Merge pull request #5433 from notoraptor/windoc

EMAIL.txt

@@ -66,8 +66,7 @@ features:
 
  * tight integration with NumPy: a similar interface to NumPy's.
    numpy.ndarrays are also used internally in Theano-compiled functions.
- * transparent use of a GPU: perform data-intensive computations up to
-   140x faster than on a CPU (support for float32 only).
+ * transparent use of a GPU: perform data-intensive computations much faster than on a CPU.
  * efficient symbolic differentiation: Theano can compute derivatives
    for functions of one or many inputs.
  * speed and stability optimizations: avoid nasty bugs when computing

doc/index.txt

@@ -7,7 +7,7 @@ evaluate mathematical expressions involving multi-dimensional
 arrays efficiently. Theano features:
 
 * **tight integration with NumPy** -- Use `numpy.ndarray` in Theano-compiled functions.
-* **transparent use of a GPU** -- Perform data-intensive calculations up to 140x faster than with CPU.(float32 only)
+* **transparent use of a GPU** -- Perform data-intensive computations much faster than on a CPU.
 * **efficient symbolic differentiation** -- Theano does your derivatives for functions with one or many inputs.
 * **speed and stability optimizations** -- Get the right answer for ``log(1+x)`` even when ``x`` is really tiny.
 * **dynamic C code generation** -- Evaluate expressions faster.

doc/install_centos6.txt

@@ -12,6 +12,7 @@ CentOS 6 Installation Instructions
     page <http://deeplearning.net/software/theano_versions/dev/install_centos6.html>`_.
 
 .. |PlatformCompiler| replace:: ``python-dev``, ``g++`` >= 4.2
+.. |CompilerName| replace:: ``g++``
 
 .. include:: requirements.inc
 

doc/install_generic.inc

@@ -9,6 +9,24 @@ Installation
 Stable Installation
 -------------------
 
+With ``conda``
+^^^^^^^^^^^^^^
+
+If you use conda, you can directly install both theano and pygpu. Libgpuarray
+will be automatically installed as a dependency.
+
+.. code-block:: bash
+
+    conda install theano pygpu
+
+With ``pip``
+^^^^^^^^^^^^
+
+If you use pip, you have to install Theano and libgpuarray separately.
+
+theano
+::::::
+
 Install the latest stable version of Theano with:
 
 .. raw:: html
@@ -27,23 +45,18 @@ Install the latest stable version of Theano with:
 
 If you encountered any trouble, head to the :ref:`troubleshooting` page.
 
-libgpuarray
-^^^^^^^^^^^
-
-It is recommanded that you don't use 0.8.2 for the new back-end. Use
-the dev version of Theano or 0.9rc3.
+The latest stable version of Theano is ``0.9.0`` (tagged with ``rel-0.9.0``).
 
-For the stable version of Theano(0.8.2) you need a specific version of libgpuarray,
-that has been tagged ``v-9998``.
-Download it with:
+libgpuarray
+:::::::::::
 
-.. raw:: html
+For the stable version of Theano you need a specific version of libgpuarray,
+that has been tagged ``v0.6.2``.
+Download it with::
 
-    <div class='highlight'><pre>
-    git clone https://github.com/Theano/libgpuarray.git --tags
-    git checkout origin/v-9998
+    git clone https://github.com/Theano/libgpuarray.git
     cd libgpuarray
-    </pre></div>
+    git checkout tags/v0.6.2 -b v0.6.2
 
 and then follow the `Step-by-step instructions <http://deeplearning.net/software/libgpuarray/installation.html#step-by-step-install>`__.
 

doc/install_macos.txt

@@ -20,6 +20,7 @@ alternative instructions here.
 .. _theano-users: http://groups.google.com/group/theano-users?pli=1
 
 .. |PlatformCompiler| replace:: ``clang`` (the system version)
+.. |CompilerName| replace:: ``Clang``
 
 .. include:: requirements.inc
 

doc/install_ubuntu.txt

@@ -14,6 +14,7 @@ Ubuntu Installation Instructions
 .. _gpu_linux:
 
 .. |PlatformCompiler| replace:: ``python-dev``, ``g++`` >= 4.2
+.. |CompilerName| replace:: ``g++``
 
