reset max memory allocated after each model

Author: RJT1990

torchbench/image_classification/utils.py

@@ -72,6 +72,7 @@ def evaluate_classification(
             end = time.time()
 
     memory_allocated = torch.cuda.max_memory_allocated(device=device)
+    torch.cuda.reset_max_memory_allocated(device=device)
 
     speed_mem_metrics = {
         'Tasks Per Second (Total)': test_loader.batch_size/inference_time.avg,

torchbench/object_detection/utils.py

@@ -255,6 +255,7 @@ def evaluate_detection_coco(
     coco_evaluator.summarize()
 
     memory_allocated = torch.cuda.max_memory_allocated(device=device)
+    torch.cuda.reset_max_memory_allocated(device=device)
 
     speed_mem_metrics = {
         'Tasks Per Second (Total)': test_loader.batch_size/inference_time.avg,

torchbench/semantic_segmentation/utils.py

@@ -192,6 +192,7 @@ def evaluate_segmentation(
     acc_global, acc, iu = confmat.compute()
 
     memory_allocated = torch.cuda.max_memory_allocated(device=device)
+    torch.cuda.reset_max_memory_allocated(device=device)
 
     speed_mem_metrics = {
         'Tasks Per Second (Total)': test_loader.batch_size/inference_time.avg,

torchbench/version.py

@@ -16,5 +16,5 @@ def __repr__(self):
         )
 
 
-version = Version(0, 0, 28)
+version = Version(0, 0, 29)
 __version__ = str(version)