[DOCS] fix doc builder (#213)

* [DOCS] fix doc builder

* fix

* fix

* fix doc builder

docs/api/python/ndarray.rst

@@ -15,4 +15,4 @@ tvm.ndarray
 .. autofunction:: tvm.metal
 .. autofunction:: tvm.ndarray.array
 
-.. autofunction:: tvm.register_dltensor
+.. autofunction:: tvm.register_extension

docs/conf.py

@@ -185,7 +185,8 @@ def setup(app):
     app.connect("builder-inited", generate_doxygen_xml)
     app.add_stylesheet('css/tvm_theme.css')
     app.add_config_value('recommonmark_config', {
-            'url_resolver': lambda url: github_doc_root + url,
+        'url_resolver': lambda url: github_doc_root + url,
+        'auto_doc_ref': True
             }, True)
     app.add_transform(AutoStructify)
 

python/tvm/contrib/rpc.py

@@ -98,8 +98,8 @@ class Server(object):
     It is also possible to implement a similar C based sever with
     TVM runtime which does not depend on the python.
 
-    Parameter
-    ---------
+    Parameters
+    ----------
     host : str
         The host url of the server.
 

tests/ci_build/Dockerfile.cpu

@@ -3,7 +3,11 @@ FROM ubuntu:14.04
 
 RUN apt-get update
 
-COPY install/ubuntu_*.sh /install/
+COPY install/ubuntu_install_core.sh /install/ubuntu_install_core.sh
 RUN bash /install/ubuntu_install_core.sh
+
+COPY install/ubuntu_install_python.sh /install/ubuntu_install_python.sh
 RUN bash /install/ubuntu_install_python.sh
+
+COPY install/ubuntu_install_iverilog.sh /install/ubuntu_install_iverilog.sh
 RUN bash /install/ubuntu_install_iverilog.sh

tests/ci_build/Dockerfile.gpu

 FROM nvidia/cuda:7.5-cudnn5-devel
 
 # Base scripts
-RUN apt-get update
+RUN apt-get update --fix-missing
 
-COPY install/ubuntu_*.sh /install/
+COPY install/ubuntu_install_core.sh /install/ubuntu_install_core.sh
 RUN bash /install/ubuntu_install_core.sh
+
+COPY install/ubuntu_install_python.sh /install/ubuntu_install_python.sh
 RUN bash /install/ubuntu_install_python.sh
-RUN bash /install/ubuntu_install_sphinx.sh
+
+COPY install/ubuntu_install_llvm.sh /install/ubuntu_install_llvm.sh
 RUN bash /install/ubuntu_install_llvm.sh
+
+COPY install/ubuntu_install_opencl.sh /install/ubuntu_install_opencl.sh
 RUN bash /install/ubuntu_install_opencl.sh
+
+COPY install/ubuntu_install_iverilog.sh /install/ubuntu_install_iverilog.sh
 RUN bash /install/ubuntu_install_iverilog.sh
 
+COPY install/ubuntu_install_sphinx.sh /install/ubuntu_install_sphinx.sh
+RUN bash /install/ubuntu_install_sphinx.sh
+
 # Fix recommonmark to latest version
 RUN git clone https://github.com/rtfd/recommonmark
 RUN cd recommonmark; python setup.py install

tests/ci_build/Dockerfile.i386

@@ -2,7 +2,11 @@ FROM ioft/i386-ubuntu:14.04
 
 RUN apt-get update
 
-COPY install/ubuntu_*.sh /install/
+COPY install/ubuntu_install_core.sh /install/ubuntu_install_core.sh
 RUN bash /install/ubuntu_install_core.sh
+
+COPY install/ubuntu_install_python.sh /install/ubuntu_install_python.sh
 RUN bash /install/ubuntu_install_python.sh
+
+COPY install/ubuntu_install_llvm.sh /install/ubuntu_install_llvm.sh
 RUN bash /install/ubuntu_install_llvm.sh

tests/ci_build/install/ubuntu_install_sphinx.sh

-pip install sphinx>=1.5.5 sphinx-gallery sphinx_rtd_theme matplotlib Image recommonmark
+pip install sphinx==1.6.2 sphinx-gallery sphinx_rtd_theme matplotlib Image commonmark>=0.7.3 docutils>=0.11

tutorials/python/reduction.py

@@ -126,8 +126,8 @@ np.testing.assert_allclose(
 
 ######################################################################
 # Describe Convolution via 2D Reduction
-# ----------------------
-# In TVM, we can describe convolution via 2D reduction in a simple way. 
+# -------------------------------------
+# In TVM, we can describe convolution via 2D reduction in a simple way.
 # Here is an example for 2D convolution with filter size = [3, 3] and strides = [1, 1].
 #
 n = tvm.var('n')