def __init__(self, scoring_key, model_config, loss_type): self.scoring_key = scoring_key self.model_config = model_config self.loss_type = loss_type self.architecture_op = architecture_factory.get_architecture( model_config=model_config)
def architecture_op(self, train_features, metadata_features): """ Define and apply the architecture of the model to produce scores from transformed features produced by the InteractionModel Parameters ---------- train_features : Tensor object Dense feature tensor object that is used to compute the model score metadata_features : dict of tensor objects Dictionary of tensor objects that are not used for training, but can be used for computing loss and metrics Returns ------- scores : Tensor object Tensor object of the score computed by the model """ return architecture_factory.get_architecture( model_config=self.model_config, feature_config=self.feature_config, file_io=self.file_io, )(train_features, metadata_features)
def architecture_op(self, train_features, metadata_features): return architecture_factory.get_architecture( model_config=self.model_config, feature_config=self.feature_config, file_io=self.file_io, )(train_features)