fb47e1487886b33181b459dfe91b67e20a96b8f7,finetune/target_models/comparison_regressor.py,ComparisonRegressor,_target_model,#ComparisonRegressor#,38

Before Change

        return ComparisonRegressionPipeline(self.config)

    def _target_model(self, *, config, featurizer_state, targets, n_outputs, train=False, reuse=None, **kwargs):
        super(ComparisonRegressor, self)._target_model(
            config=config, featurizer_state=featurizer_state, targets=targets, n_outputs=n_outputs,
            train=train, reuse=reuse, **kwargs)
        featurizer_state["sequence_features"] = tf.abs(tf.reduce_sum(featurizer_state["sequence_features"], 1))
        featurizer_state["features"] = tf.abs(tf.reduce_sum(featurizer_state["features"], 1))
        return regressor(
            hidden=featurizer_state["features"],

After Change

        featurizer_state["features"] = tf.abs(tf.reduce_sum(featurizer_state["features"], 1))
        if "context" in featurizer_state:
            featurizer_state["context"] = tf.abs(tf.reduce_sum(featurizer_state["context"], 1))
        self._add_context_embed(featurizer_state)
        return regressor(
            hidden=featurizer_state["features"],
            targets=targets, 
            n_targets=n_outputs,

Instances