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Massively Parallel Deep Reinforcement Learning. 🔥

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While Running the last command on eRL_demo_StockTrading.ipynb on colab ```python args.init_before_training(if_main=False) args.env.draw_cumulative_return(args, torch) ``` ```error --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) in () ----> 1 args.env.draw_cumulative_return(args, torch) 2 frames...

bug

get error message "TypeError: __init__() got an unexpected keyword argument 'if_off_policy'" when I try to run eRL_demo_StockTrading.ipynb

bug

请教下AgentPPO中的explore_one_env中的splice list 的作用是什么 ` def explore_one_env(self, env, target_step): traj_temp = list() state = self.states[0] last_done = 0 for i in range(target_step): action, noise = [ary[0] for ary in self.select_actions((state,))] next_state,...

help_wanted

Great library and truly enjoyed using it. Experience would be ever so slightly better with a Baseline Model made to be used to compare with the other big brothers! Thanks...

Suggestion

Is there any guideline on how to log training metrics to Tensorboard? Is there something similar to callback mechanism in SB 3?

dicussion

Can you provide a test demo, reproduce the optimal policy and save the video? (e.g. for LunarLanderContinuous-v2 or BipedalWalker-v3)

Suggestion

First when installing FinRL ,i.e., executing !pip install git+https://github.com/AI4Finance-LLC/FinRL-Library.git I see the following error message: ERROR: pip's dependency resolver does not currently take into account all the packages that are...

bug

I have tried to solve this according to https://exerror.com/jsondecodeerror-expecting-value-line-1-column-1-char-0-yfinance/ but it still not work return complexjson.loads(self.text, **kwargs) File "/usr/local/Cellar/[email protected]/3.9.6/Frameworks/Python.framework/Versions/3.9/lib/python3.9/json/__init__.py", line 346, in loads return _default_decoder.decode(s) File "/usr/local/Cellar/[email protected]/3.9.6/Frameworks/Python.framework/Versions/3.9/lib/python3.9/json/decoder.py", line 337, in...

bug

In eRL_demo_PPOinSingleFile.py there are two _get_reward_sum_ functions: ``` def get_reward_sum_raw(self, buf_len, buf_reward, buf_mask, buf_value) -> (torch.Tensor, torch.Tensor): buf_r_sum = torch.empty(buf_len, dtype=torch.float32, device=self.device) # reward sum pre_r_sum = 0 for i...

dicussion

运行程序: args=Arguments(if_on_policy=False) args.agent=AgentDDPG() env=gym.make('Pendulum-v0') env.target_reward=-200 args.env=PreprocessEnv(env=env) args.reward_scale=2**-3 args.net_dim=2**7 args.batch_size=2**7 train_and_evaluate(args) 发生错误: File "F:/engine_research_20210901/ElegantRL/ElegantRL-master/elegantrl/run.py", line 717, in demo_continuous_action train_and_evaluate(args) File "F:/engine_research_20210901/ElegantRL/ElegantRL-master/elegantrl/run.py", line 190, in train_and_evaluate steps, r_exp = update_buffer(trajectory) File "F:/engine_research_20210901/ElegantRL/ElegantRL-master/elegantrl/run.py",...

bug