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more cleanup

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This commit is contained in:
robcaulk 2022-05-23 09:55:58 +02:00
parent 3587bd82e1
commit ee3cdd0ffe
2 changed files with 9 additions and 14 deletions
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15
freqtrade/freqai/data_kitchen.py
View File

@ -690,8 +690,7 @@ class FreqaiDataKitchen:
return full_timerange
def check_if_new_training_required(self, trained_timerange: TimeRange,
metadata: dict,
timestamp: int = 0) -> Tuple[bool, TimeRange, int]:
metadata: dict) -> Tuple[bool, TimeRange]:
time = datetime.datetime.now(tz=datetime.timezone.utc).timestamp()
@ -708,21 +707,19 @@ class FreqaiDataKitchen:
trained_timerange.stopts = int(time)
retrain = True
timestamp = trained_timerange.stopts
if retrain:
coin, _ = metadata['pair'].split("/")
# set the new model_path
self.model_path = Path(self.full_path / str("sub-train" + "-" +
str(timestamp)))
str(int(trained_timerange.stopts))))
self.model_filename = "cb_" + coin.lower() + "_" + str(timestamp)
self.model_filename = "cb_" + coin.lower() + "_" + str(int(trained_timerange.stopts))
# this is not persistent at the moment TODO
self.freqai_config['live_trained_timerange'] = str(timestamp)
self.freqai_config['live_trained_timerange'] = str(int(trained_timerange.stopts))
# enables persistence, but not fully implemented into save/load data yer
self.data['live_trained_timerange'] = str(timestamp)
self.data['live_trained_timerange'] = str(int(trained_timerange.stopts))
return retrain, trained_timerange, timestamp
return retrain, trained_timerange
def download_new_data_for_retraining(self, timerange: TimeRange, metadata: dict) -> None:

8
freqtrade/freqai/freqai_interface.py
View File

@ -64,7 +64,6 @@ class IFreqaiModel(ABC):
self.training_on_separate_thread = False
self.retrain = False
self.first = True
self.timestamp = 0
if self.freqai_info['live_trained_timerange']:
self.new_trained_timerange = TimeRange.parse_timerange(
self.freqai_info['live_trained_timerange'])
@ -157,10 +156,9 @@ class IFreqaiModel(ABC):
if not self.training_on_separate_thread:
# this will also prevent other pairs from trying to train simultaneously.
(self.retrain,
self.new_trained_timerange,
self.timestamp) = self.dh.check_if_new_training_required(self.new_trained_timerange,
metadata,
timestamp=self.timestamp)
self.new_trained_timerange) = self.dh.check_if_new_training_required(
self.new_trained_timerange,
metadata)
else:
logger.info("FreqAI training a new model on background thread.")
self.retrain = False