Fix exceptions when training fails
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e3e4fbd5ba
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@ -104,6 +104,7 @@ class IFreqaiModel(ABC):
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self.data_provider: Optional[DataProvider] = None
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self.data_provider: Optional[DataProvider] = None
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self.max_system_threads = max(int(psutil.cpu_count() * 2 - 2), 1)
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self.max_system_threads = max(int(psutil.cpu_count() * 2 - 2), 1)
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self.can_short = True # overridden in start() with strategy.can_short
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self.can_short = True # overridden in start() with strategy.can_short
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self.model: Any = None
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record_params(config, self.full_path)
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record_params(config, self.full_path)
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@ -338,13 +339,14 @@ class IFreqaiModel(ABC):
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except Exception as msg:
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except Exception as msg:
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logger.warning(
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logger.warning(
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f"Training {pair} raised exception {msg.__class__.__name__}. "
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f"Training {pair} raised exception {msg.__class__.__name__}. "
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f"Message: {msg}, skipping.")
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f"Message: {msg}, skipping.", exc_info=True)
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self.model = None
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self.dd.pair_dict[pair]["trained_timestamp"] = int(
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self.dd.pair_dict[pair]["trained_timestamp"] = int(
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tr_train.stopts)
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tr_train.stopts)
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if self.plot_features:
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if self.plot_features and self.model is not None:
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plot_feature_importance(self.model, pair, dk, self.plot_features)
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plot_feature_importance(self.model, pair, dk, self.plot_features)
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if self.save_backtest_models:
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if self.save_backtest_models and self.model is not None:
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logger.info('Saving backtest model to disk.')
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logger.info('Saving backtest model to disk.')
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self.dd.save_data(self.model, pair, dk)
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self.dd.save_data(self.model, pair, dk)
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else:
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else:
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