Merge branch 'develop' into freqai_bt_from_predictions_improvement

freqtrade/freqai/RL/BaseEnvironment.py

@@ -194,12 +194,12 @@ class BaseEnvironment(gym.Env):
         if self._position == Positions.Neutral:
             return 0.
         elif self._position == Positions.Short:
-            current_price = self.add_exit_fee(self.prices.iloc[self._current_tick].open)
-            last_trade_price = self.add_entry_fee(self.prices.iloc[self._last_trade_tick].open)
-            return (last_trade_price - current_price) / last_trade_price
-        elif self._position == Positions.Long:
             current_price = self.add_entry_fee(self.prices.iloc[self._current_tick].open)
             last_trade_price = self.add_exit_fee(self.prices.iloc[self._last_trade_tick].open)
+            return (last_trade_price - current_price) / last_trade_price
+        elif self._position == Positions.Long:
+            current_price = self.add_exit_fee(self.prices.iloc[self._current_tick].open)
+            last_trade_price = self.add_entry_fee(self.prices.iloc[self._last_trade_tick].open)
             return (current_price - last_trade_price) / last_trade_price
         else:
             return 0.

freqtrade/freqai/RL/BaseReinforcementLearningModel.py

@@ -64,7 +64,7 @@ class BaseReinforcementLearningModel(IFreqaiModel):
         self.policy_type = self.freqai_info['rl_config']['policy_type']
         self.unset_outlier_removal()
         self.net_arch = self.rl_config.get('net_arch', [128, 128])
-        self.dd.model_type = "stable_baselines"
+        self.dd.model_type = import_str
 
     def unset_outlier_removal(self):
         """

freqtrade/freqai/data_drawer.py

@@ -503,7 +503,7 @@ class FreqaiDataDrawer:
             dump(model, save_path / f"{dk.model_filename}_model.joblib")
         elif self.model_type == 'keras':
             model.save(save_path / f"{dk.model_filename}_model.h5")
-        elif 'stable_baselines' in self.model_type:
+        elif 'stable_baselines' in self.model_type or 'sb3_contrib' == self.model_type:
             model.save(save_path / f"{dk.model_filename}_model.zip")
 
         if dk.svm_model is not None:
@@ -589,9 +589,9 @@ class FreqaiDataDrawer:
         elif self.model_type == 'keras':
             from tensorflow import keras
             model = keras.models.load_model(dk.data_path / f"{dk.model_filename}_model.h5")
-        elif self.model_type == 'stable_baselines':
+        elif 'stable_baselines' in self.model_type or 'sb3_contrib' == self.model_type:
             mod = importlib.import_module(
-                'stable_baselines3', self.freqai_info['rl_config']['model_type'])
+                self.model_type, self.freqai_info['rl_config']['model_type'])
             MODELCLASS = getattr(mod, self.freqai_info['rl_config']['model_type'])
             model = MODELCLASS.load(dk.data_path / f"{dk.model_filename}_model")
 

freqtrade/main.py

@@ -7,6 +7,8 @@ import logging
 import sys
 from typing import Any, List
 
+from freqtrade.util.gc_setup import gc_set_threshold
+
 
 # check min. python version
 if sys.version_info < (3, 8):  # pragma: no cover
@@ -36,6 +38,7 @@ def main(sysargv: List[str] = None) -> None:
         # Call subcommand.
         if 'func' in args:
             logger.info(f'freqtrade {__version__}')
+            gc_set_threshold()
             return_code = args['func'](args)
         else:
             # No subcommand was issued.

freqtrade/util/gc_setup.py

@@ -0,0 +1,18 @@
+import gc
+import logging
+import platform
+
+
+logger = logging.getLogger(__name__)
+
+
+def gc_set_threshold():
+    """
+    Reduce number of GC runs to improve performance (explanation video)
+    https://www.youtube.com/watch?v=p4Sn6UcFTOU
+
+    """
+    if platform.python_implementation() == "CPython":
+        # allocs, g1, g2 = gc.get_threshold()
+        gc.set_threshold(50_000, 500, 1000)
+        logger.debug("Adjusting python allocations to reduce GC runs")