diff --git a/advanced_source/cpp_extension.rst b/advanced_source/cpp_extension.rst
index 383d14851d1..6db82bc7711 100644
--- a/advanced_source/cpp_extension.rst
+++ b/advanced_source/cpp_extension.rst
@@ -147,23 +147,22 @@ For the "ahead of time" flavor, we build our C++ extension by writing a
 ``setup.py`` script that uses setuptools to compile our C++ code. For the LLTM, it
 looks as simple as this::
 
-  from setuptools import setup
-  from torch.utils.cpp_extension import CppExtension, BuildExtension
+  from setuptools import setup, Extension
+  from torch.utils import cpp_extension
 
   setup(name='lltm_cpp',
-        ext_modules=[CppExtension('lltm', ['lltm.cpp'])],
-        cmdclass={'build_ext': BuildExtension})
-
+        ext_modules=[cpp_extension.CppExtension('lltm_cpp', ['lltm.cpp'])],
+        cmdclass={'build_ext': cpp_extension.BuildExtension})
 
 In this code, :class:`CppExtension` is a convenience wrapper around
 :class:`setuptools.Extension` that passes the correct include paths and sets
 the language of the extension to C++. The equivalent vanilla :mod:`setuptools`
 code would simply be::
 
-  setuptools.Extension(
+  Extension(
      name='lltm_cpp',
      sources=['lltm.cpp'],
-     include_dirs=torch.utils.cpp_extension.include_paths(),
+     include_dirs=cpp_extension.include_paths(),
      language='c++')
 
 :class:`BuildExtension` performs a number of required configuration steps and
@@ -413,7 +412,7 @@ see::
 If we call ``help()`` on the function or module, we can see that its signature
 matches our C++ code::
 
-  In[4] help(lltm.forward)
+  In[4] help(lltm_cpp.forward)
   forward(...) method of builtins.PyCapsule instance
       forward(arg0: torch::Tensor, arg1: torch::Tensor, arg2: torch::Tensor, arg3: torch::Tensor, arg4: torch::Tensor) -> List[torch::Tensor]
 
@@ -473,6 +472,8 @@ small benchmark to see how much performance we gained from rewriting our op in
 C++. We'll run the LLTM forwards and backwards a few times and measure the
 duration::
 
+  import time
+
   import torch
 
   batch_size = 16