change from recommendation to try

Author: williamwen42

intermediate_source/torch_compile_tutorial.rst

@@ -184,8 +184,9 @@ much as possible, and so we chose ``"reduce-overhead"``. For your own models,
 you may need to experiment with different modes to maximize speedup. You can
 read more about modes `here <https://pytorch.org/get-started/pytorch-2.0/#user-experience>`__.
 
-We also note that for general PyTorch benchmarking, we recommend using ``torch.utils.benchmark``.
-We wrote our own timing functions in this tutorial to show ``torch.compile``'s compilation latency.
+For general PyTorch benchmarking, you can try using ``torch.utils.benchmark`` instead of the ``timed``
+function we defined above. We wrote our own timing function in this tutorial to show
+``torch.compile``'s compilation latency.
 
 Now, let's consider comparing training.
 

intermediate_source/torch_compile_tutorial_.py

@@ -187,8 +187,9 @@ def evaluate(mod, inp):
 # you may need to experiment with different modes to maximize speedup. You can
 # read more about modes `here <https://pytorch.org/get-started/pytorch-2.0/#user-experience>`__.
 #
-# We also note that for general PyTorch benchmarking, we recommend using ``torch.utils.benchmark``.
-# We wrote our own timing functions in this tutorial to show ``torch.compile``'s compilation latency.
+# For general PyTorch benchmarking, you can try using ``torch.utils.benchmark`` instead of the ``timed``
+# function we defined above. We wrote our own timing function in this tutorial to show
+# ``torch.compile``'s compilation latency.
 #
 # Now, let's consider comparing training.