That's right. There is no such package, it's just a custom module.
But that module uses tensorflow
, and ClearML does not add it to the list of packages to install. The only solution available so far is to include it manually via Task.add_requirements
?
So ClearML will scan all the repository code searching for package dependencies? Is that right?
Hi GiganticTurtle0
ClearML will only list the directly imported packaged (not their requirements), meaning in your case it will only list "tf_funcs" (which you imported).
But I do not think there is a package named "tf_funcs" right ?
Then ClearML should also detect the dependencies of the imported scripts? In this case shouldn't it detect that I am going to use tensorflow
and install it as well? Because it is not actually recognizing it.
, it's just a custom module.
Is this your own module ? Is this a local folder we import from ?
Thanks for helping. You and your team are doing a great job for the ML community.
Correct.
It starts with the initial script (entry point), if it is self contained (i.e. does not interact with the rest of the repo) it will only analyze it, otherwise it will analyze the entire repo code.
It's my own module (called 'tf_funcs.py')
Hi GiganticTurtle0 ,
All the packages you are using should be under installed packages
section in your task (in the UI). ClearML analyze and the full report should be under this section.
You can add any package you like with Task.add_requirements('tensorflow', '2.4.0')
for tensorflow version 2.4.0 (or Task.add_requirements('tensorflow', '')
for no limit).
If you dont want the package analyzer, you can configure in your ~/clearml.conf file: sdk.development.detect_with_pip_freeze: true
and the installed packages section will be the same as you python environment pip freeze
GiganticTurtle0 is it in the same repository ?
If it is it should have detected the fact that it needs to analyze the entire repository (not just the standalone script, and then discover tensorflow)