def maybe_save_model(savedir, state):
"""This function checkpoints the model and state of the training algorithm."""
if savedir is None:
return
start_time = time.time()
model_dir = "model-{}".format(state["num_iters"])
U.save_state(os.path.join(savedir, model_dir, "saved"))
relatively_safe_pickle_dump(state, os.path.join(savedir, 'training_state.pkl.zip'), compression=True)
relatively_safe_pickle_dump(state["monitor_state"], os.path.join(savedir, 'monitor_state.pkl'))
logger.log("Saved model in {} seconds\n".format(time.time() - start_time))
def maybe_save_model(savedir, container, state):
"""This function checkpoints the model and state of the training algorithm."""
if savedir is None:
return
start_time = time.time()
model_dir = "model-{}".format(state["num_iters"])
U.save_state(os.path.join(savedir, model_dir, "saved"))
if container is not None:
container.put(os.path.join(savedir, model_dir), model_dir)
relatively_safe_pickle_dump(state, os.path.join(savedir, 'training_state.pkl.zip'), compression=True)
if container is not None:
container.put(os.path.join(savedir, 'training_state.pkl.zip'), 'training_state.pkl.zip')
relatively_safe_pickle_dump(state["monitor_state"], os.path.join(savedir, 'monitor_state.pkl'))
if container is not None:
container.put(os.path.join(savedir, 'monitor_state.pkl'), 'monitor_state.pkl')
logger.log("Saved model in {} seconds\n".format(time.time() - start_time))
def save(self, path, session):
"""This function checkpoints the model and state of the training algorithm."""
if path is None:
return
state = {
# 'replay_buffer': self.replay_buffer,
'num_iters': self.num_iters,
# 'monitor_state': monitored_env.get_state(),
}
start_time = time.time()
model_dir = "model-{}".format(state["num_iters"])
U.save_state(os.path.join(path, model_dir, "saved"), session=session)
relatively_safe_pickle_dump(state, os.path.join(path, 'training_state.pkl.zip'), compression=True)
# relatively_safe_pickle_dump(state["monitor_state"], os.path.join(path, 'monitor_state.pkl'))
logger.log("Saved model in {} seconds\n".format(time.time() - start_time))
def maybe_save_model(savedir, container, state, rewards, steps):
"""This function checkpoints the model and state of the training algorithm."""
if savedir is None:
return
start_time = time.time()
model_dir = "model-{}".format(state["num_iters"])
U.save_state(os.path.join(savedir, model_dir, "saved"))
if container is not None:
container.put(os.path.join(savedir, model_dir), model_dir)
relatively_safe_pickle_dump(state,
os.path.join(savedir,
'training_state.pkl.zip'),
compression=True)
if container is not None:
container.put(os.path.join(savedir, 'training_state.pkl.zip'),
'training_state.pkl.zip')
# relatively_safe_pickle_dump(state["monitor_state"], os.path.join(savedir, 'monitor_state.pkl'))
# if container is not None:
# container.put(os.path.join(savedir, 'monitor_state.pkl'), 'monitor_state.pkl')
relatively_safe_pickle_dump(rewards, os.path.join(savedir, 'rewards.pkl'))
if container is not None:
container.put(os.path.join(savedir, 'rewards.pkl'), 'rewards.pkl')
relatively_safe_pickle_dump(steps, os.path.join(savedir, 'steps.pkl'))
if container is not None:
container.put(os.path.join(savedir, 'steps.pkl'), 'steps.pkl')
plotly_plot(rewards, os.path.join(savedir, 'returns.html'))
logger.log("Saved model in {} seconds\n".format(time.time() - start_time))
def maybe_save_model(savedir, container, state):
u"""This function checkpoints the model and state of the training algorithm."""
if savedir is None:
return
start_time = time.time()
model_dir = u"model-{}".format(state[u"num_iters"])
save_state(os.path.join(savedir, model_dir, u"saved"))
if container is not None:
container.put(os.path.join(savedir, model_dir), model_dir)
relatively_safe_pickle_dump(state,
os.path.join(savedir,
u'training_state.pkl.zip'),
compression=True)
if container is not None:
container.put(os.path.join(savedir, u'training_state.pkl.zip'),
u'training_state.pkl.zip')
relatively_safe_pickle_dump(state[u"monitor_state"],
os.path.join(savedir, u'monitor_state.pkl'))
if container is not None:
container.put(os.path.join(savedir, u'monitor_state.pkl'),
u'monitor_state.pkl')
logger.log(u"Saved model in {} seconds\n".format(time.time() - start_time))
def save_model(dict_state):
save_state("saved_model/model.ckpt")
relatively_safe_pickle_dump(dict_state, "saved_model/model_state.pkl.zip", compression=True)