 .. include:: requirements.inc
 

doc/internal/how_to_release.txt

@@ -153,7 +153,7 @@ For final releases, send the e-mail to the following mailing lists:
 * theano-users
 * theano-announce
 * numpy-discussion@scipy.org
-* scipy-user@scipy.org
+* scipy-user@python.org
 * G+, Scientific Python: https://plus.google.com/communities/108773711053400791849
 
 For release candidates, only e-mail:

doc/requirements.inc

@@ -7,21 +7,28 @@ Requirements
 
 .. _BLAS: http://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms
 .. _Python: http://www.python.org/
+.. _LaTeX: http://www.latex-project.org/
+.. _dvipng: http://savannah.nongnu.org/projects/dvipng/
+.. _NVIDIA CUDA drivers and SDK: http://developer.nvidia.com/object/gpucomputing.html
+.. _libgpuarray: http://deeplearning.net/software/libgpuarray/installation.html
+.. _pycuda: https://mathema.tician.de/software/pycuda/
+.. _skcuda: http://scikit-cuda.readthedocs.io/en/latest/
 
-    Python_ >= 2.7 or >= 3.3 The development package (python-dev or
+    Python_ == 2.7 or ( >= 3.3 and <= 3.5 )
+        The development package (python-dev or
         python-devel on most Linux distributions) is recommended (see
         just below). Python 2.4 was supported up to and including the
         release 0.6. Python 2.6 was supported up to and including the
         release 0.8.2. Python 3 is supported past the 3.3 release.
 
-    `NumPy <http://numpy.scipy.org/>`_ >= 1.9.1 < 1.11.1
+    `NumPy <http://numpy.scipy.org/>`_ >= 1.9.1 <= 1.12
         Earlier versions could work, but we don’t test it.
 
     `SciPy <http://scipy.org>`_ >= 0.14 < 0.17.1
         Only currently required for sparse matrix and special functions support, but highly recommended. SciPy >=0.8 could work, but earlier versions have known bugs with sparse matrices.
 
     `BLAS`_ installation (with Level 3 functionality)
-        * **Recommended**: MKL, which is free through Conda. 
+        * **Recommended**: MKL, which is free through Conda.
         * Alternatively, we suggest to install OpenBLAS, with the development headers (``-dev``, ``-devel``, depending on your Linux distribution).
 
 **Optional requirements**
@@ -42,10 +49,9 @@ Requirements
         **Highly recommended** Required for GPU code generation/execution on NVIDIA gpus. See instruction below.
 
     `libgpuarray`_
-        Required for GPU/CPU code generation on CUDA and OpenCL devices (see: :ref:`gpuarray`.)
+        Required for GPU/CPU code generation on CUDA and OpenCL devices (see: :ref:`gpuarray`).
 
     `pycuda`_ and `skcuda`_
-
         Required for some extra operations on the GPU like fft and
         solvers. We use them to wrap cufft and cusolver. Quick install
         ``pip install pycuda scikit-cuda``. For cuda 8, the dev
@@ -63,7 +69,9 @@ Follow this `link <http://conda.pydata.org/miniconda.html>`__ to install Minicon
 
 .. note::
 
-    If you want fast compiled code (recommended), make sure you have g++ (Windows/Linux) or Clang (OS X) installed.
+    If you want fast compiled code (recommended), make sure you have |CompilerName| installed.
+
+.. install_requirements_and_optional_packages
 
 Install requirements and optional packages
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
@@ -109,9 +117,4 @@ Install and configure the GPU drivers (recommended)
     * add a ``cuda.root`` flag to :envvar:`THEANO_FLAGS`, as in ``THEANO_FLAGS='cuda.root=/path/to/cuda/root'``, or
     * add a [cuda] section to your .theanorc file containing the option ``root = /path/to/cuda/root``.
 
-.. _LaTeX: http://www.latex-project.org/
-.. _dvipng: http://savannah.nongnu.org/projects/dvipng/
-.. _NVIDIA CUDA drivers and SDK: http://developer.nvidia.com/object/gpucomputing.html
-.. _libgpuarray: http://deeplearning.net/software/libgpuarray/installation.html
-.. _pycuda: https://mathema.tician.de/software/pycuda/
-.. _skcuda: http://scikit-cuda.readthedocs.io/en/latest/
+

doc/requirements.txt

 .. |PlatformCompiler| replace:: ``g++`` (Linux and Windows), ``clang`` (OS X)
 
+.. |CompilerName| replace:: ``g++`` (Windows/Linux) or ``Clang`` (OS X)
 .. include:: requirements.inc