Using detect_with_pip_freeze: true runs into package version not found for some of the ones I have locally.

Hey AgitatedDove14 after playing around seems that if the callback filepath points to an hdf5 file it is not uploaded.

Thanks AgitatedDove14 !

AgitatedDove14 I filed an issue of fire for them to point us to the argument parsing method https://github.com/google/python-fire/issues/291

Thanks SuccessfulKoala55 !

Thanks for the info AgitatedDove14 !

Pigar is capturing different versions that the ones I have installed on my local machine (not a problem except for one). I just want to force the version of that package in a way that I don’t have to manually change it from the UI for every experiment.

Basically one points to an hdf5 and the other one has no extensiion

Thanks TimelyPenguin76 , the example works fine! I’ll debug further on my side!

On the server through the command line?

Using the get_weights(True) I get ValueError: Could not retrieve a local copy of model weights <ID>, failed downloading <URL>

Makes sense! Then where would I have to add output_uri to save the weights?

Thanks so much AgitatedDove14 !

👌 Great

Yes, everything is that way (work dir and args are ok) except the script path . It shows -m module arg1 arg2 .

I’ll show you what I have through PM!

Thanks Martin! 🙌

I’ll open the PR!

I am using the code inside the on_train_epoch_end inside a metric. So the important part is:
` fig = plt.figure()

my plot

logger.experiment.add_figure("fig", fig)
plt.close() `

AgitatedDove14 I am not sure why the packages get different versions, maybe since the package is not directly imported in my code it is possible to get a different version to what I have locally (?). Should all the libraries versions match exactly between local and the code that runs in the agent? The Task.add_requirements(package_name, package_version=None) workaround works perfectly! I just add the previous version that doesn’t break the code. Yes, definitely a force flag could help ...

Yes! I think thats what I will do 👌 Let me know if there is a way to contribute a mode to keep logging off. We just don’t want to pollute the server when debugging.

Hi CostlyOstrich36 ! The message is the following:
clearml.model - INFO - Selected model id: 27c1a1700b0b4e25a4344dc4ef9868faThey are not models, those are intermediate tensors I am caching to make training faster. I don't need to log them.

Thanks SuccessfulKoala55 !

Yes! What env variables should I pass

Thanks!

I'll give that a try! Thanks CostlyOstrich36

SuccessfulKoala55 Is the update from 1.2.0 only updating the docker-compose file?

Yes, the files are inside the folder

Thanks AgitatedDove14 !

Thanks SuccessfulKoala55 i’ll try this out!