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| First Steps |
Install ClearML
First, sign up for free
Install the clearml python package:
pip install clearml
Connect your computer to the server by creating credentials, then run the below and follow the setup instructions:
clearml-init
Auto-log Experiment
In ClearML, experiments are organized as Tasks.
ClearML will automatically log your experiment and code, including outputs and parameters from popular ML frameworks, once you integrate the ClearML SDK with your code. To control what ClearML automatically logs, see this FAQ.
At the beginning of your code, import the clearml package:
from clearml import Task
:::note Full Automatic Logging To ensure full automatic logging, it is recommended to import the ClearML package at the top of your entry script. :::
Then initialize the Task object in your main() function, or the beginning of the script.
task = Task.init(project_name='great project', task_name='best experiment')
Task name is not unique, it's possible to have multiple experiments with the same name. If the project does not already exist, a new one will be created automatically.
The console should return the following output:
ClearML Task: created new task id=1ca59ef1f86d44bd81cb517d529d9e5a
2021-07-25 13:59:09
ClearML results page: https://community/projects/4043a1657f374e9298649c6ba72ad233/experiments/1ca59ef1f86d44bd81cb517d529d9e5a/output/log
2021-07-25 13:59:16
That’s it! You are done integrating ClearML with your code :)
Now, command-line arguments, console output as well as Tensorboard and Matplotlib will automatically be logged in the UI under the created Task.
Sit back, relax, and watch your models converge :) or continue to see what else can be done with ClearML here.