hey WhoppingMole85 good morning !
try to pip it !
pip install clearml -U
and then check with
pip show clearml

Hi CrabbyKoala94
I am working on your issue, I will update you asap. Thanks

You need to use the API for exporting experiments to csv/excel. I am preparing an example for you

hi ScaryBluewhale66
Can please elaborate, i am not sure that i get your question ? What do you need to compare ?

hey
You have 2 options to retrieve a dataset : by its id or by the project_name AND dataset_name - those ones are working together, you need to pass both of them !

https://clear.ml/docs/latest/docs/integrations/storage#caching

hey @<1523704089874010112:profile|FloppyDeer99>
did you manage to get rid of your issue ?
thanks

good to know. we will try to enquire that. thanks

I see some points that you should fix
in the train step, you return 2 items but you have only one in its decorator: add mock do you really need to init a task in the pipeline controller ? you will automatically get one when executing the pipeline

Yes I think that it would be great if you could try to run it with a simpler configuration

Hey UnevenDolphin73
When you use the parameter "use_current_task" the dataset and the resulting task will be the same (same id). So to retrieve this dataset for using it into another task, use Task.get(...) to retrieve its id.
Then when you will need it into another task, simply retrieve it from within that task by using Dataset.get(dataset_id=...)

Hi GentleSwallow91 ,
I can't manage to reproduce the issue, it is working fine for me. I use a local minio docker-based image. The conf file has to be precisely configured, but it seems that you did it ok, because you don't have a denied access here. It is strange that he is waiting for the upload to finish. We have this flag for upload_artefact : wait_on_upload . His default value should be False, but i would try to add it...

Also I don't understand what you mean by " I can see files in ...

Also, change this line of the conf file to false :

development {
# Development-mode options

    # dev task reuse window
    task_reuse_time_window_in_hours: 72.0

    # Run VCS repository detection asynchronously
    vcs_repo_detect_async:  true      <== change to false

hey OutrageousSheep60
what about the process ? there must be one clearml-agent process that runs somwhere, and that is why it can continue reporting to the server

yes i have the behavior. I think that we have a bug. We will release a fix and will keep you updated 🙂
can you please open a github issue ? Of course if it is a problem, i can do it for you, just let me know 🙂
http://github.com/allegroai/clearml/issues

Could you please give me some details about what you need to achieve ? It could also help if you could explain me what you mean by : When I use Task.create it works ?
A screenshot would be welcomed here 🙂

Concerning how to use ParameterSet :
I first declare the set
my_param_set = ParameterSet([ {'General/batch_size': 32, 'General/epochs': 30}, {'General/batch_size': 64, 'General/epochs': 20}, {'General/batch_size': 128, 'General/epochs': 10} ])This is a very basic example, it is also possible to use more complex things into the set (see https://clear.ml/docs/latest/docs/references/sdk/hpo_parameters_parameterset/ for UniformParameter Range usage in ParameterSet).

Then i do ...

i dont know if it will help but here is what i would test :
remove temporary the task init in the controller use name and project parameters that dont have spaces in their name dont use services as a default queue

thanks for those info. i check that and come back to you

thanks for all those precisions. I will try to reproduce and keep you updated 🙂

i managed to import a custom package using the same way you did : i have added the current dir path to my system
i have a 2 steps pipeline :

1. Run a function from a custom package. This function returns a Dataloader (built from torchvision.MNIST) 2) This step receives the dataloader built in the first step as a parameter ; it shows random samples from itthere has been no error to return the dataloader at the end of step1 and to import it at step2. Here is my code :

` from clearml import Pi...

hey WickedElephant66 TenderCoyote78
I'm working on a solution, just hold on, I update you asap

In the meantime, it is also possible to create a figure that will contain +2 histo and then report it to the logger using report_plotly.
You can have a look there :
https://plotly.com/python/histograms/#overlaid-histogram
https://plotly.com/python/histograms/#stacked-histograms

` log = task.get_logger()

x0 = np.random.randn(1500)
x1 = np.random.randn(1500) - 1

fig = go.Figure()

fig.add_trace(go.Histogram(y=x0))
fig.add_trace(go.Histogram(y=x1))

fig.update_layout(barmode='overlay') ...

Hi SteepDeer88
I wrote this script to try to reproduce the error. I am passing there +50 parameters and so far everything works fine. Could you please give me some more details about your issue, so that we could reproduce it ?

from clearml import Task
import argparse

'''
COMMAND LINE:
python -m my_script --project_name my_project --task_name my_task --execute_remotely true --remote_queue default --param_1 parameter...

Hi WickedElephant66
When you are in the Projects section of the WebApp (second icon on the left), enter either "All Experiments" or any project you want to access to. Up on the center is the Models section. You csn find the url the model can be downloaded from, in the details, section

Hi SparklingElephant70
The function doesn't seem to find any datasets which project_name matches your request.
Some more detailed code on how you create your dataset, and how you try to retrieve it, could help me to better understand the issue 🙂

Hope it will help 🤞 . Do not hesitate to ask if the error persists

hi SoggyBeetle95
i reproduced the issue, could you confirm me that it is the issue ?
here is what i did :
i declared some secret env var in the agent section of clearml.conf i used extra_keys to have hidden on the console, it is indeed hidden but in the execution -> container section it is clear

No, it is supposed to have its status updated automatically. We may have a bug. Can you share some example code with me, so that i could try to figure out what is happening here ?

hey ApprehensiveSeahorse83
can you please check that the trigger is correctly added ? Simply retrieve the return value of add_task_trigger
res = trigger.add_task_trigger( .....
print(f'Trigger correctly added ? {res}')