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)