87c962eb21167aa6ab80f7dd6654b1e89deff9e1,ludwig/models/model.py,Model,batch_evaluation,#Model#Any#Any#Any#Any#Any#Any#Any#Any#Any#,919

Before Change

        while not batcher.last_batch():
            batch = batcher.next_batch()
            result = session.run(
                output_nodes,
                feed_dict=self.feed_dict(
                    batch,
                    regularization_lambda=regularization_lambda,
                    dropout_rate=0.0,
                    is_training=is_training
                )
            )

            output_stats, seq_set_size = self.update_output_stats_batch(
                output_stats,
                seq_set_size,

After Change

            // create array for target
            // is there more than one target
            if len(self.hyperparameters["output_features"]) > 1:
                target = reduce(lambda x, y: np.vstack((x, y)),
                                [batch[f["name"]] for f in
                                 self.hyperparameters["output_features"]]).T
            else:
                target = batch[
                    self.hyperparameters["output_features"][0]["name"]]

Instances