def load_config(config_file):
"""Load config from file."""
import os
import pickle
import vega
with open(config_file, 'rb') as f:
config = pickle.load(f)
for (key, value) in config["env"].items():
if value is not None:
os.environ[key] = value
vega.set_backend(os.environ['BACKEND_TYPE'].lower(), os.environ["DEVICE_CATEGORY"])
from vega.common.class_factory import ClassFactory
from vega.common.general import General
from vega.datasets.conf.dataset import DatasetConfig
from vega.networks.model_config import ModelConfig
from vega.trainer.conf import TrainerConfig
from vega.evaluator.conf import EvaluatorConfig
from vega.core.pipeline.conf import PipeStepConfig
ClassFactory.__registry__ = config["class_factory"]
General.from_dict(config["general"])
DatasetConfig.from_dict(config["dataset"])
ModelConfig.from_dict(config["model"])
TrainerConfig.from_dict(config["trainer"])
EvaluatorConfig.from_dict(config["evaluator"])
PipeStepConfig.from_dict(config["pipe_step"])
def _simulate_tiny_pipeline(self, cfg_tiny):
"""Simulate tiny pipeline by using one sample one epoch."""
report = ReportServer()
for i, step_name in enumerate(PipelineConfig.steps):
step_cfg = cfg_tiny.get(step_name)
if step_cfg.pipe_step.type != 'SearchPipeStep':
continue
step_cfg.trainer.distributed = False
step_cfg.trainer.epochs = 1
self.restrict_config.trials[step_name] = 1
General.step_name = step_name
PipeStepConfig.from_dict(step_cfg)
pipestep = PipeStep()
if i == 0:
pipestep.do()
record = report.get_step_records(step_name)[-1]
self.epoch_time = record.runtime
_worker_path = TaskOps().local_base_path
if os.path.exists(_worker_path):
os.system('rm -rf {}'.format(_worker_path))
if step_cfg.pipe_step.type == 'SearchPipeStep':
self.params_dict[step_name][
'max_samples'] = pipestep.generator.search_alg.max_samples
_file = os.path.join(TaskOps().step_path, ".generator")
if os.path.exists(_file):
os.system('rm {}'.format(_file))
import horovod.torch as hvd
from zeus.common import ClassFactory
from zeus.common.general import General
from vega.core.pipeline.conf import PipeStepConfig
parser = argparse.ArgumentParser(description='Horovod Fully Train')
parser.add_argument('--cf_file', type=str, help='ClassFactory pickle file')
args = parser.parse_args()
if 'VEGA_INIT_ENV' in os.environ:
exec(os.environ.copy()['VEGA_INIT_ENV'])
logging.info('start horovod setting')
hvd.init()
try:
import moxing as mox
mox.file.set_auth(obs_client_log=False)
except Exception:
pass
hvd.join()
with open(args.cf_file, 'rb') as f:
cf_content = pickle.load(f)
model_desc = cf_content.get('model_desc')
worker_id = cf_content.get('worker_id')
ClassFactory.__registry__ = cf_content.get('registry')
General.from_dict(cf_content.get('general_config'))
PipeStepConfig.from_dict(cf_content.get('pipe_step_config'))
cls_trainer = ClassFactory.get_cls('trainer')
# for record in records:
trainer = cls_trainer(model_desc=model_desc, id=worker_id)
trainer.train_process()