lychiyu/freqtrade_origin
1
0
Fork 0
mirror of https://github.com/freqtrade/freqtrade.git synced 2024-09-20 01:21:11 +00:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity

remove union

Browse Source
This commit is contained in:
Aleksey Savin 2024-04-23 23:11:08 +00:00
parent 49487afc86
commit c5e68afb2c
1 changed files with 2 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
freqtrade/freqai/freqai_interface.py
View File

@ -5,7 +5,7 @@ from abc import ABC, abstractmethod
from collections import deque from collections import deque
from datetime import datetime, timezone from datetime import datetime, timezone
from pathlib import Path from pathlib import Path
from typing import Any, Dict, List, Literal, Optional, Tuple, Union from typing import Any, Dict, List, Literal, Optional, Tuple
import datasieve.transforms as ds import datasieve.transforms as ds
import numpy as np import numpy as np
@ -108,7 +108,6 @@ class IFreqaiModel(ABC):
self.data_provider: Optional[DataProvider] = None self.data_provider: Optional[DataProvider] = None
self.max_system_threads = max(int(psutil.cpu_count() * 2 - 2), 1) self.max_system_threads = max(int(psutil.cpu_count() * 2 - 2), 1)
self.can_short = True # overridden in start() with strategy.can_short self.can_short = True # overridden in start() with strategy.can_short
self.model: Union[Any, None] = None
if self.ft_params.get('principal_component_analysis', False) and self.continual_learning: if self.ft_params.get('principal_component_analysis', False) and self.continual_learning:
self.ft_params.update({'principal_component_analysis': False}) self.ft_params.update({'principal_component_analysis': False})
logger.warning('User tried to use PCA with continual learning. Deactivating PCA.') logger.warning('User tried to use PCA with continual learning. Deactivating PCA.')
@ -258,7 +257,7 @@ class IFreqaiModel(ABC):
self.dd.save_metric_tracker_to_disk() self.dd.save_metric_tracker_to_disk()
def _train_model(self, dataframe_train, pair, dk, tr_backtest) -> Union[Any, None]: def _train_model(self, dataframe_train, pair, dk, tr_backtest):
try: try:
self.tb_logger = get_tb_logger(self.dd.model_type, dk.data_path, self.tb_logger = get_tb_logger(self.dd.model_type, dk.data_path,
self.activate_tensorboard) self.activate_tensorboard)