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) # ---------------------------------------------------------- ###########################