if logdir is not None:
training_stats.report(
tensor_values["policy_cost"],
tensor_values["value_cost"],
tensor_values["l2_cost"],
tensor_values["combined_cost"])
if i % 100 == 0 and logdir is not None:
After Change
train_tensors = train_ops(
input_tensors, output_tensors, **self.hparams)
weight_summary_op = logging_ops()
weight_tensors = tf.trainable_variables()
self.initialize_weights(init_from)
if logdir is not None:
training_stats = StatisticsCollector()
logger = tf.summary.FileWriter(logdir, self.sess.graph)