Model doesn't run after submit - local compute

[matsuobasho]

I'm running the following from the example:

from azureml.core import Workspace
from azureml.core.experiment import Experiment
from azureml.core.environment import Environment
from azureml.core.conda_dependencies import CondaDependencies
from azureml.core import ScriptRunConfig, Experiment

ws = Workspace.get(name="ws_name", subscription_id='id', resource_group='rg')
myenv = Environment(name="myenv")
runconfig = ScriptRunConfig(source_directory="../src", script="train.py")
conda_dep = CondaDependencies()

conda_dep.add_conda_package("numpy==1.17.0")
conda_dep.add_pip_package("sklearn")
conda_dep.add_pip_package("joblib")

myenv.python.conda_dependencies=conda_dep

exp = Experiment(name="test-experiment", workspace = ws)
runconfig.run_config.target = "local"
runconfig.run_config.environment = myenv
run = exp.submit(runconfig)

train.py is the same as shown in the Tutorial. I'm expecting a churn-model.pkl to be saved in my local directory. However, that doesn't happen. When I check the Experiment section on the AzureML dashboard, the status shows 'starting'.

Or do I need an additional command in order to actually launch the job?

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Document Details

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• ID: eb938463-51c2-43f3-d528-76a07a28bec8
• Version Independent ID: e15753c0-6fe1-100a-0efc-08c1f845dc83
• Content: Azure Machine Learning SDK for Python - Azure Machine Learning Python
• Content Source: AzureML-Docset/docs-ref-conceptual/index.md
• Service: machine-learning
• Sub-service: core
• GitHub Login: C.J. Gronlund (@cjgronlund)
• Microsoft Alias: cgronlun

[alobroke]

For local runs with the AzureML SDK (v1), submitting the experiment alone does not always start execution immediately.

After:

run = exp.submit(runconfig)

we shall explicitly wait for the run to execute:

run.wait_for_completion(show_output=True)

Without calling wait_for_completion(...), the run can remain in "Starting" state in the AzureML dashboard and not actually execute locally.

A couple of additional checks:

• Ensure runconfig.run_config.target = "local" is set before submission.
• Verify that source_directory="../src" is correct relative to your current working directory.
• For local runs, execution logs are written under the azureml_runs/ folder — check there for errors.
• If you expect churn-model.pkl to be captured by AzureML, write it to the outputs/ directory (AzureML automatically uploads files from outputs/ after run completion).

If the issue persists after adding wait_for_completion, sharing the output logs from the local run would help diagnose further.