Debugging update.

.jenkins/build.sh

@@ -19,7 +19,7 @@ pip install cython torch_nightly -f https://download.pytorch.org/whl/nightly/cu8
 export PATH=/opt/conda/bin:$PATH
 # pillow >= 4.2 will throw error when trying to write mode RGBA as JPEG,
 # this is a workaround to the issue.
-conda install -y sphinx==1.7.9 pandas pillow=4.1.1
+conda install -y sphinx==1.8.2 pandas pillow=4.1.1
 # PyTorch Theme
 rm -rf src
 pip install -e git+git://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme

advanced_source/cpp_export.rst

@@ -44,7 +44,7 @@ language.
   reference <https://pytorch.org/docs/master/jit.html>`_.
 
 Converting to Torch Script via Tracing
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 To convert a PyTorch model to Torch Script via tracing, you must pass an
 instance of your model along with an example input to the ``torch.jit.trace``
@@ -286,7 +286,7 @@ to the resulting ``example-app`` binary, we should be rewarded with a friendly
   ok
 
 Step 4: Executing the Script Module in C++
-----------------------------------------
+------------------------------------------
 
 Having succesfully loaded our serialized ``ResNet18`` in C++, we are now just a
 couple lines of code away from executing it! Let's add those lines to our C++

intermediate_source/spatial_transformer_tutorial.py

@@ -242,7 +242,6 @@ def visualize_stn():
         axarr[1].imshow(out_grid)
         axarr[1].set_title('Transformed Images')
 
-
 for epoch in range(1, 20 + 1):
     train(epoch)
     test()

requirements.txt

@@ -1,11 +1,12 @@
 # Refer to ./jenkins/build.sh for tutorial build instructions 
 
-sphinx==1.7.9
+sphinx
 sphinx-gallery
 tqdm
 numpy
 matplotlib
 torchvision
+PyHamcrest
 
 # PyTorch Theme
 -e git+git://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme