def argument_parser():
parser = basic_argument_parser(distributed=True, requires_output_dir=False)
parser.add_argument("--num-gpus",
type=int,
default=0,
help="number of GPUs per machine")
return parser
def get_parser():
parser = basic_argument_parser(distributed=False)
parser.add_argument(
"--predictor-types",
type=str,
nargs="+",
help="List of strings specify the types of predictors to export",
)
parser.add_argument(
"--compare-accuracy",
action="store_true",
help=
"If true, all exported models and the original pytorch model will be"
" evaluated on cfg.DATASETS.TEST",
)
parser.add_argument(
"--skip-if-fail",
action="store_true",
default=False,
help=
"If set, suppress the exception for failed exporting and continue to"
" export the next type of model",
)
parser.add_argument(
"--inference-config-file",
type=str,
default=None,
help=
"Inference config file containing the model parameters for c++ sdk pipeline",
)
return parser
def cli(args):
parser = basic_argument_parser()
parser.add_argument(
"--predictor-path",
type=str,
help="Path (a directory) to the exported model that will be evaluated",
)
# === performance config ===========================================================
parser.add_argument(
"--num-threads",
type=int,
default=None,
help=
"Number of omp/mkl threads (per process) to use in Caffe2's GlobalInit",
)
parser.add_argument(
"--caffe2-engine",
type=str,
default=None,
help="If set, engine of all ops will be set by this value",
)
parser.add_argument(
"--caffe2_logging_print_net_summary",
type=int,
default=0,
help="Control the --caffe2_logging_print_net_summary in GlobalInit",
)
run_with_cmdline_args(parser.parse_args())
def cli(args):
parser = basic_argument_parser(requires_output_dir=False)
parser.add_argument("--eval-only",
action="store_true",
help="perform evaluation only")
parser.add_argument(
"--resume",
action="store_true",
help="whether to attempt to resume from the checkpoint directory",
)
run_with_cmdline_args(parser.parse_args(args))
print_metrics_table(metrics)
return {
"accuracy": metrics,
"metrics": metrics,
}
def run_with_cmdline_args(args):
cfg, output_dir, runner = prepare_for_launch(args)
launch(
post_mortem_if_fail_for_main(main),
num_processes_per_machine=args.num_processes,
num_machines=args.num_machines,
machine_rank=args.machine_rank,
dist_url=args.dist_url,
backend=args.dist_backend,
args=(cfg, output_dir, runner, args.is_train),
)
if __name__ == "__main__":
parser = basic_argument_parser(requires_output_dir=True)
parser.add_argument(
"--is-train",
type=bool,
default=True,
help="data loader is train",
)
run_with_cmdline_args(parser.parse_args())
always_spawn=False,
args=(
cfg,
output_dir,
runner,
# binary specific optional arguments
args.predictor_path,
args.num_threads,
args.caffe2_engine,
args.caffe2_logging_print_net_summary,
),
)
if __name__ == "__main__":
parser = basic_argument_parser()
parser.add_argument(
"--predictor-path",
type=str,
help="Path (a directory) to the exported model that will be evaluated",
)
# === performance config ===========================================================
parser.add_argument(
"--num-threads",
type=int,
default=None,
help="Number of omp/mkl threads (per process) to use in Caffe2's GlobalInit",
)
parser.add_argument(
"--caffe2-engine",
type=str,