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**

Inizia con l’esempio indicato e il relativo train.py, quindi riproduci l’invio locale alla destinazione usando la configurazione mostrata di Workspace, Environment, ScriptRunConfig ed Experiment. Verifica perché l’esecuzione rimane in “starting” e se churn-model.pkl è previsto nella directory locale; il lavoro è completato quando il comportamento previsto dell’esecuzione locale e la posizione dell’artefatto sono documentati o corretti.

Scritto dal modello di indicizzazione a partire dal testo della issue.