Small type and typo fixes in freqai_interface
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@ -61,19 +61,21 @@ class IFreqaiModel(ABC):
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self.config = config
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self.assert_config(self.config)
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self.freqai_info = config["freqai"]
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self.data_split_parameters = config.get("freqai", {}).get("data_split_parameters")
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self.model_training_parameters = config.get("freqai", {}).get("model_training_parameters")
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self.freqai_info: Dict[str, Any] = config["freqai"]
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self.data_split_parameters: Dict[str, Any] = config.get("freqai", {}).get(
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"data_split_parameters", {})
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self.model_training_parameters: Dict[str, Any] = config.get("freqai", {}).get(
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"model_training_parameters", {})
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self.feature_parameters = config.get("freqai", {}).get("feature_parameters")
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self.retrain = False
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self.first = True
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self.set_full_path()
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self.follow_mode = self.freqai_info.get("follow_mode", False)
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self.follow_mode: bool = self.freqai_info.get("follow_mode", False)
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self.dd = FreqaiDataDrawer(Path(self.full_path), self.config, self.follow_mode)
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self.lock = threading.Lock()
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self.identifier = self.freqai_info.get("identifier", "no_id_provided")
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self.identifier: str = self.freqai_info.get("identifier", "no_id_provided")
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self.scanning = False
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self.keras = self.freqai_info.get("keras", False)
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self.keras: bool = self.freqai_info.get("keras", False)
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if self.keras and self.freqai_info.get("feature_parameters", {}).get("DI_threshold", 0):
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self.freqai_info["feature_parameters"]["DI_threshold"] = 0
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logger.warning("DI threshold is not configured for Keras models yet. Deactivating.")
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@ -253,7 +255,7 @@ class IFreqaiModel(ABC):
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# get the model metadata associated with the current pair
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(_, trained_timestamp, return_null_array) = self.dd.get_pair_dict_info(metadata["pair"])
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# if the metadata doesnt exist, the follower returns null arrays to strategy
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# if the metadata doesn't exist, the follower returns null arrays to strategy
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if self.follow_mode and return_null_array:
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logger.info("Returning null array from follower to strategy")
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self.dd.return_null_values_to_strategy(dataframe, dk)
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@ -364,7 +366,7 @@ class IFreqaiModel(ABC):
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raise OperationalException(
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"Trying to access pretrained model with `identifier` "
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"but found different features furnished by current strategy."
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"Change `identifer` to train from scratch, or ensure the"
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"Change `identifier` to train from scratch, or ensure the"
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"strategy is furnishing the same features as the pretrained"
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"model"
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)
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@ -457,7 +459,7 @@ class IFreqaiModel(ABC):
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data_load_timerange: TimeRange,
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):
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"""
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Retreive data and train model in single threaded mode (only used if model directory is empty
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Retrieve data and train model in single threaded mode (only used if model directory is empty
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upon startup for dry/live )
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:param new_trained_timerange: TimeRange = the timerange to train the model on
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:param metadata: dict = strategy provided metadata
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