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cheat flake8 for now until we can refactor save into the model class

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robcaulk 2023-03-14 21:13:30 +01:00 committed by Yinon Polak
parent 244662b1a4
commit fab505be1b
3 changed files with 4 additions and 4 deletions
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4
freqtrade/freqai/data_drawer.py
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@ -446,7 +446,7 @@ class FreqaiDataDrawer:
dump(model, save_path / f"{dk.model_filename}_model.joblib")
elif self.model_type == 'keras':
model.save(save_path / f"{dk.model_filename}_model.h5")
elif self.model_type in ["stable_baselines", "sb3_contrib", "pytorch"]:
elif self.model_type in ["stable_baselines3", "sb3_contrib", "pytorch"]:
model.save(save_path / f"{dk.model_filename}_model.zip")
if dk.svm_model is not None:
@ -496,7 +496,7 @@ class FreqaiDataDrawer:
dk.training_features_list = dk.data["training_features_list"]
dk.label_list = dk.data["label_list"]
def load_data(self, coin: str, dk: FreqaiDataKitchen) -> Any:
def load_data(self, coin: str, dk: FreqaiDataKitchen) -> Any: # noqa: C901
"""
loads all data required to make a prediction on a sub-train time range
:returns:

2
freqtrade/freqai/freqai_interface.py
View File

@ -563,7 +563,7 @@ class IFreqaiModel(ABC):
file_type = ".joblib"
elif self.dd.model_type == 'keras':
file_type = ".h5"
elif self.dd.model_type in ["stable_baselines", "sb3_contrib", "pytorch"]:
elif self.dd.model_type in ["stable_baselines3", "sb3_contrib", "pytorch"]:
file_type = ".zip"
path_to_modelfile = Path(dk.data_path / f"{dk.model_filename}_model{file_type}")

2
freqtrade/freqai/prediction_models/PyTorchClassifierMultiTarget.py
View File

@ -41,7 +41,7 @@ class PyTorchClassifierMultiTarget(BasePyTorchModel):
self.max_n_eval_batches: Optional[int] = model_training_params.get(
"max_n_eval_batches", None
)
self.model_kwargs: Dict = model_training_params.get("model_kwargs", {})
self.model_kwargs: Dict[str, any] = model_training_params.get("model_kwargs", {})
self.class_name_to_index = None
self.index_to_class_name = None