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Is it possible to use a local compute for the TensorFlow estimator? Provisioning a virtual machine for a training run takes an enormous amount of time, and I would like to be able to try a few runs locally until my configuration is stable.

It is possible to do this with ScriptRunConfig by creating an empty RunConfiguration. The documentation claims that it is possible to create a local ComputeTarget, but the documentation on how to do this is missing:

Local computer

Create and attach: There's no need to create or attach a compute target to use your local computer as the training environment.

Configure: When you use your local computer as a compute target, the training code is run in your development environment. If that environment already has the Python packages you need, use the user-managed environment.


1 Answer

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Create an empty RunConfiguration and write this code: 

from azureml.core.runconfig import RunConfiguration

# Edit a run configuration property on the fly.

run_local = RunConfiguration()

run_local.environment.python.user_managed_dependencies = True

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