Can I Use TensorBoard With Google Colab?

Answer :

EDIT: You probably want to give the official %tensorboard magic a go, available from TensorFlow 1.13 onward.

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Prior to the existence of the %tensorboard magic, the standard way to achieve this was to proxy network traffic to the Colab VM using ngrok. A Colab example can be found here.

These are the steps (the code snippets represent cells of type "code" in colab):

1. Get TensorBoard running in the background.
   Inspired by this answer.

   LOG_DIR = '/tmp/log' get_ipython().system_raw(     'tensorboard --logdir {} --host 0.0.0.0 --port 6006 &'     .format(LOG_DIR) ) 

2. Download and unzip ngrok.
   Replace the link passed to wget with the correct download link for your OS.

   ! wget https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip ! unzip ngrok-stable-linux-amd64.zip 

3. Launch ngrok background process...

   get_ipython().system_raw('./ngrok http 6006 &') 

   ...and retrieve public url. Source

   ! curl -s http://localhost:4040/api/tunnels | python3 -c \     "import sys, json; print(json.load(sys.stdin)['tunnels'][0]['public_url'])" 

Many of the answers here are now obsolete. So will be mine I'm sure in a few weeks. But at the time of this writing all I had to do is run these lines of code from colab. And tensorboard opened up just fine.

%load_ext tensorboard %tensorboard --logdir logs 

Here's an easier way to do the same ngrok tunneling method on Google Colab.

!pip install tensorboardcolab 

then,

from tensorboardcolab import TensorBoardColab, TensorBoardColabCallback  tbc=TensorBoardColab() 

Assuming you are using Keras:

model.fit(......,callbacks=[TensorBoardColabCallback(tbc)]) 

You can read the original post here.