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How to export a saved model, as zip file, in a managed folder?

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radiantly
Level 2
How to export a saved model, as zip file, in a managed folder?

It would be great to have some help from the community:
"How to export a saved model, as zip file, in a managed folder?"

It seems like that I need to do it two steps:
# Step 1: save the model as a zip file at the instance where the current project is running
# Step 2: upload the zip file from the instance location to the managed folder

How to do it in 1 step without saving the file in the local instance?

The example provided in the link #1 below uses "get_scoring_python" method which takes a 'filename' as an input. One can provide path + filename to save the zip file in a specific location. I might be wrong, but it seems like it does not allow 'folder_path' as a 'path' but accept any path from the local instance.

 

Capture01.PNG

Thank you.

Location of the project:
/home/dataiku/lib/

Location of the managed folder:
/home/dataiku/data/managed_folder/xxxx

 

I have explored the following links:

1. https://developer.dataiku.com/latest/concepts-and-examples/ml.html 

2. https://doc.dataiku.com/dss/latest/machine-learning/models-export.html 

 

I have checked the following threads where there were discussion along this line but could not find the exact solution that I need:

https://community.dataiku.com/t5/Using-Dataiku/Using-Models-Outside-DSS/m-p/32693 

https://community.dataiku.com/t5/Using-Dataiku/Export-model-from-dataiku-jupyter-to-my-local-machine... 

 

 

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2 Solutions
AdrienL
Dataiker

You can try to combine the model's get_scoring_python_stream with the managed folder's upload_stream, e.g.

with model.get_scoring_python_stream() as s:
    folder.upload_stream(managedfolder_file_name, s)

 

View solution in original post

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radiantly
Level 2
Author

Thank you. The method 'get_scoring_python_stream' works.  Adding my complete code in case someone needs it in the future. 

 

client = dataiku.api_client()
project = client.get_default_project()

project_key = project.project_key

# Get the saved model id from here
project.list_saved_models()
sm_id = 'saved model id'
saved_model = project.get_saved_model( sm_id )

version_id = saved_model.get_active_version()['id']
saved_model= saved_model.get_version_details( version_id=version_id )

folder = dataiku.Folder('your managed folder name')

managedfolder_file_name= 'model-archieve.zip'

with saved_model.get_scoring_python_stream() as s:
    folder.upload_stream(folder_file_name, s)

 

View solution in original post

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2 Replies
AdrienL
Dataiker

You can try to combine the model's get_scoring_python_stream with the managed folder's upload_stream, e.g.

with model.get_scoring_python_stream() as s:
    folder.upload_stream(managedfolder_file_name, s)

 

0 Kudos
radiantly
Level 2
Author

Thank you. The method 'get_scoring_python_stream' works.  Adding my complete code in case someone needs it in the future. 

 

client = dataiku.api_client()
project = client.get_default_project()

project_key = project.project_key

# Get the saved model id from here
project.list_saved_models()
sm_id = 'saved model id'
saved_model = project.get_saved_model( sm_id )

version_id = saved_model.get_active_version()['id']
saved_model= saved_model.get_version_details( version_id=version_id )

folder = dataiku.Folder('your managed folder name')

managedfolder_file_name= 'model-archieve.zip'

with saved_model.get_scoring_python_stream() as s:
    folder.upload_stream(folder_file_name, s)

 

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