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Update mnist tutorial to use tensorboard - #5425
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| from IPython.display import clear_output | ||
| import matplotlib.pyplot as plt | ||
| from tensorboardX import SummaryWriter | ||
| import tensorboard |
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Why do we need to import tensorboard here?
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For the '%tensorboard' magic to visualize within Jupyter. Unfortunately, the within-notebook Jupyter doesn't seem to show up in the Sphinx rendering. Perhaps it's easiest no to use the within-notebook tensorboard magic and instead put in screetshots like the original jax AI stack one does.
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I added a screenshot (because the %jupyter magic doesn't survive Sphinx), but kept the use of the magic.
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This PR ports the example https://docs.jaxstack.ai/en/latest/JAX_visualizing_models_metrics.html from the Jax AI stack. It also switches the import of MNIST to huggingface datasets rather than tfd. For real world examples, we use grain over tfd anyway, so teaching users about using tfd seems unnecessary. We can also avoid the heavy weight tensorflow dependency this way.