Convert the given value to Feature if necessary.

def to_feature(value):
  """Convert the given value to Feature if necessary."""
  if isinstance(value, FeatureConnector):
    return value
  elif utils.is_dtype(value):  # tf.int32, tf.string,...
    return Tensor(shape=(), dtype=tf.as_dtype(value))
  elif isinstance(value, dict):
    return FeaturesDict(value)
  else:
    raise ValueError('Feature not supported: {}'.format(value))