training param for batchnorm

examples/benchmark_train_efficientnet.py

@@ -16,6 +16,7 @@ NUM = int(os.getenv("NUM", 2))
 BS = int(os.getenv("BS", 8))
 CNT = int(os.getenv("CNT", 10))
 BACKWARD = int(os.getenv("BACKWARD", 0))
+TRAINING = int(os.getenv("TRAINING", 1))
 
 if __name__ == "__main__":
   print(f"NUM:{NUM} BS:{BS} CNT:{CNT}")
@@ -23,7 +24,7 @@ if __name__ == "__main__":
   parameters = get_parameters(model)
   optimizer = optim.SGD(parameters, lr=0.001)
 
-  Tensor.training = True
+  Tensor.training = TRAINING
   for i in trange(CNT):
     cpy = time.monotonic()
     x_train = Tensor.randn(BS, 3, 224, 224, requires_grad=False).realize()