def feature_layer_op(self, inputs: Dict[str, Input]):
"""
Convert input tensorflow features into numeric
train features and metadata features by applying respective feature
transformation functions as specified in the FeatureConfig
Parameters
----------
inputs : dict
Dictionary of the inputs to the tensorflow keras model
Returns
-------
train_features : dict
Dict of feature tensors that are used for training
metadata_features : dict
Dictionary of feature tensors that can be used for
computing custom metrics and losses
"""
train_features, metadata_features = define_feature_layer(
feature_config=self.feature_config,
tfrecord_type=self.tfrecord_type,
feature_layer_map=self.feature_layer_map,
file_io=self.file_io,
)(inputs)
return train_features, metadata_features
def feature_layer_op(self, inputs: Dict[str, Input]):
"""
Apply feature layer functions on each of the tf.keras.Input
Args:
inputs: dictionary of keras input symbolic tensors
Returns:
train_features: dictionary of feature tensors that can be used for training
metadata_features: dictionary of feature tensors that can be used as additional metadata
"""
train_features, metadata_features = define_feature_layer(
feature_config=self.feature_config,
tfrecord_type=self.tfrecord_type,
feature_layer_map=self.feature_layer_map,
file_io=self.file_io,
)(inputs)
return train_features, metadata_features