FinRL_Compare_ElegantRL_RLlib_Stablebaseline3 BUGs!

ElegantRL and RLlib Training:

ValueError Traceback (most recent call last)
Cell In [28], line 4
1 #demo for rllib
2 ray.shutdown() #always shutdown previous session if any
----> 4 train(start_date = TRAIN_START_DATE,
5 end_date = TRAIN_END_DATE,
6 ticker_list = config_tickers.DOW_30_TICKER,
7 data_source = 'yahoofinance',
8 time_interval= '1D',
9 technical_indicator_list= INDICATORS,
10 drl_lib='rllib',
11 env=env,
12 model_name='ppo',
13 cwd='./test_ppo',
14 rllib_params = RLlib_PARAMS,
15 total_episodes=30)

Cell In [10], line 12, in train(start_date, end_date, ticker_list, data_source, time_interval, technical_indicator_list, drl_lib, env, model_name, if_vix, **kwargs)
10 if if_vix:
11 data = DP.add_vix(data)
---> 12 price_array, tech_array, turbulence_array = DP.df_to_array(data, if_vix)
13 env_config = {'price_array':price_array,
14 'tech_array':tech_array,
15 'turbulence_array':turbulence_array,
16 'if_train':True}
17 env_instance = env(config=env_config)

File /usr/local/lib/python3.10/site-packages/finrl/meta/data_processor.py:68, in DataProcessor.df_to_array(self, df, if_vix)
67 def df_to_array(self, df, if_vix) -> np.array:
---> 68 price_array, tech_array, turbulence_array = self.processor.df_to_array(
69 df, self.tech_indicator_list, if_vix
70 )
71 # fill nan and inf values with 0 for technical indicators
72 tech_nan_positions = np.isnan(tech_array)

File /usr/local/lib/python3.10/site-packages/finrl/meta/data_processors/processor_yahoofinance.py:311, in YahooFinanceProcessor.df_to_array(self, df, tech_indicator_list, if_vix)
309 if_first_time = False
310 else:
--> 311 price_array = np.hstack(
312 [price_array, df[df.tic == tic][["adjcp"]].values]
313 )
314 tech_array = np.hstack(
315 [tech_array, df[df.tic == tic][tech_indicator_list].values]
316 )
317 assert price_array.shape[0] == tech_array.shape[0]

File <__array_function__ internals>:180, in hstack(*args, **kwargs)

File /usr/local/lib/python3.10/site-packages/numpy/core/shape_base.py:345, in hstack(tup)
343 return _nx.concatenate(arrs, 0)
344 else:
--> 345 return _nx.concatenate(arrs, 1)

File <__array_function__ internals>:180, in concatenate(*args, **kwargs)

ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 0, the array at index 0 has size 1657 and the array at index 1 has size 1656

RLlib Testing:

AttributeError Traceback (most recent call last)
Cell In [29], line 3
1 ray.shutdown() #always shutdown previous session if any
----> 3 account_value_rllib = test(start_date = TEST_START_DATE,
4 end_date = TEST_END_DATE,
5 ticker_list = config_tickers.DOW_30_TICKER,
6 data_source = 'yahoofinance',
7 time_interval= '1D',
8 technical_indicator_list= INDICATORS,
9 drl_lib='rllib',
10 env=env,
11 model_name='ppo',
12 cwd='./test_ppo/checkpoint_000030/checkpoint-30',
13 rllib_params = RLlib_PARAMS)

Cell In [11], line 35, in test(start_date, end_date, ticker_list, data_source, time_interval, technical_indicator_list, drl_lib, env, model_name, if_vix, **kwargs)
31 return episode_total_assets
33 elif drl_lib == 'rllib':
34 #load agent
---> 35 episode_total_assets = DRLAgent_rllib.DRL_prediction(
36 model_name=model_name,
37 env = env,
38 price_array=price_array,
39 tech_array=tech_array,
40 turbulence_array=turbulence_array,
41 agent_path = cwd)
43 return episode_total_assets
45 elif drl_lib == 'stable_baselines3':

File /usr/local/lib/python3.10/site-packages/finrl/agents/rllib/models.py:148, in DRLAgent.DRL_prediction(model_name, env, price_array, tech_array, turbulence_array, agent_path)
146 # ray.init() # Other Ray APIs will not work until `ray.init()` is called.
147 if model_name == "ppo":
--> 148 trainer = MODELS[model_name].PPOTrainer(env=env, config=model_config)
149 elif model_name == "a2c":
150 trainer = MODELS[model_name].A2CTrainer(env=env, config=model_config)

AttributeError: module 'ray.rllib.algorithms.ppo.ppo' has no attribute 'PPOTrainer'