def _get_automl_settings(automl_settings, logger):
automl_settings_obj = None
current_run = Run.get_submitted_run()
found_data_store = False
data_store = None
start = time.time()
try:
experiment = current_run.experiment
parent_run_id = _get_parent_run_id(current_run._run_id)
print("parent run id {}".format(parent_run_id))
automl_settings_obj = _AutoMLSettings.from_string_or_dict(automl_settings)
data_store = experiment.workspace.get_default_datastore()
found_data_store = True
except Exception as e:
logger.warning("getting data store, fallback to default {}".format(e))
print("failed to get default data store {}".format(e))
found_data_store = False
end = time.time()
print("Caching supported {}, time taken for get default DS {}".format(sdk_has_cache_capability and found_data_store, (end - start)))
return automl_settings_obj, found_data_store, data_store
def driver_wrapper(script_directory, automl_settings, run_id,
training_percent, iteration, pipeline_spec, pipeline_id,
dataprep_json, entry_point, **kwargs):
automl_settings_obj = _AutoMLSettings.from_string_or_dict(
automl_settings)
logger, sdk_has_custom_dimension_logger = _init_logger(
automl_settings_obj)
if sdk_has_custom_dimension_logger:
logger.update_default_properties({
"parent_run_id":
_get_parent_run_id(run_id),
"child_run_id":
run_id
})
logger.info("[RunId:{}]: remote automl driver begins.".format(run_id))
try:
script_directory = _init_directory(directory=script_directory,
logger=logger)
automl_settings_obj, found_data_store, data_store = _get_automl_settings(
automl_settings=automl_settings, logger=logger)
transformed_data_context = _load_transformed_data_context_from_cache(
automl_settings_obj=automl_settings_obj,
parent_run_id=_get_parent_run_id(run_id),
found_data_store=found_data_store,
data_store=data_store,
logger=logger)
result = _start_run(
automl_settings_obj=automl_settings_obj,
run_id=run_id,
training_percent=training_percent,
iteration=iteration,
pipeline_spec=pipeline_spec,
pipeline_id=pipeline_id,
dataprep_json=dataprep_json,
script_directory=script_directory,
entry_point=entry_point,
logger=logger,
transformed_data_context=transformed_data_context)
_post_run(result=result,
run_id=run_id,
automl_settings=automl_settings,
logger=logger)
except Exception as e:
logger.error("driver_wrapper meets exceptions. {}".format(e))
log_traceback(e, logger)
raise Exception(e)
logger.info(
"[RunId:{}]: remote automl driver finishes.".format(run_id))
return result
def setup_wrapper(script_directory, dataprep_json, entry_point,
automl_settings, task_type, preprocess,
enable_subsampling, num_iterations, **kwargs):
automl_settings_obj = _AutoMLSettings.from_string_or_dict(
automl_settings)
logger, sdk_has_custom_dimension_logger = _init_logger(
automl_settings_obj)
try:
child_run_id = Run.get_submitted_run()._run_id
parent_run_id = _get_parent_run_id(child_run_id)
if sdk_has_custom_dimension_logger:
logger.update_default_properties({
"parent_run_id": parent_run_id,
"child_run_id": child_run_id
})
logger.info("[ParentRunId:{}]: remote setup script begins.".format(
parent_run_id))
script_directory = _init_directory(directory=script_directory,
logger=logger)
logger.info("Preparing data for set problem info now.")
fit_iteration_parameters_dict = _prepare_data(
dataprep_json=dataprep_json,
automl_settings_obj=automl_settings_obj,
script_directory=script_directory,
entry_point=entry_point,
logger=logger)
fit_iteration_parameters_dict = _get_auto_cv_dict(
fit_iteration_parameters_dict, automl_settings_obj, logger)
print("Setting Problem Info now.")
_set_problem_info_for_setup(
fit_iteration_parameters_dict=fit_iteration_parameters_dict,
automl_settings_obj=automl_settings_obj,
task_type=task_type,
preprocess=preprocess,
enable_subsampling=enable_subsampling,
num_iterations=num_iterations,
logger=logger)
except Exception as e:
logger.error("setup_wrapper meets exceptions. {}".format(e))
log_traceback(e, logger)
raise Exception(e)
_post_setup(logger=logger)
logger.info("[ParentRunId:{}]: remote setup script finishes.".format(
parent_run_id))
return # PLACEHOLDER for RemoteScript helper functions
