training is False by default

examples/train_efficientnet.py

@@ -48,6 +48,7 @@ if __name__ == "__main__":
   BS, steps = int(os.getenv("BS", "64" if TINY else "16")), 2048
   print("training with batch size %d for %d steps" % (BS, steps))
 
+  Tensor.training = True
   for i in (t := trange(steps)):
     samp = np.random.randint(0, X_train.shape[0], size=(BS))
 

tinygrad/tensor.py

@@ -49,7 +49,7 @@ class Device:
 
 class Tensor:
   did_float_warning = False
-  training = True
+  training = False
   ops = defaultdict(dict)
 
   def __init__(self, data, device=Device.DEFAULT, requires_grad=True):