def train(self, images, labels):
self.steps += 1
feed_dict = {self.images: images, self.labels: labels}
if self.steps == 1:
metadata = tf.RunMetadata()
self.session.run(self.training, feed_dict, options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE), run_metadata = metadata)
self.summary_writer.add_run_metadata(metadata, 'step1')
elif self.steps % 100 == 0:
_, summary = self.session.run([self.training, self.summaries['training']], feed_dict)
self.summary_writer.add_summary(summary, self.steps)
else:
self.session.run(self.training, feed_dict)
3-mnist-run-metadata-and-histograms.py 文件源码
python
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