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Hi, I'M Trying To Access/Use Experiment'S Model+Data+Params My Model And Data Are Stored In S3 And I'M Not Sure What Is The Practice Of Getting Them Reddy To Use. When I Use

Hi, I'm trying to access/use experiment's model+data+params
My model and data are stored in s3 and I'm not sure what is the practice of getting them reddy to use.
When I use local_csv = a_task.artifacts['train_data'].get_local_copy()
and cls = a_task.models['output'] I don't get the actual data and model.
The params dict I can get using get_parameters() but for some reason I get in my dict key string an addition of 'general/' followed by my param string 'max_depth'
I wish to understand what is the easiest way to reproduce my experiment using clearml SDK and have it ready to run again from my python interperter.
Thanks!

  
  
Posted 2 years ago
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Answers 4


HappyDove3 , Hi 🙂

I'm not sure I understand what you want to do. You want to get a local copy of your model file or you just want to play with the experiment and reproduce it 1:1 ?

  
  
Posted 2 years ago

IIRC, get_local_copy() downloads a local copy and returns the path to the downloaded file. So you might be interested in e.g.
local_csv = pd.read_csv(a_task.artifacts['train_data'].get_local_copy())
With the models, you're looking for get_weights() . It acts the same as get_local_copy() , so it returns a path.

EDIT: I think also get_local_copy() for a model should work 👍

  
  
Posted 2 years ago

I want to play with the experiment and reproduce it 1:1.
I managed to it with the advice of UnevenDolphin73 is there a different way to do it?

  
  
Posted 2 years ago

You can clone it via the UI, enqueue it to a queue that has a worker running against that queue. You should get a perfect 1:1 reproduction

  
  
Posted 2 years ago
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