LeNetBN.py 文件源码

def get(self, images, num_classes, train_phase=False, l2_penalty=0.0):
        """ define the model with its inputs.
        Use this function to define the model in training and when exporting the model
        in the protobuf format.

        Args:
            images: model input
            num_classes: number of classes to predict
            train_phase: set it to True when defining the model, during train
            l2_penalty: float value, weight decay (l2) penalty

        Returns:
            is_training_: tf.bool placeholder enable/disable training ops at run time
            logits: the model output
        """
        is_training_ = tf.placeholder_with_default(
            False, shape=(), name="is_training_")
        # build a graph that computes the logits predictions from the images
        logits = self._inference(images, num_classes, is_training_, train_phase,
                                 l2_penalty)

        return is_training_, logits