more cleanup
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3587bd82e1
commit
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@ -690,8 +690,7 @@ class FreqaiDataKitchen:
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return full_timerange
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return full_timerange
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def check_if_new_training_required(self, trained_timerange: TimeRange,
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def check_if_new_training_required(self, trained_timerange: TimeRange,
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metadata: dict,
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metadata: dict) -> Tuple[bool, TimeRange]:
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timestamp: int = 0) -> Tuple[bool, TimeRange, int]:
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time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp()
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time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp()
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@ -708,21 +707,19 @@ class FreqaiDataKitchen:
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trained_timerange.stopts = int(time)
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trained_timerange.stopts = int(time)
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retrain = True
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retrain = True
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timestamp = trained_timerange.stopts
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if retrain:
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if retrain:
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coin, _ = metadata['pair'].split("/")
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coin, _ = metadata['pair'].split("/")
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# set the new model_path
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# set the new model_path
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self.model_path = Path(self.full_path / str("sub-train" + "-" +
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self.model_path = Path(self.full_path / str("sub-train" + "-" +
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str(timestamp)))
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str(int(trained_timerange.stopts))))
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self.model_filename = "cb_" + coin.lower() + "_" + str(timestamp)
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self.model_filename = "cb_" + coin.lower() + "_" + str(int(trained_timerange.stopts))
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# this is not persistent at the moment TODO
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# this is not persistent at the moment TODO
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self.freqai_config['live_trained_timerange'] = str(timestamp)
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self.freqai_config['live_trained_timerange'] = str(int(trained_timerange.stopts))
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# enables persistence, but not fully implemented into save/load data yer
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# enables persistence, but not fully implemented into save/load data yer
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self.data['live_trained_timerange'] = str(timestamp)
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self.data['live_trained_timerange'] = str(int(trained_timerange.stopts))
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return retrain, trained_timerange, timestamp
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return retrain, trained_timerange
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def download_new_data_for_retraining(self, timerange: TimeRange, metadata: dict) -> None:
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def download_new_data_for_retraining(self, timerange: TimeRange, metadata: dict) -> None:
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@ -64,7 +64,6 @@ class IFreqaiModel(ABC):
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self.training_on_separate_thread = False
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self.training_on_separate_thread = False
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self.retrain = False
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self.retrain = False
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self.first = True
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self.first = True
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self.timestamp = 0
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if self.freqai_info['live_trained_timerange']:
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if self.freqai_info['live_trained_timerange']:
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self.new_trained_timerange = TimeRange.parse_timerange(
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self.new_trained_timerange = TimeRange.parse_timerange(
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self.freqai_info['live_trained_timerange'])
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self.freqai_info['live_trained_timerange'])
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@ -157,10 +156,9 @@ class IFreqaiModel(ABC):
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if not self.training_on_separate_thread:
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if not self.training_on_separate_thread:
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# this will also prevent other pairs from trying to train simultaneously.
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# this will also prevent other pairs from trying to train simultaneously.
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(self.retrain,
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(self.retrain,
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self.new_trained_timerange,
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self.new_trained_timerange) = self.dh.check_if_new_training_required(
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self.timestamp) = self.dh.check_if_new_training_required(self.new_trained_timerange,
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self.new_trained_timerange,
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metadata,
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metadata)
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timestamp=self.timestamp)
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else:
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else:
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logger.info("FreqAI training a new model on background thread.")
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logger.info("FreqAI training a new model on background thread.")
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self.retrain = False
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self.retrain = False
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