Method multi_process_evaluation

utils/engine/dist_test.py:109–139

(self)

        results.close()

    def multi_process_evaluation(self):
        start_eval_time = time.perf_counter()
        nr_devices = len(self.devices)
        stride = int(np.ceil(self.ndata / nr_devices))

        # start multi-process on multi-gpu
        procs = []
        for d in range(nr_devices):
            e_record = min((d + 1) * stride, self.ndata)
            shred_list = list(range(d * stride, e_record))
            device = self.devices[d]
            logger.info("GPU %s handle %d data." % (device, len(shred_list)))
            p = self.context.Process(target=self.worker, args=(shred_list, device))
            procs.append(p)

        for p in procs:
            p.start()

        all_results = []
        for _ in tqdm(range(self.ndata)):
            t = self.results_queue.get()
            all_results.append(t)
            if self.verbose:
                self.compute_metric(all_results)

        for p in procs:
            p.join()

        result_line = self.compute_metric(all_results)
        logger.info("Evaluation Elapsed Time: %.2fs" % (time.perf_counter() - start_eval_time))
        return result_line

    def worker(self, shred_list, device):
        start_load_time = time.time()