d6c1b86594ef9a97e9f503547ab6567f89508486,tests/integration_tests/test_experiment.py,,test_image_resizing_num_channel_handling,#Any#,401

Before Change

    df1 = pd.read_csv(rel_path)

    input_features_template = Template(
        "[{type: text, name: random_text, vocab_size: 100,"
        " max_len: 10, encoder: stacked_cnn}, {type: numerical,"
        " name: random_number}, "
        "{type: image, name: random_image, preprocessing: {width: 8,"
        " in_memory: ${in_memory}, height: 8, num_channels: 1},"
        " encoder: ${encoder}, fc_size: 32, "
        " resnet_size: 8, destination_folder: ${folder}}]")

    input_features = input_features_template.substitute(
        encoder="resnet",
        folder=image_dest_folder,
        in_memory="true",
    )
    rel_path = generate_data(
        input_features, output_features, csv_filename, num_examples=100
    )
    df2 = pd.read_csv(rel_path)

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=8,
            num_filters=8
        ),
        text_feature(encoder="embed", min_len=1),
        numerical_feature()
    ]
    output_features = [binary_feature(), numerical_feature()]
    rel_path = generate_data(
        input_features, output_features, csv_filename, num_examples=50
    )

Instances