Update Tensorboard use
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Nicola Demo
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tutorials/tutorial1/tutorial.py
vendored
8
tutorials/tutorial1/tutorial.py
vendored
@@ -261,13 +261,11 @@ plt.legend()
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# The solution is overlapped with the actual one, and they are barely indistinguishable. We can also take a look at the loss using `TensorBoard`:
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# In[10]:
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# In[ ]:
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# Load the TensorBoard extension
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get_ipython().run_line_magic('load_ext', 'tensorboard')
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# Show saved losses
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get_ipython().run_line_magic('tensorboard', "--logdir 'tutorial_logs'")
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print('\nTo load TensorBoard run load_ext tensorboard on your terminal')
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print("To visualize the loss you can run tensorboard --logdir 'tutorial_logs' on your terminal\n")
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# As we can see the loss has not reached a minimum, suggesting that we could train for longer! Alternatively, we can also take look at the loss using callbacks. Here we use `MetricTracker` from `pina.callback`:
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