c3a6d11e727277100b3b9a66b823b496fa3b9901,examples/atari_dqn.py,ConvNet,train_on_batch,#ConvNet#Any#Any#,168

Before Change

            return self.all_q.predict(x, **fit_params)

    def train_on_batch(self, x, y, **fit_params):
        self.q.train_on_batch(x, y, **fit_params)

    def set_weights(self, w):
        self.q.set_weights(w)

After Change

            return self.all_q.predict(x, **fit_params)

    def train_on_batch(self, x, y, **fit_params):
        loss = self.q.train_on_batch(x, y, **fit_params)
        summary = tf.Summary(value=[tf.Summary.Value(tag="loss",
                                                     simple_value=loss), ])
        self.writer.add_summary(summary)

Instances