def _coordinate_eval()

in torchbiggraph/train_cpu.py [0:0]

• 26 lines of code
• 3 McCabe index (conditional complexity)

    def _coordinate_eval(self, edges, eval_edge_idxs) -> Optional[Stats]:
        eval_batch_size = round_up_to_nearest_multiple(
            self.config.batch_size, self.config.eval_num_batch_negs
        )
        if eval_edge_idxs is not None:
            self.bucket_logger.debug("Waiting for workers to perform evaluation")
            future_all_eval_stats = self.pool.map_async(
                call,
                [
                    partial(
                        process_in_batches,
                        batch_size=eval_batch_size,
                        model=self.model,
                        batch_processor=self.evaluator,
                        edges=edges,
                        indices=eval_edge_idxs[s],
                    )
                    for s in split_almost_equally(
                        eval_edge_idxs.size(0), num_parts=self.num_workers
                    )
                ],
            )
            all_eval_stats = get_async_result(future_all_eval_stats, self.pool)
            return Stats.sum(all_eval_stats).average()
        else:
            return None