TensorBoard is a suite of visualization tools very very useful to debug and optimize deep nets.
Looking inside the fastai repo I found this nice callback file tensorboard.py. I assume it will be introduced sometime in the next lessons, but if you want to start playing with it you need just few steps:
- Install and run Tensorboard:
pip install tensorflow==2.0.0-alpha0 pip install tensorboard conda install -c conda-forge tensorboardx tensorboard --logdir **path-to-your-log**/
Add these few lines into your notebook:
from fastai.callbacks.tensorboard import *
tboard_path = Path('**path-to-your-log**')
learn.callback_fns.append(partial(LearnerTensorboardWriter, base_dir=tboard_path, name='Smthng'))
Fit your model and see the results in tesorboard:
Super Easy!! Thanks again to the nice callback system we can now have traces of our training.
I am sure Jeremy will introduce it more deeply in the future but in the meantime why don’t you try