

After Change

    image_dest_folder = os.path.join(os.getcwd(), "generated_images")

    // Resnet encoder
    input_features = [
        image_feature(
            folder=image_dest_folder,
            encoder="resnet",
            preprocessing={
                "in_memory": True,
                "height": 8,
                "width": 8,
                "num_channels": 3
            },
            fc_size=16,
            num_filters=8
        ),
        text_feature(encoder="embed", min_len=1),
        numerical_feature()
    ]
    output_features = [
        categorical_feature(vocab_size=2, reduce_input="sum"),
        numerical_feature()
    ]

    rel_path = generate_data(input_features, output_features, csv_filename)
    run_experiment(input_features, output_features, data_csv=rel_path)

    // Stacked CNN encoder
    input_features[0]["encoder"] = "stacked_cnn"
    rel_path = generate_data(input_features, output_features, csv_filename)
    run_experiment(input_features, output_features, data_csv=rel_path)

Instances