import tensorflow as tf

            gan_train_ops.generator_train_op,
            global_step.assign_add(1))

    if params['use_tpu']:
        # TPU version of EstimatorSpec
        return tf.contrib.tpu.TPUEstimatorSpec(
            mode=mode,
            predictions=predictions,
            loss=loss,
            train_op=train_op,)
    else:
        return tf.estimator.EstimatorSpec(
            mode=mode,
            predictions=predictions,
            loss=loss,
            train_op=train_op,)


def train_input_fn(params={}):
    # make some fake noise
    data_size = 100
    noise_tensor = tf.random_normal((data_size, INPUT_DIM))
