text: import logging
  from functools import partial
  
  import tensorflow as tf
  
  from inputs import gpt2_pred_input
  from models.gpt2 import encoder
  
  
  # Takes in the user supplied text and generates output texts. Outputs to log/console and a file
  def gpt2_predict(network, text, params):
      logger = logging.getLogger('tensorflow')
  
      enc = encoder.get_encoder(params["encoder_path"])
      predictions = network.predict(input_fn=partial(gpt2_pred_input, text=text))
  
      with tf.io.gfile.GFile(params["predict_path"], "a") as f:
          for i, p in enumerate(predictions):
              p = p["tokens"]
              text = enc.decode(p)
              f.write("=" * 40 + " SAMPLE " + str(i) + " " + "=" * 40 + "\n")
              f.write(text)
              f.write("\n" + "=" * 80 + "\n")
  
              logger.info("=" * 40 + " SAMPLE " + str(i) + " " + "=" * 40 + "\n")
              logger.info(text)
              logger.info("\n" + "=" * 80 + "\n")
  