def register_environment(
workspace=None,
environment_directory=None,
# We should enforce a logger
logger=None):
definition = Environment.load_from_directory(environment_directory)
result = definition.register(workspace)
return Environment._serialize_to_dict(result)
print('Error while retrieving compute', e)
sys.exit(-1)
env = None
try:
env = Environment.get(workspace=ws,
name=os.environ.get('AML_ENVIRONMENT', 'myenv'))
except Exception as e:
print('Environment not found in workspace')
print('Trying to retrieve from local config')
if env is None:
try:
dir_path = Path(__file__).resolve().parent.parent
env_path = dir_path / '< folder to use >'
env = Environment.load_from_directory(path=env_path)
except Exception as e:
print('Environment folder not found')
print('Shutting everything down !')
sys.exit(-1)
src = ScriptRunConfig(source_directory='./src', script='/train.py')
# Set compute target to the one created in previous step
src.run_config.target = compute_target.name
# Set environment
src.run_config.environment = env
run = experiment.submit(config=src)
# ----------------------------------------------------------
###########################