def load_data()

in autoencoder.py [0:0]

• 25 lines of code
• 4 McCabe index (conditional complexity)

def load_data(configs, path):
    data_configs = json.loads(configs["data"])

    if "shapes" and "2k-classes" in path:
        data = datasets.SimpleShapes(
            configs["batch_size"],
            n_rotations=data_configs["n_rotations"],
            n_x_translations=data_configs["n_x_translations"],
            n_y_translations=data_configs["n_y_translations"],
            n_classes=2000,
            seed=0,
        )
    elif "mnist" in path:
        data = datasets.ProjectiveMNIST(
            configs["batch_size"],
            n_rotations=data_configs["n_rotations"],
            n_x_translations=data_configs["n_x_translations"],
            n_y_translations=data_configs["n_y_translations"],
            train_set_proportion=0.01,
            valid_set_proportion=0.01,
            test_set_proportion=1.0,
            seed=0,
        )
    else:
        raise ValueError("data not found")
    return data