From e278c81adfb3257f394d41204a34ece907df2576 Mon Sep 17 00:00:00 2001 From: Richard Zou Date: Mon, 24 Oct 2022 10:26:47 -0700 Subject: [PATCH] [1.13] Update nvfuser tutorial Fixes https://github.com/pytorch/tutorials/issues/2093. Addresses https://github.com/pytorch/tutorials/issues/2093 -- This PR adds a note to clarify the usage of memory_efficient_fusion and make it clearer that the feature is experimental and subject to change. --- intermediate_source/nvfuser_intro_tutorial.py | 13 ++++++++++--- 1 file changed, 10 insertions(+), 3 deletions(-) diff --git a/intermediate_source/nvfuser_intro_tutorial.py b/intermediate_source/nvfuser_intro_tutorial.py index 2a92fe8b328..91166fcce1e 100644 --- a/intermediate_source/nvfuser_intro_tutorial.py +++ b/intermediate_source/nvfuser_intro_tutorial.py @@ -557,9 +557,16 @@ def primitive_definition_for_memory_efficient_fusion( # # .. figure:: /_static/img/nvfuser_intro/nvfuser_tutorial_5.png # -# .. note:: FuncTorch’s memory efficient pass is still actively in development -# and future versions are expected to achieve performance closer -# to that of TorchScript with the composite definition. +# .. note:: FuncTorch’s memory efficient pass is experimental and still +# actively in development. +# Future versions of the API are expected to achieve performance +# closer to that of TorchScript with the composite definition. +# +# .. note:: FuncTorch’s memory efficient pass specializes on the shapes of +# the inputs to the function. If new inputs are provided with +# different shapes, then you need to construct a new function +# using `memory_efficient_fusion` and apply it to the new inputs. + ###################################################################### # Transformer Block With a Novel Normalization