5b3f462771d7a558e24a6a42d98dc4cc1ffaa11a,dytb/evaluators/RegressorEvaluator.py,RegressorEvaluator,_error,#RegressorEvaluator#Any#Any#Any#Any#Any#,88

Before Change

        InputType.check(input_type)

        with tf.Graph().as_default():
            tf.set_random_seed(69)
            // Get images and labels from the dataset
            with tf.device("/cpu:0"):
                images, labels = dataset.inputs(
                    input_type=input_type,

After Change

            // Build a Graph that computes the predictions from the inference model.
            _, predictions = self._model.get(
                images, dataset.num_classes, train_phase=False, l2_penalty=0.0)
            loss = self.metric["fn"](predictions, labels)
            saver = tf.train.Saver(variables_to_restore())

            average_error = float("inf")

Instances