def run(args, myargs):
my_config = getattr(myargs.config, args.command)
config = SearchConfig()
for k, v in args.items():
assert not hasattr(config, k)
setattr(config, k, v)
for k, v in my_config.items():
if not hasattr(config, k):
print('* config does not have %s' % k)
setattr(config, k, v)
device = torch.device("cuda")
writer = myargs.writer
writer.add_text('all_config', config.as_markdown(), 0)
logger = myargs.logger
config.print_params(logger.info_msg)
config.data_path = os.path.expanduser(config.data_path)
config.plot_path = os.path.join(args.outdir, 'plot')
config.path = args.outdir
main(config=config, logger=logger, device=device, myargs=myargs)
def get_current_node_index():
if "PAI_CURRENT_TASK_ROLE_CURRENT_TASK_INDEX" not in os.environ:
return 0
return int(os.environ["PAI_CURRENT_TASK_ROLE_CURRENT_TASK_INDEX"])
if __name__ == "__main__":
config = SearchConfig()
if config.nni:
if config.nni == "gt_mock":
nni_tools.mock_result()
else:
config.designated_subgraph = [nni_tools.get_param()]
config.path = nni_tools.get_output_dir()
# tensorboard
writer = SummaryWriter(log_dir=os.path.join(config.path, "tb"))
writer.add_text('config', config.as_markdown(), 0)
logger = utils.get_logger(os.path.join(config.path, "{}.log".format(config.name)))
config.print_params(logger.info)
main(config, writer, logger)
writer.close()
elif config.shared_policy == "group":
config.shared_policy = "all"
if "designated_partition" in config.shared_policy_kwargs:
