Available here: https://medium.com/analytics-vidhya/basics-of-using-tensorboard-in-tensorflow-1-2-b715b068ac5a
For tensorboard-examples_tf1.ipynb:
- Tested in Python 3.7.7 (pretty much any version of Python 3 should work)
- tensorflow==1.15.0
- keras==2.2.4
- keras_contrib==2.0.8
For tensorboard-examples_tf2.ipynb:
- Tested in Python 3.7.7 (pretty much any version of Python 3 should work)
- tensorflow==2.1.0
The code will likely still work with other versions of these packages, but that hasn't been tested. If you have a capable GPU, you can substitute tensorflow with tensorflow-gpu.
conda create -n using-tensorboard-tf1 -y python=3.7.7
conda activate using-tensorboard-tf1
conda install -y tensorflow==1.15.0
conda install keras==2.2.4
keras_contrib is required for the InstanceNormalization layer. Unfortunately, it isn't available directly through Anaconda, and must be installed with pip. If you wish to install it in your Anaconda environment you can use: /your/path/to/anaconda/envs/using-tensorboard-tf1/bin/pip install git+https://www.github.com/keras-team/keras-contrib.git. Given my installation of Anaconda, I use, ~/anaconda3/envs/using-tensorboard-tf1/bin/pip install git+https://www.github.com/keras-team/keras-contrib.git.
conda create -n using-tensorboard-tf2 -y python=3.7.7
conda activate using-tensorboard-tf2
conda install -y tensorflow==2.1.0