revert to using model_training_parameters
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@ -34,13 +34,15 @@ class PyTorchClassifierMultiTarget(BasePyTorchModel):
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"""
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super().__init__(**kwargs)
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trainer_kwargs = self.freqai_info.get("trainer_kwargs", {})
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self.n_hidden: int = trainer_kwargs.get("n_hidden", 1024)
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self.max_iters: int = trainer_kwargs.get("max_iters", 100)
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self.batch_size: int = trainer_kwargs.get("batch_size", 64)
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self.learning_rate: float = trainer_kwargs.get("learning_rate", 3e-4)
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self.max_n_eval_batches: Optional[int] = trainer_kwargs.get("max_n_eval_batches", None)
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self.model_kwargs: Dict = trainer_kwargs.get("model_kwargs", {})
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model_training_params = self.freqai_info.get("model_training_parameters", {})
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self.n_hidden: int = model_training_params.get("n_hidden", 1024)
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self.max_iters: int = model_training_params.get("max_iters", 100)
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self.batch_size: int = model_training_params.get("batch_size", 64)
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self.learning_rate: float = model_training_params.get("learning_rate", 3e-4)
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self.max_n_eval_batches: Optional[int] = model_training_params.get(
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"max_n_eval_batches", None
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)
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self.model_kwargs: Dict = model_training_params.get("model_kwargs", {})
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self.class_name_to_index = None
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self.index_to_class_name = None
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