lychiyu/freqtrade_origin
1
0
Fork 0
mirror of https://github.com/freqtrade/freqtrade.git synced 2024-11-10 10:21:59 +00:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

fix tensorboard path so that users can track all historical models

Browse Source
This commit is contained in:
robcaulk 2022-08-31 16:50:39 +02:00
parent 2493e0c8a5
commit 240b529533
3 changed files with 6 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
config_examples/config_freqai-rl.example.json
View File

@ -72,8 +72,8 @@
"5m",
"30m"
],
"indicator_max_period_candles": 10,
"indicator_periods_candles": [5]
"indicator_max_period_candles": 20,
"indicator_periods_candles": [14]
},
"data_split_parameters": {
"test_size": 0.5,

4
freqtrade/freqai/prediction_models/ReinforcementLearner.py
View File

@ -28,14 +28,14 @@ class ReinforcementLearner(BaseReinforcementLearningModel):
if dk.pair not in self.dd.model_dictionary or not self.continual_learning:
model = self.MODELCLASS(self.policy_type, self.train_env, policy_kwargs=policy_kwargs,
tensorboard_log=Path(dk.data_path / "tensorboard"),
tensorboard_log=Path(
dk.full_path / "tensorboard" / dk.pair.split('/')[0]),
**self.freqai_info['model_training_parameters']
)
else:
logger.info('Continual training activated - starting training from previously '
'trained agent.')
model = self.dd.model_dictionary[dk.pair]
model.tensorboard_log = Path(dk.data_path / "tensorboard")
model.set_env(self.train_env)
model.learn(

4
freqtrade/freqai/prediction_models/ReinforcementLearner_multiproc.py
View File

@ -31,14 +31,14 @@ class ReinforcementLearner_multiproc(BaseReinforcementLearningModel):
if dk.pair not in self.dd.model_dictionary or not self.continual_learning:
model = self.MODELCLASS(self.policy_type, self.train_env, policy_kwargs=policy_kwargs,
tensorboard_log=Path(dk.full_path / "tensorboard"),
tensorboard_log=Path(
dk.full_path / "tensorboard" / dk.pair.split('/')[0]),
**self.freqai_info['model_training_parameters']
)
else:
logger.info('Continual learning activated - starting training from previously '
'trained agent.')
model = self.dd.model_dictionary[dk.pair]
model.tensorboard_log = Path(dk.data_path / "tensorboard")
model.set_env(self.train_env)
model.learn(