Closed nkchem09 closed 3 years ago
Hello nkchem09 I'm getting the same error, were you able to solve it ?
Hi there, No, I am still can not solve it.
At 2021-04-19 02:37:16, "anuragsingh31" @.***> wrote:
Hello nkchem09 I'm getting the same error, were you able to solve it ?
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you can solve it by using
!pip install torch==1.4.0
Reason: If you ran !pip install git+https://github.com/AI4Finance-LLC/FinRL-Library.git you will see: torch>=1.4.0; as of 4 May 2021, torch version is ~1.8.0 (compatability issues, so u need to backtrack the pytorch installation)
Hope it helps1
Hello nkchem09 I'm getting the same error, were you able to solve it ?
you can solve it by using
!pip install torch==1.4.0
Reason: If you ran !pip install git+https://github.com/AI4Finance-LLC/FinRL-Library.git you will see: torch>=1.4.0; as of 4 May 2021, torch version is ~1.8.0 (compatability issues, so u need to backtrack the pytorch installation)
Hope it helps1
Thank you very much.
Best wishes.
Thanks for your great work.
I found a bug when running main.py on windows 10 using "CSI_300_TICKER" or other stocks.
The error is showing as follows:
Traceback (most recent call last): File "D:/worksPool/works2020/adair2020_W/some/S72/FinRL-Library-master/main.py", line 58, in
main()
File "D:/worksPool/works2020/adair2020_W/some/S72/FinRL-Library-master/main.py", line 38, in main
finrl.autotrain.training.train_one()
File "D:\worksPool\works2020\adair2020_W\some\S72\FinRL-Library-master\finrl\autotrain\training.py", line 109, in train_one
model=model_sac, tb_log_name="sac", total_timesteps=80000
File "D:\worksPool\works2020\adair2020_W\some\S72\FinRL-Library-master\finrl\model\models.py", line 124, in train_model
model = model.learn(total_timesteps=total_timesteps, tb_log_name=tb_log_name)
File "D:\py_envs\S72P2\lib\site-packages\stable_baselines3\sac\sac.py", line 291, in learn
reset_num_timesteps=reset_num_timesteps,
File "D:\py_envs\S72P2\lib\site-packages\stable_baselines3\common\off_policy_algorithm.py", line 273, in learn
log_interval=log_interval,
File "D:\py_envs\S72P2\lib\site-packages\stable_baselines3\common\off_policy_algorithm.py", line 469, in collect_rollouts
action, buffer_action = self._sample_action(learning_starts, action_noise)
File "D:\py_envs\S72P2\lib\site-packages\stable_baselines3\common\off_policy_algorithm.py", line 321, in _sample_action
unscaledaction, = self.predict(self._last_obs, deterministic=False)
File "D:\py_envs\S72P2\lib\site-packages\stable_baselines3\common\base_class.py", line 497, in predict
return self.policy.predict(observation, state, mask, deterministic)
File "D:\py_envs\S72P2\lib\site-packages\stable_baselines3\common\policies.py", line 276, in predict
actions = self._predict(observation, deterministic=deterministic)
File "D:\py_envs\S72P2\lib\site-packages\stable_baselines3\sac\policies.py", line 361, in _predict
return self.actor(observation, deterministic)
File "D:\py_envs\S72P2\lib\site-packages\torch\nn\modules\module.py", line 889, in _call_impl
result = self.forward(*input, kwargs)
File "D:\py_envs\S72P2\lib\site-packages\stable_baselines3\sac\policies.py", line 184, in forward
return self.action_dist.actions_from_params(mean_actions, log_std, deterministic=deterministic, kwargs)
File "D:\py_envs\S72P2\lib\site-packages\stable_baselines3\common\distributions.py", line 178, in actions_from_params
self.proba_distribution(mean_actions, log_std)
File "D:\py_envs\S72P2\lib\site-packages\stable_baselines3\common\distributions.py", line 210, in proba_distribution
super(SquashedDiagGaussianDistribution, self).proba_distribution(mean_actions, log_std)
File "D:\py_envs\S72P2\lib\site-packages\stable_baselines3\common\distributions.py", line 152, in proba_distribution
self.distribution = Normal(mean_actions, action_std)
File "D:\py_envs\S72P2\lib\site-packages\torch\distributions\normal.py", line 50, in init
super(Normal, self).init(batch_shape, validate_args=validate_args)
File "D:\py_envs\S72P2\lib\site-packages\torch\distributions\distribution.py", line 53, in init
raise ValueError("The parameter {} has invalid values".format(param))
ValueError: The parameter loc has invalid values
I am wondering, why the "DOW_30_TICKER" data can run, while other data can not.
Thank you for your help.