def train(self, args):
self.agent.start_interaction(self.envs, nlump=self.hps['nlumps'], dynamics=self.dynamics)
sess = tf.get_default_session()
self.save = functools.partial(save_variables, sess=sess)
self.load = functools.partial(load_variables, sess=sess)
checkdir = osp.join(logger.get_dir(), 'checkpoints')
os.makedirs(checkdir, exist_ok=True)
load_weights = args['load_weights']
start_nupdates = 0
if load_weights is not None:
load_path = osp.join(checkdir, load_weights)
start_nupdates = int(load_weights)
print('Loading checkpoint from %s ' % load_weights)
self.load(load_path)
while True:
info = self.agent.step()
if info['update']:
info['update']['n_updates'] += start_nupdates
info['update']['tcount'] += start_nupdates*args['nsteps_per_seg']*args['envs_per_process']
logger.logkvs(info['update'])
logger.dumpkvs()
if info['update']['n_updates'] % 10 == 0:
weights_index = info['update']['n_updates']
savepath = osp.join(checkdir, '%.5i'% weights_index)
print('Saving to', savepath)
self.save(savepath)
if self.agent.rollout.stats['tcount'] > self.num_timesteps:
break
self.agent.stop_interaction()
def train(self):
self.agent.start_interaction(self.envs,
nlump=self.hps['nlumps'],
dynamics=self.dynamics)
while True:
info = self.agent.step()
if info['update']:
logger.logkvs(info['update'])
logger.dumpkvs()
if self.agent.rollout.stats['tcount'] > self.num_timesteps:
break
self.agent.stop_interaction()
def train(self):
self.agent.start_interaction(self.envs,
nlump=self.hps['nlumps'],
dynamics=self.dynamics)
if self.hps['ckptpath'] is not None:
self.agent.restore_model(logdir=self.hps['ckptpath'],
exp_name=self.hps['exp_name'])
while True:
info = self.agent.step()
if info['update']:
logger.logkvs(info['update'])
logger.dumpkvs()
if info['update']['n_updates'] % 60 == 0:
self.agent.save_model(
logdir=logger.get_dir(),
exp_name=self.hps['exp_name'],
global_step=info['update']['n_updates'])
if self.agent.rollout.stats['tcount'] > self.num_timesteps:
break
self.agent.stop_interaction()
def train(self):
self.agent.start_interaction(self.envs,
nlump=self.hps['nlumps'],
dynamics=self.dynamics)
sess = tf.get_default_session()
self.save = functools.partial(save_variables, sess=sess)
while True:
info = self.agent.step()
if info['update']:
logger.logkvs(info['update'])
logger.dumpkvs()
if info['update']['n_updates'] % 10 == 0:
checkdir = osp.join(logger.get_dir(), 'checkpoints')
os.makedirs(checkdir, exist_ok=True)
savepath = osp.join(checkdir,
'%.5i' % info['update']['n_updates'])
print('Saving to', savepath)
self.save(savepath)
if self.agent.rollout.stats['tcount'] > self.num_timesteps:
break
self.agent.stop_interaction()
