human
Solve the following python programming problem given the following code:
# Creating my own input function for a given color
def get_input_fn(color):
  def input_fn():
    seq_len = len(color)
    # color is now a sequence of chars
    color_split = tf.string_split([color], '').values

    # creating dataset
    dataset = tf.contrib.data.Dataset.from_tensors((color_split))
    # generating a batch, so it has the right rank
    dataset = dataset.batch(1)

    # creating iterator
    color_name = dataset.make_one_shot_iterator().get_next()

    features = {
        COLOR_NAME_KEY: color_name,
        SEQUENCE_LENGTH_KEY: [seq_len]
    }

    # we're just predicting, so the label can be None
    # if you're training make sure to return a label
    return features, None
  return input_fn

# Making Predictions
print('Colorbot is ready to generate colors!')

EXIT_COMMAND = '<exit>'
while True:
  color_name = raw_input('give me a color name (or %s): ' % (EXIT_COMMAND))
  if color_name == EXIT_COMMAND:
    break

  print('Generating color...')
  preds = estimator.predict(input_fn=get_input_fn(color_name))
  for p, name in zip(preds, [color_name]):
    color = tuple(map(int, p * 255))
    _plot_rgb(p)
Given the above code, generate some markdown instructions for it.
assistant
#Here is the Python code you requested.

This is hacky code from "play_colorbot.py" to interactively make predictions