Comments (2)
The model name is hard coded in the score.py function :
model_path = Model.get_model_path('diabetes-model')
Is there a way to variabilize it ?
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in a nutshell, I would say it's not really possible to do so. There has to be a model name (which corresponds to what you would have registered to Azure Machine Learning in the devops pipeline. That exact name has to be reused there to rehydrate the model when the init
function runs.
from pipelines-azureml.
Related Issues (15)
- Issue with model train command . HOT 5
- Running h2o.ai in Azure ML (Installing Java is a must) HOT 1
- Any example of model deployment on local compute?
- Unable to delete pipeline drafts?
- 'Error': TypeError("'<' not supported between instances of 'int' and 'NoneType'",)} HOT 1
- Compute name 'cpu-cluster-1' is invalid
- Readme instructions broken
- Retry pipeline and/or task on failure
- Testing the model
- Problems executing the pipeline examples HOT 1
- Error in Attach folder to workspace step
- Error in train model HOT 2
- Issue running Azure DevOps pipeline from pipelines/diabetes-train-and-deploy.yml HOT 1
- This repo is missing important files
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