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

Merge d7b86ee436 into c28446dad0

Browse Source
This commit is contained in:
Alxy Savin 2024-09-18 04:52:20 +02:00 committed by GitHub
commit 12ef588bd6
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 35 additions and 29 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

64
freqtrade/freqai/freqai_interface.py
View File

@ -70,7 +70,7 @@ class IFreqaiModel(ABC):
self.retrain = False
self.first = True
self.set_full_path()
self.save_backtest_models: bool = self.freqai_info.get("save_backtest_models", True)
self.save_backtest_models: bool = self.freqai_info.get("save_backtest_models", False)
if self.save_backtest_models:
logger.info("Backtesting module configured to save all models.")
@ -258,6 +258,23 @@ class IFreqaiModel(ABC):
if self.freqai_info.get("write_metrics_to_disk", False):
self.dd.save_metric_tracker_to_disk()
def _train_model(self, dataframe_train, pair, dk, tr_backtest):
try:
self.tb_logger = get_tb_logger(
self.dd.model_type, dk.data_path, self.activate_tensorboard
)
model = self.train(dataframe_train, pair, dk)
self.tb_logger.close()
return model
except Exception as msg:
logger.warning(
f"Training {pair} raised exception {msg.__class__.__name__}. "
f"from {tr_backtest.start_fmt} to {tr_backtest.stop_fmt}."
f"Message: {msg}, skipping.",
exc_info=True,
)
return None
def start_backtesting(
self, dataframe: DataFrame, metadata: dict, dk: FreqaiDataKitchen, strategy: IStrategy
) -> FreqaiDataKitchen:
@ -352,37 +369,26 @@ class IFreqaiModel(ABC):
if not self.model_exists(dk):
dk.find_features(dataframe_train)
dk.find_labels(dataframe_train)
self.model = self._train_model(dataframe_train, pair, dk, tr_backtest)
try:
self.tb_logger = get_tb_logger(
self.dd.model_type, dk.data_path, self.activate_tensorboard
)
self.model = self.train(dataframe_train, pair, dk)
self.tb_logger.close()
except Exception as msg:
logger.warning(
f"Training {pair} raised exception {msg.__class__.__name__}. "
f"Message: {msg}, skipping.",
exc_info=True,
)
self.model = None
self.dd.pair_dict[pair]["trained_timestamp"] = int(tr_train.stopts)
if self.plot_features and self.model is not None:
plot_feature_importance(self.model, pair, dk, self.plot_features)
if self.save_backtest_models and self.model is not None:
logger.info("Saving backtest model to disk.")
self.dd.save_data(self.model, pair, dk)
else:
logger.info("Saving metadata to disk.")
self.dd.save_metadata(dk)
if self.model:
self.dd.pair_dict[pair]["trained_timestamp"] = int(tr_train.stopts)
if self.plot_features and self.model is not None:
plot_feature_importance(self.model, pair, dk, self.plot_features)
if self.save_backtest_models and self.model is not None:
logger.info("Saving backtest model to disk.")
self.dd.save_data(self.model, pair, dk)
else:
logger.info("Saving metadata to disk.")
self.dd.save_metadata(dk)
else:
self.model = self.dd.load_data(pair, dk)
pred_df, do_preds = self.predict(dataframe_backtest, dk)
append_df = dk.get_predictions_to_append(pred_df, do_preds, dataframe_backtest)
dk.append_predictions(append_df)
dk.save_backtesting_prediction(append_df)
if self.model and len(dataframe_backtest):
pred_df, do_preds = self.predict(dataframe_backtest, dk)
append_df = dk.get_predictions_to_append(pred_df, do_preds, dataframe_backtest)
dk.append_predictions(append_df)
dk.save_backtesting_prediction(append_df)
self.backtesting_fit_live_predictions(dk)
dk.fill_predictions(dataframe)
@ -829,7 +835,7 @@ class IFreqaiModel(ABC):
:param pair: current pair
:return: if the data exists or not
"""
if self.config.get("freqai_backtest_live_models", False) and len_dataframe_backtest == 0:
if len_dataframe_backtest == 0:
logger.info(
f"No data found for pair {pair} from "
f"from {tr_backtest.start_fmt} to {tr_backtest.stop_fmt}. "