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try limiting tb_logger to pytorch only (XGBoost still gets its callback)
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@@ -635,9 +635,11 @@ class IFreqaiModel(ABC):
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dk.find_features(unfiltered_dataframe)
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dk.find_labels(unfiltered_dataframe)
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self.tb_logger = TBLogger(dk.data_path)
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if self.dd.model_type == "pytorch":
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self.tb_logger = TBLogger(dk.data_path)
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model = self.train(unfiltered_dataframe, pair, dk)
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self.tb_logger.close()
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if self.dd.model_type == "pytorch":
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self.tb_logger.close()
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self.dd.pair_dict[pair]["trained_timestamp"] = trained_timestamp
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dk.set_new_model_names(pair, trained_timestamp)
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