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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
⚠ Do not edit this section. It is required for learn.microsoft.com ➟ GitHub issue linking.
ID: eb938463-51c2-43f3-d528-76a07a28bec8
Version Independent ID: e15753c0-6fe1-100a-0efc-08c1f845dc83
I'm running the following from the example:
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
⚠ Do not edit this section. It is required for learn.microsoft.com ➟ GitHub issue linking.
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