Unable to run conda package manager. AzureML uses conda to provision python environments from a dependency specification. about dp100-azuredatascientistassociate HOT 3 CLOSED

Running the script as an experiment
To run the script, create a ScriptRunConfig that references the folder and script file. You generally also need to define a Python (Conda) environment that includes any packages required by the script. In this example, the script uses Scikit-Learn so you must create an environment that includes that. The script also uses Azure Machine Learning to log metrics, so you need to remember to include the azureml-defaults package in the environment.

from dp100-azuredatascientistassociate.

https://docs.microsoft.com/en-ca/azure/machine-learning/how-to-use-environments
https://docs.microsoft.com/en-ca/azure/machine-learning/concept-environments

from dp100-azuredatascientistassociate.

According to the documentation available in: https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-environments#create-an-environment

It is necessary to set the property Environment.python.user_managed_dependencies = True.

The specific part of the documentation is related to a containerized environment, which is not this case, but the same property works for local Python environments as I have been running these notebooks locally with VS Code and a local Conda installation.

Specify your own Python interpreter
In some situations, your custom base image may already contain a Python environment with packages that you want to use.

To use your own installed packages and disable Conda, set the parameter Environment.python.user_managed_dependencies = True. Ensure that the base image contains a Python interpreter, and has the packages your training script needs.

For example, to run in a base Miniconda environment that has NumPy package installed, first specify a Dockerfile with a step to install the package. Then set the user-managed dependencies to True.

You can also specify a path to a specific Python interpreter within the image, by setting the Environment.python.interpreter_path variable.

from dp100-azuredatascientistassociate.