I'm running a CNN Deep Learning Classification model on colab pro+. However, without reason, session is interrupted, and no log is presented in the app.log file.
enter image description here
As can be seen in the image, It's 30th november and the last entry in the app.log was yesterday. The program has just stopped running without reason.
Can you help me?
I've sent a question to colab github acccount.
Related
Colab unexpectedly gets stuck and hangs after executing input() function (Python), e.g.: input("What is your name? "). see attached file. I am using Colab free version.
Please advice, what can be done? Thanks in advance!
After Google Colab gets stuck and hangs the only thing to do is to interrupt execution and re-run the cell
I have a colab pro plus subscription, and I ran a python code that runs a network using pytorch.
Until now, I succeeded in training my network and using my Google drive to save checkpoints and such.
But now I had a run that ran for around 16 hours, and no checkpoint or any other data was saved - even though the logs clearly show that I have saved the data and even evaluated the metrics on saved data.
Maybe the data was saved on a different folder somehow?
I looked in the drive activity and I could not see any data that was saved.
Has anyone ran to this before?
Any help would be appreciated.
I am doing some data pre-processing on Google Colab and just wondering how it works with manipulating dataset. For example R does not change the original dataset until you use write.csv to export the changed dataset. Does it work similarly in colab? Thank you!
Until you explicitly save your changed data, e.g. using df.to_csv to the same file you read from, your changed dataset is not saved.
You must remember that due to inactivity (up to an hour or so), you colab session might expire and all progress be lost.
Update
To download a model, dataset or a big file from Google Drive, gdown command is already available
!gdown https://drive.google.com/uc?id=FILE_ID
Download your code from GitHub and run predictions using the model you already downloaded
!git clone https://USERNAME:PASSWORD#github.com/username/project.git
Write ! before a line of your code in colab and it would be treated as bash command. You can download files form internet using wget for example
!wget file_url
You can commit and push your updated code to GitHub etc. And updated dataset / model to Google Drive or Dropbox.
I was recently working in a notebook on Google Colab and my computer ran out of battery and died. All the progress I had made was not saved anywhere!
I'm very used to having jupyter notebooks, which saves my files pretty much every time I execute a cell.
Is there a way to have an equivalent feature in Google Colab?
Autosave is already implemented in Google Colab, but there is a certain delay between the moment you execute a cell and when the save occurs.
You can try this yourself by going into File>Revision History, executing a cell, and waiting for the list to refresh.
That being said, I have also experienced loss of data in the past, which I can't explain. It might be a glitch.
As a good practice, I try to save every time I remember.
Good luck.
Autosave every 60 seconds by running this "magic command" into a new code cell :
%autosave 60
Colab will confirm it when you run the cell with printing : "Autosave changes every 60 seconds"
To display the list of all magic commands you can use the command :
%lsmagic
Additionally, you can call the Quick Reference Guide, describing all the magic commands and what they do using the command :
%quickref
Enjoy!
I am trying to visualize a training session I trained in a remote server. I used scp to copy the file in my local iMac. I tried to visualize the data by running tensorboard. It runs the tensorboard site but I can't get the visualization. Every chart has a single dot at zero. I get this warning on the terminal.
WARNING:tensorflow:Unable to get first event timestamp for run
470_313_0.0001_2500_200/train
WARNING:tensorflow:Unable to get first event timestamp for run
470_313_0.0001_2500_200/train
WARNING:tensorflow:Unable to get first event timestamp for run
470_313_0.0001_2500_200/val
WARNING:tensorflow:Unable to get first event timestamp for run
470_313_0.0001_2500_50/train
WARNING:tensorflow:Unable to get first event timestamp for run
470_313_0.0001_2500_50/val
Any idea what is going on?
I ran into the same problem (with a TensorFlow 1.4 trainer running in the cloud with Google Cloud ML Engine).
Explicitly closing tf.summary.FileWriters with close() solved it in my case.
I ran into a similar problem. There are 2 solutions to it -
Delete all past tfevents files from the directory and keep the latest one (temporary solution).
Create a new directory for building your logs (permanent solution).
In given below picture, first I build logs in directory 2 which resulted in same error/warnings. Later I changed the directory to 3 and build logs there and tensorboard ran successfully.
In my case, the problem was the directory names for the runs were too long. After I manually renamed them, the problem is solved.