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update samples from Release-53 as a part of 1.19.0 SDK stable release

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amlrelsa-ms
2020-12-07 18:55:07 +00:00
parent 41366a4af0
commit 48e3e7b510
39 changed files with 371 additions and 279 deletions
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39
how-to-use-azureml/automated-machine-learning/forecasting-bike-share/run_forecast.py
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@@ -1,29 +1,32 @@
from azureml.train.estimator import Estimator
from azureml.core import ScriptRunConfig
def run_rolling_forecast(test_experiment, compute_target, train_run, test_dataset,
target_column_name, inference_folder='./forecast'):
def run_rolling_forecast(test_experiment, compute_target, train_run,
test_dataset, target_column_name,
inference_folder='./forecast'):
train_run.download_file('outputs/model.pkl',
inference_folder + '/model.pkl')
inference_env = train_run.get_environment()
est = Estimator(source_directory=inference_folder,
entry_script='forecasting_script.py',
script_params={
'--target_column_name': target_column_name
},
inputs=[test_dataset.as_named_input('test_data')],
compute_target=compute_target,
environment_definition=inference_env)
config = ScriptRunConfig(source_directory=inference_folder,
script='forecasting_script.py',
arguments=['--target_column_name',
target_column_name,
'--test_dataset',
test_dataset.as_named_input(test_dataset.name)],
compute_target=compute_target,
environment=inference_env)
run = test_experiment.submit(est,
tags={
'training_run_id': train_run.id,
'run_algorithm': train_run.properties['run_algorithm'],
'valid_score': train_run.properties['score'],
'primary_metric': train_run.properties['primary_metric']
})
run = test_experiment.submit(config,
tags={'training_run_id':
train_run.id,
'run_algorithm':
train_run.properties['run_algorithm'],
'valid_score':
train_run.properties['score'],
'primary_metric':
train_run.properties['primary_metric']})
run.log("run_algorithm", run.tags['run_algorithm'])
return run