Can I use TensorBoard with Google Colab?

Question

Is there any way to use TensorBoard when training a TensorFlow model on Google Colab?

Answer 1

There is an alternative solution but we have to use TFv2.0 preview. So if you don't have problems with the migration try this:

install tfv2.0 for GPU or CPU (TPU no available yet)

CPU
tf-nightly-2.0-preview
GPU
tf-nightly-gpu-2.0-preview

%%capture
!pip install -q tf-nightly-gpu-2.0-preview
# Load the TensorBoard notebook extension
# %load_ext tensorboard.notebook # For older versions
%load_ext tensorboard

import TensorBoard as usual:

from tensorflow.keras.callbacks import TensorBoard

Clean or Create folder where to save the logs (run this lines before run the training fit())

# Clear any logs from previous runs
import time

!rm -R ./logs/ # rf
log_dir="logs/fit/{}".format(time.strftime("%Y%m%d-%H%M%S", time.gmtime()))
tensorboard = TensorBoard(log_dir=log_dir, histogram_freq=1)

Have fun with TensorBoard! :)

%tensorboard --logdir logs/fit

Here the official colab notebook and the repo on github

New TFv2.0 alpha release:

CPU
!pip install -q tensorflow==2.0.0-alpha0 GPU
!pip install -q tensorflow-gpu==2.0.0-alpha0