(self, real_x, batch_size=None)
return pred
Classify given dataspace points `real_x`.

    Args:
      real_x: A numpy array of dataspace points.
      batch_size: (Optional) a integer to indication batch size for computation
          which is useful if the classification requires lots of GPU memory.

    Returns:
      A numpy array, the prediction from classifier.
Classify given dataspace points `real_x`.
Classify given dataspace points real_x .
def classify(self, real_x, batch_size=None):
    """Classify given dataspace points `real_x`.

    Args:
      real_x: A numpy array of dataspace points.
      batch_size: (Optional) a integer to indication batch size for computation
          which is useful if the classification requires lots of GPU memory.

    Returns:
      A numpy array, the prediction from classifier.
    """
    m = self.m
    op_target = m.pred_classifier
    op_feed = m.x
    arr_feed = real_x
    batch_size = batch_size or self.DEFAULT_BATCH_SIZE
    pred = run_with_batch(self.sess, op_target, op_feed, arr_feed, batch_size)
    pred = np.argmax(pred, axis=-1)
    return pred
def classify ( self , real_x , batch_size = None ) : m = self . m op_target = m . pred_classifier op_feed = m . x arr_feed = real_x batch_size = batch_size or self . DEFAULT_BATCH_SIZE pred = run_with_batch ( self . sess , op_target , op_feed , arr_feed , batch_size ) pred = np . argmax ( pred , axis = - 1 ) return pred