def __init__(self, spec, global_nets=None):
self.spec = spec
self.index = self.spec['meta']['session']
util.set_random_seed(self.spec)
util.set_cuda_id(self.spec)
util.set_logger(self.spec, logger, 'session')
spec_util.save(spec, unit='session')
self.agent, self.env = make_agent_env(self.spec, global_nets)
with util.ctx_lab_mode('eval'): # env for eval
self.eval_env = make_env(self.spec)
self.agent.body.eval_env = self.eval_env
self.num_eval = ps.get(self.agent.spec, 'meta.num_eval')
self.warmup_epi = ps.get(self.agent.agent_spec, 'algorithm.warmup_epi') or -1
logger.info(util.self_desc(self))
def run_spec(spec, lab_mode):
'''Run a spec in lab_mode'''
os.environ['lab_mode'] = lab_mode
if lab_mode in TRAIN_MODES:
spec_util.save(spec) # first save the new spec
if lab_mode == 'dev':
spec = spec_util.override_dev_spec(spec)
if lab_mode == 'search':
spec_util.tick(spec, 'experiment')
Experiment(spec).run()
else:
spec_util.tick(spec, 'trial')
Trial(spec).run()
elif lab_mode in EVAL_MODES:
spec_util.tick(spec, 'session')
spec = spec_util.override_eval_spec(spec)
Session(spec).run()
else:
print("%s".format(EVAL_MODES))
raise ValueError(f'Unrecognizable lab_mode not of {TRAIN_MODES} or {EVAL_MODES}')
def __init__(self, spec):
self.spec = spec
self.index = self.spec['meta']['experiment']
util.set_logger(self.spec, logger, 'trial')
spec_util.save(spec, unit='experiment')
