Merge branch 'move-disk-writing-to-ram' into add-metric-tracker
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commit
3b4402aaab
@ -66,6 +66,8 @@ class FreqaiDataDrawer:
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self.pair_dict: Dict[str, pair_info] = {}
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self.pair_dict: Dict[str, pair_info] = {}
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# dictionary holding all actively inferenced models in memory given a model filename
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# dictionary holding all actively inferenced models in memory given a model filename
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self.model_dictionary: Dict[str, Any] = {}
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self.model_dictionary: Dict[str, Any] = {}
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# all additional metadata that we want to keep in ram
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self.meta_data_dictionary: Dict[str, Dict[str, Any]] = {}
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self.model_return_values: Dict[str, DataFrame] = {}
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self.model_return_values: Dict[str, DataFrame] = {}
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self.historic_data: Dict[str, Dict[str, DataFrame]] = {}
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self.historic_data: Dict[str, Dict[str, DataFrame]] = {}
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self.historic_predictions: Dict[str, DataFrame] = {}
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self.historic_predictions: Dict[str, DataFrame] = {}
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@ -504,9 +506,14 @@ class FreqaiDataDrawer:
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)
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)
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# if self.live:
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# if self.live:
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# store as much in ram as possible to increase performance
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self.model_dictionary[coin] = model
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self.model_dictionary[coin] = model
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self.pair_dict[coin]["model_filename"] = dk.model_filename
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self.pair_dict[coin]["model_filename"] = dk.model_filename
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self.pair_dict[coin]["data_path"] = str(dk.data_path)
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self.pair_dict[coin]["data_path"] = str(dk.data_path)
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if coin not in self.meta_data_dictionary:
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self.meta_data_dictionary[coin] = {}
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self.meta_data_dictionary[coin]["train_df"] = dk.data_dictionary["train_features"]
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self.meta_data_dictionary[coin]["meta_data"] = dk.data
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self.save_drawer_to_disk()
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self.save_drawer_to_disk()
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return
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return
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@ -543,14 +550,19 @@ class FreqaiDataDrawer:
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/ dk.data_path.parts[-1]
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/ dk.data_path.parts[-1]
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)
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)
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with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp:
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if coin in self.meta_data_dictionary:
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dk.data = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
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dk.data = self.meta_data_dictionary[coin]["meta_data"]
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dk.training_features_list = dk.data["training_features_list"]
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dk.data_dictionary["train_features"] = self.meta_data_dictionary[coin]["train_df"]
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dk.label_list = dk.data["label_list"]
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else:
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with open(dk.data_path / f"{dk.model_filename}_metadata.json", "r") as fp:
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dk.data = rapidjson.load(fp, number_mode=rapidjson.NM_NATIVE)
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dk.data_dictionary["train_features"] = pd.read_pickle(
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dk.data_dictionary["train_features"] = pd.read_pickle(
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dk.data_path / f"{dk.model_filename}_trained_df.pkl"
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dk.data_path / f"{dk.model_filename}_trained_df.pkl"
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)
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)
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dk.training_features_list = dk.data["training_features_list"]
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dk.label_list = dk.data["label_list"]
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# try to access model in memory instead of loading object from disk to save time
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# try to access model in memory instead of loading object from disk to save time
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if dk.live and coin in self.model_dictionary:
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if dk.live and coin in self.model_dictionary:
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