- 000
Do you have an example code that single-leaner + multi-envs ?
- 000
I have cuda installed. I have given "device": "cuda" in params but I am still getting using cpu device.
A2C_PARAMS = {"n_steps": 5, "ent_coef": 0.01, "learning_rate": 0.0005, "device": "cuda"}
output:
{'n_steps': 5, 'ent_coef': 0.01, 'learning_rate': 0.0005, 'device': 'cuda'}
Using cpu device
Loggin...
- 000
Describe the bug
Thank you for wonderful OpenSource project!
The installation guide here, which uses pip install ., can install pytorch cpu version. If this is the case, users cannot use gpu when training.
I think it would be better to instruct users that the below pytorch install might be required...
- 000
Run Stock_NeurIPS2018_2_Train.ipynb in FinRL/examples
Colab report error
thanks!
- 000
Describe the bug
I am getting the following error when I run the command "pip install git+https://github.com/AI4Finance-Foundation/FinRL.git". Same error when running pip install wrds
Compiler for C supports arguments -Wno-unused-but-set-variable: NO
Compiler for C supports arguments -Wno-unused-fun...
- 000
Hi All,
I'm trying to train an agent from ElegantRL in StockTradingEnv on Windows11 using Jupiterlab. I'm using the codes from 'FinRL: Compare ElegantRL, RLlib, and Stablebaselines3'.
When arriving at running the 'train' function I get the following error: EvaluatorProc.init() missing 1 required pos...
- 000
after #1007 Update processor_alpaca.py
Run FinRL_PaperTrading_Demo.ipynb in FinRL/examples/
colab reports an error
thanks!
- 000
In running the following code in google colab for Stock_NeurIPS2018_SB3.ipynb
env_train, _ = e_train_gym.get_sb_env()
I get the following error. Seems related to gym version.
Gynasium 0.28.1 is installed.
TypeError Traceback (most recent call last)
in <cell line:...
- 000
Describe the bug
The bugs occur in Part 2 Train the agent while running train cell.
The error message is ValueError: Too many values to unplack (expected 4) occurs in function explore_env. Here is the message:
ValueError Traceback (most recent call last)
in <cell l...