I am training a neural network for object detection using Google Colab. I wanted to visualize the learning process but every time I try to access tensorboard, it shows me the following:
No dashboards are active for the current data set. Probable causes: - You haven’t written any data to your event files. - TensorBoard can’t find your event files.
I am not training the model locally and have configured my google drive account with the colab notebook for the training data so user hpabst's answer does not seem useful.
I also tried setting up tensorboard using ngrok but that gave me a similar output.
I made sure I am generating summary data in a log directory by creating a summary writer:
import tensorflow as tf
sess = tf.Session()
file_writer = tf.summary.FileWriter('/content/logs/my_log_dir/', sess.graph)
and followed that with
tensorboard = TensorBoard(log_dir="/content/logs/my_log_dir/",batch_size=32, write_graph=True, update_freq='epoch')
model.fit_generator(
train_generator,
steps_per_epoch=(train_data/BS),
epochs=EPOCHS,
validation_data=validation_generator,
validation_steps=(test_data/BS),
callbacks=[tensorboard, checkpoint])
and finally
tensorboard --logdir /content/logs/my_log_dir/
The event files are in place. The path to the log directory is also correct.
Like I said, I was getting the same- No active dashboards error using ngrok. I moved over to the SCALARS menu in the Tensorboard GUI and to the left, under the runs section, at the bottom, I found out that the path to the log directory was being shown as '/content/ log /my_log_dir' although everywhere in my code I had only mentioned the path as -'/content/ logs /my_log_dir'. Maybe setting up tensorboard using ngrok expects the files to be in the 'log' and not the 'logs' directory. I made the change and now it works just fine.