zhifu gao
2024-02-06 d92cd5ae037ae85ab9730499d99e5c1bd475eed2
funasr/train_utils/trainer.py
@@ -204,7 +204,25 @@
            my_context = self.model.no_sync if batch_idx % accum_grad != 0 else nullcontext
            with my_context():
                time2 = time.perf_counter()
                print("before, GPU, memory: {:.1} MB, "
                      "{:.1} MB, "
                      "{:.1} MB, "
                      "{:.1} MB".format(torch.cuda.memory_allocated()/1024/1024/1024,
                                     torch.cuda.max_memory_allocated()/1024/1024/1024,
                                     torch.cuda.memory_reserved()/1024/1024/1024,
                                     torch.cuda.max_memory_reserved()/1024/1024/1024,
                                     ))
                retval = self.model(**batch)
                torch.cuda.empty_cache()
                print("after, GPU, memory: {:.1} MB, "
                      "{:.1} MB, "
                      "{:.1} MB, "
                      "{:.1} MB".format(torch.cuda.memory_allocated()/1024/1024/1024,
                                     torch.cuda.max_memory_allocated()/1024/1024/1024,
                                     torch.cuda.memory_reserved()/1024/1024/1024,
                                     torch.cuda.max_memory_reserved()/1024/1024/1024,
                                     ))
                time3 = time.perf_counter()
                speed_stats["forward_time"] = f"{time3 - time2:0.3f}"
                loss, stats, weight = retval