def METHOD_NAME(raw_features):
    raw_features = tf.expand_dims(raw_features, axis=0)
    transformed_features = model.feature_mapper(raw_features)
    outputs = model(transformed_features)
    outputs = tf.squeeze(outputs, axis=0)
    outputs = tf.cast(tf.greater(outputs, 0.5), tf.int64)
    decoded_outputs = model.label_inverse_lookup_layer(outputs)
    return tf.squeeze(decoded_outputs, axis=0)