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tf.summary.scalar("training_loss", m_loss.numpy(), step=int(ckpt.step)) | tf.summary.scalar("training_loss", m_loss.numpy(), step=int(ckpt.step)) | ||
</syntaxhighlight> | </syntaxhighlight> | ||
==PyTorch== | |||
PyTorch also supports output tensorboard logs. | |||
See [https://pytorch.org/docs/stable/tensorboard.html https://pytorch.org/docs/stable/tensorboard.html]. | |||
There is also [https://github.com/lanpa/tensorboardX lanpa/tensorboardX] but I haven't tried it. | |||
==Resources== | ==Resources== | ||
* [https://www.tensorflow.org/tensorboard/get_started Getting started with TensorBoard] | * [https://www.tensorflow.org/tensorboard/get_started Getting started with TensorBoard] | ||
* [https://www.youtube.com/watch?v=eBbEDRsCmv4 Hands-on TensorBoard (TensorFlow Dev Summit 2017)] | * [https://www.youtube.com/watch?v=eBbEDRsCmv4 Hands-on TensorBoard (TensorFlow Dev Summit 2017)] |