Model doesn't run after submit - local compute

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?

---
#### 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](https://learn.microsoft.com/en-us/python/api/overview/azure/ml/?view=azure-ml-py)
* Content Source: [AzureML-Docset/docs-ref-conceptual/index.md](https://github.com/MicrosoftDocs/MachineLearning-Python-pr/blob/live/AzureML-Docset/docs-ref-conceptual/index.md)
* Service: **machine-learning**
* Sub-service: **core**
* GitHub Login: @cjgronlund
* Microsoft Alias: **cgronlun**

Beginne mit dem referenzierten Beispiel und seiner train.py und reproduziere anschließend die lokale Zielübermittlung mit dem gezeigten Setup aus Workspace, Environment, ScriptRunConfig und Experiment. Prüfe, warum der Lauf in „starting“ verbleibt und ob churn-model.pkl im lokalen Verzeichnis erwartet wird; abgeschlossen bedeutet, dass das erwartete lokale Ausführungsverhalten und der Speicherort des Artefakts dokumentiert oder korrigiert sind.

Vom Indexierungsmodell aus dem Issue-Text verfasst.