Merge 605f8e9 into 3dd6ff6

chainer/cuda.py

@@ -1,6 +1,6 @@
 """Device, context and memory management on CuPy.
 
-Chainer uses `CuPy <http://docs.cupy.chainer.org/>`_ (with very thin wrapper)
+Chainer uses `CuPy <https://cupy.chainer.org/>`_ (with very thin wrapper)
 to exploit the speed of GPU computation. Following modules and classes defined
 in CuPy are imported to :mod:`chainer.cuda` module for convenience (refer to
 this table when reading chainer's source codes).

docs/source/conf.py

@@ -323,7 +323,7 @@
 intersphinx_mapping = {
     'python': ('https://docs.python.org/3/', None),
     'numpy': ('http://docs.scipy.org/doc/numpy/', None),
-    'cupy': ('http://docs.cupy.chainer.org/en/latest/', None),
+    'cupy': ('https://docs-cupy.chainer.org/en/latest/', None),
 }
 
 doctest_global_setup = '''

docs/source/install.rst

@@ -38,7 +38,7 @@ Chainer can be installed without them, in which case the corresponding features
 
 * CUDA/cuDNN support
 
-  * `cupy <http://docs.cupy.chainer.org/>`__ 1.0+
+  * `cupy <https://cupy.chainer.org/>`__ 1.0+
 
 * Caffe model support
 
@@ -103,9 +103,9 @@ It may help you::
 Enable CUDA/cuDNN support
 ~~~~~~~~~~~~~~~~~~~~~~~~~
 
-In order to enable CUDA support, you have to install `CuPy <http://docs.cupy.chainer.org/>`_ manually.
+In order to enable CUDA support, you have to install `CuPy <https://cupy.chainer.org/>`_ manually.
 If you also want to use cuDNN, you have to install CuPy with cuDNN support.
-See `CuPy's installation guide <http://docs.cupy.chainer.org/en/latest/install.html>`_ to install CuPy.
+See `CuPy's installation guide <https://docs-cupy.chainer.org/en/latest/install.html>`_ to install CuPy.
 Once CuPy is correctly set up, Chainer will automatically enable CUDA support.
 
 You can refer to the following flags to confirm if CUDA/cuDNN support is actually available.
@@ -212,4 +212,4 @@ If you don't need cuDNN, ignore this message.
 Otherwise, retry to install CuPy with cuDNN.
 ``-vvvv`` option helps you.
 There is no need of re-installing Chainer itself.
-See `CuPy's installation guide <http://docs.cupy.chainer.org/en/latest/install.html>`_ for more details.
+See `CuPy's installation guide <https://docs-cupy.chainer.org/en/latest/install.html>`_ for more details.

docs/source/tutorial/gpu.rst

@@ -27,7 +27,7 @@ Relationship between Chainer and CuPy
    Even if you have CUDA installed in your environment, you have to install CuPy separately to use GPUs.
    See :ref:`install_cuda` for the way to set up CUDA support.
 
-Chainer uses `CuPy <http://docs.cupy.chainer.org/>`_ as its backend for GPU computation.
+Chainer uses `CuPy <https://cupy.chainer.org/>`_ as its backend for GPU computation.
 In particular, the :class:`cupy.ndarray` class is the GPU array implementation for Chainer.
 CuPy supports a subset of features of NumPy with a compatible interface.
 It enables us to write a common code for CPU and GPU.
@@ -49,7 +49,7 @@ Chainer changes the default allocator of CuPy to the memory pool, so user can us
 Basics of :class:`cupy.ndarray`
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-See `the document of CuPy <http://docs.cupy.chainer.org/en/latest/>`_ for the basic usage of :class:`cupy.ndarray`
+See `the document of CuPy <https://docs-cupy.chainer.org/en/latest/>`_ for the basic usage of :class:`cupy.ndarray`
 
 CuPy is a GPU array backend that implements a subset of NumPy interface.
 The :class:`cupy.ndarray` class is in its core, which is a compatible GPU alternative of :class:`numpy.ndarray`.