def test_agent_main(agent,
config,
training_procedure=regular_train_agent_procedure):
from configs.arguments import parse_arguments
args = parse_arguments(f'{type(agent)}', config)
if 'CONFIG' in args.__dict__.keys() and args.__dict__['CONFIG']:
import importlib.util
spec = importlib.util.spec_from_file_location('overloaded.config',
args.__dict__['CONFIG'])
config = importlib.util.module_from_spec(spec)
spec.loader.exec_module(config)
else:
for key, arg in args.__dict__.items():
if key != 'CONFIG':
setattr(config, key, arg)
U.sprint(f'\nUsing config: {config}\n', highlight=True, color='yellow')
if not args.skip_confirmation:
for key, arg in U.get_upper_vars_of(config).items():
print(f'{key} = {arg}')
input('\nPress Enter to begin... ')
try:
training_procedure(agent, config)
except KeyboardInterrupt:
print('Stopping')
torch.cuda.empty_cache()
def set_config_attributes(self, config, **kwargs) -> None:
if config:
config_vars = U.get_upper_vars_of(config)
self.__check_for_duplicates_in_args(**config_vars)
self.__parse_set_attr(**config_vars)
self.__parse_set_attr(**kwargs)
LOG_DIRECTORY=C.LOG_DIRECTORY)
U.save_model(_trained_model, config)
env.close()
if __name__ == '__main__':
import experiments.continuous.c2d_config as C
from configs.arguments import parse_arguments
args = parse_arguments('C2D', C)
for key, arg in args.__dict__.items():
setattr(C, key, arg)
U.sprint(f'\nUsing config: {C}\n', highlight=True, color='yellow')
if not args.skip_confirmation:
for key, arg in U.get_upper_vars_of(C).items():
print(f'{key} = {arg}')
input('\nPress Enter to begin... ')
_agent = C.AGENT_TYPE(C)
try:
train_agent(C, _agent)
except KeyboardInterrupt:
print('Stopping')
torch.cuda.empty_cache()
def to_dict(C):
return U.get_upper_vars_of(C)