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

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.

Answer 2

To join @solver149 answer, here is a simple example how to use TensorBoard in google colab

1.Create the Graph,ex:

a = tf.constant(3.0, dtype=tf.float32)
b = tf.constant(4.0) 
total = a + b

2. Install Tensorboard

!pip install tensorboardcolab # to install tensorboeadcolab if it does not it not exist

==> Result in my case :

Requirement already satisfied: tensorboardcolab in /usr/local/lib/python3.6/dist-packages (0.0.22)

3. Use it :)

Fist of all import TensorBoard from tensorboaedcolab (you can use import* to import everything at once), then create your tensorboeardcolab after that attach a writer to it like this :

from tensorboardcolab import * 
tbc = TensorBoardColab() # To create a tensorboardcolab object it will automatically creat a link
writer = tbc.get_writer() # To create a FileWriter
writer.add_graph(tf.get_default_graph()) # add the graph 
writer.flush()

==> Result

Using TensorFlow backend.

Wait for 8 seconds...
TensorBoard link:
http://cf426c39.ngrok.io

4.Check the given link :D

This example was token from TF guide : TensorBoard.

Answer 3

TensorBoard works with Google Colab and TensorFlow 2.0

!pip install tensorflow==2.0.0-alpha0 
%load_ext tensorboard.notebook

Answer 4

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

Answer 5

I am using tensorflow==1.15.

%load_ext tensorboard
%tensorboard --logdir /content/logs

works for me.

/content/logs

is the path of my logs in google drive.

Answer 6

According to the documentation all you need to do is this:

%load_ext tensorboard
!rm -rf ./logs/ #to delete previous runs
%tensorboard --logdir logs/
tensorboard = TensorBoard(log_dir="./logs")

And just call it in the fit method:

model.fit(X_train, y_train, epochs = 1000,
         callbacks=[tensorboard], validation_data=(X_test, y_test))

And that should give you something like this: