def parse_arguments(arguments: List[str] = None):
parser = argparse.ArgumentParser(description=__doc__)
subparsers = parser.add_subparsers(title="Model", description="")
# -- * -- Common Arguments & Each Model's Arguments -- * --
CNNModel.add_arguments(parser, default_type="matting")
matting_nets.MattingNetModel.add_arguments(parser)
for class_name in matting_nets._available_nets:
subparser = subparsers.add_parser(class_name)
subparser.add_argument("--model",
default=class_name,
type=str,
help="DO NOT FIX ME")
add_matting_net_arguments = eval(
"matting_nets.{}.add_arguments".format(class_name))
add_matting_net_arguments(subparser)
Evaluator.add_arguments(parser)
Base.add_arguments(parser)
DataWrapperBase.add_arguments(parser)
MattingDataWrapper.add_arguments(parser)
MetricManagerBase.add_arguments(parser)
args = parser.parse_args(arguments)
model_arguments = utils.get_subparser_argument_list(parser, args.model)
args.model_arguments = model_arguments
return args
def parse_arguments(arguments: List[str] = None):
parser = argparse.ArgumentParser(description=__doc__)
subparsers = parser.add_subparsers(title="Model", description="")
TFModel.add_arguments(parser)
audio_nets.AudioNetModel.add_arguments(parser)
for class_name in audio_nets._available_nets:
subparser = subparsers.add_parser(class_name)
subparser.add_argument("--model",
default=class_name,
type=str,
help="DO NOT FIX ME")
add_audio_net_arguments = eval(
f"audio_nets.{class_name}.add_arguments")
add_audio_net_arguments(subparser)
DataWrapperBase.add_arguments(parser)
AudioDataWrapper.add_arguments(parser)
Base.add_arguments(parser)
TrainerBase.add_arguments(parser)
SingleLabelAudioTrainer.add_arguments(parser)
MetricManagerBase.add_arguments(parser)
args = parser.parse_args(arguments)
return args
def parse_arguments(arguments: List[str] = None):
parser = argparse.ArgumentParser(description=__doc__)
subparsers = parser.add_subparsers(title="Model", description="")
# -- * -- Common Arguments & Each Model's Arguments -- * --
CNNModel.add_arguments(parser, default_type="matting")
matting_nets.MattingNetModel.add_arguments(parser)
for class_name in matting_nets._available_nets:
subparser = subparsers.add_parser(class_name)
subparser.add_argument("--model",
default=class_name,
type=str,
help="DO NOT FIX ME")
add_matting_net_arguments = eval(
f"matting_nets.{class_name}.add_arguments")
add_matting_net_arguments(subparser)
# -- * -- Parameters & Options for MattingTrainer -- * --
TrainerBase.add_arguments(parser)
MattingTrainer.add_arguments(parser)
Base.add_arguments(parser)
DataWrapperBase.add_arguments(parser)
MattingDataWrapper.add_arguments(parser)
MetricManagerBase.add_arguments(parser)
# -- Parse arguments
args = parser.parse_args(arguments)
# Hack!!! subparser's arguments and dynamically add it to args(Namespace)
# it will be used for convert.py
model_arguments = utils.get_subparser_argument_list(parser, args.model)
args.model_arguments = model_arguments
return args
def __init__(self, model, session, args, dataset, dataset_name, name):
self.log = get_logger(name)
self.model = model
self.session = session
self.args = args
self.dataset = dataset
self.dataset_name = dataset_name
if Path(self.args.checkpoint_path).is_dir():
latest_checkpoint = tf.train.latest_checkpoint(
self.args.checkpoint_path)
if latest_checkpoint is not None:
self.args.checkpoint_path = latest_checkpoint
self.log.info(
f"Get latest checkpoint and update to it: {self.args.checkpoint_path}"
)
self.watch_path = self._build_watch_path()
self.variables_to_restore = Base.get_variables_to_restore(
args=self.args, log=self.log, debug=False)
self.session.run(tf.global_variables_initializer())
self.session.run(tf.local_variables_initializer())
self.ckpt_loader = Ckpt(
session=session,
variables_to_restore=self.variables_to_restore,
include_scopes=args.checkpoint_include_scopes,
exclude_scopes=args.checkpoint_exclude_scopes,
ignore_missing_vars=args.ignore_missing_vars,
)
"logger": log,
}
for ckpt_path in ckpt_iterator(evaluator.watch_path, **kwargs):
log.info(f"[watch] {ckpt_path}")
evaluator.evaluate_once(ckpt_path)
else:
raise ValueError(f"Undefined valid_type: {args.valid_type}")
if __name__ == "__main__":
parser = argparse.ArgumentParser(description=__doc__)
subparsers = parser.add_subparsers(title="Model", description="")
Base.add_arguments(parser)
Evaluator.add_arguments(parser)
DataWrapperBase.add_arguments(parser)
AudioDataWrapper.add_arguments(parser)
TFModel.add_arguments(parser)
audio_nets.AudioNetModel.add_arguments(parser)
MetricManagerBase.add_arguments(parser)
for class_name in audio_nets._available_nets:
subparser = subparsers.add_parser(class_name)
subparser.add_argument("--model", default=class_name, type=str, help="DO NOT FIX ME")
add_audio_arguments = eval("audio_nets.{}.add_arguments".format(class_name))
add_audio_arguments(subparser)
args = parser.parse_args()