Generate a string that contains a command with all necessary
       parameters to train the model.

def generate_training_command(model_folder):
    """Generate a string that contains a command with all necessary
       parameters to train the model."""
    update_if_outdated(model_folder)
    model_description_file = os.path.join(model_folder, "info.yml")
    # Read the model description file
    with open(model_description_file, 'r') as ymlfile:
        model_description = yaml.load(ymlfile)

    # Get the data paths (hdf5 files)
    project_root = utils.get_project_root()
    data = {}
    data['training'] = os.path.join(project_root,
                                    model_description["data-source"],
                                    "traindata.hdf5")
    data['testing'] = os.path.join(project_root,
                                   model_description["data-source"],
                                   "testdata.hdf5")
    data['validating'] = os.path.join(project_root,
                                      model_description["data-source"],
                                      "validdata.hdf5")

    # Get latest model file
    basename = "model"
    latest_model = utils.get_latest_working_model(model_folder)

    if latest_model == "":
        logging.error("There is no model with basename '%s'.", basename)
        return None
    else:
        logging.info("Model '%s' found.", latest_model)
        i = int(latest_model.split("-")[-1].split(".")[0])
        model_src = os.path.join(model_folder, "%s-%i.json" % (basename, i))
        model_target = os.path.join(model_folder,
                                    "%s-%i.json" % (basename, i+1))

    # generate the training command
    training = model_description['training']
    training = training.replace("{{testing}}", data['testing'])
    training = training.replace("{{training}}", data['training'])
    training = training.replace("{{validation}}", data['validating'])
    training = training.replace("{{src_model}}", model_src)
    training = training.replace("{{target_model}}", model_target)
    training = training.replace("{{nntoolkit}}", utils.get_nntoolkit())
    return training