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)