How do I use the Tensorboard callback of Keras?

Question

I have built a neural network with Keras. I would visualize its data by Tensorboard, therefore I have utilized:

keras.callbacks.TensorBoard(log_dir='/Graph', histogram_freq=0,
                            write_graph=True, write_images=True)

as explained in keras.io. When I run the callback I get <keras.callbacks.TensorBoard at 0x7f9abb3898>, but I don't get any file in my folder "Graph". Is there something wrong in how I have used this callback?

Answer 1

keras.callbacks.TensorBoard(log_dir='./Graph', histogram_freq=0,  
          write_graph=True, write_images=True)

This line creates a Callback Tensorboard object, you should capture that object and give it to the fit function of your model.

tbCallBack = keras.callbacks.TensorBoard(log_dir='./Graph', histogram_freq=0, write_graph=True, write_images=True)
...
model.fit(...inputs and parameters..., callbacks=[tbCallBack])

This way you gave your callback object to the function. It will be run during the training and will output files that can be used with tensorboard.

If you want to visualize the files created during training, run in your terminal

tensorboard --logdir path_to_current_dir/Graph 

Hope this helps !

Answer 2

This is how you use the TensorBoard callback:

from keras.callbacks import TensorBoard

tensorboard = TensorBoard(log_dir='./logs', histogram_freq=0,
                          write_graph=True, write_images=False)
# define model
model.fit(X_train, Y_train,
          batch_size=batch_size,
          epochs=nb_epoch,
          validation_data=(X_test, Y_test),
          shuffle=True,
          callbacks=[tensorboard])

Answer 3

Change

keras.callbacks.TensorBoard(log_dir='/Graph', histogram_freq=0,  
          write_graph=True, write_images=True)

to

tbCallBack = keras.callbacks.TensorBoard(log_dir='Graph', histogram_freq=0,  
          write_graph=True, write_images=True)

and set your model

tbCallback.set_model(model)

Run in your terminal

tensorboard  --logdir Graph/

Answer 4

If you are working with Keras library and want to use tensorboard to print your graphs of accuracy and other variables, Then below are the steps to follow.

step 1: Initialize the keras callback library to import tensorboard by using below command

from keras.callbacks import TensorBoard

step 2: Include the below command in your program just before "model.fit()" command.

tensor_board = TensorBoard(log_dir='./Graph', histogram_freq=0, write_graph=True, write_images=True)

Note: Use "./graph". It will generate the graph folder in your current working directory, avoid using "/graph".

step 3: Include Tensorboard callback in "model.fit()".The sample is given below.

model.fit(X_train,y_train, batch_size=batch_size, epochs=nb_epoch, verbose=1, validation_split=0.2,callbacks=[tensor_board])

step 4 : Run your code and check whether your graph folder is there in your working directory. if the above codes work correctly you will have "Graph" folder in your working directory.

step 5 : Open Terminal in your working directory and type the command below.

tensorboard --logdir ./Graph

step 6: Now open your web browser and enter the address below.

http://localhost:6006

After entering, the Tensorbaord page will open where you can see your graphs of different variables.