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提交 754f3b72 authored 作者: Frédéric Bastien's avatar Frédéric Bastien 提交者： GitHub
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Merge pull request #4985 from abergeron/fix_req_compiler

Fix the recommended compiler so that it matches the platform instructructions
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doc/install_centos6.txt
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......@@ -11,7 +11,9 @@ CentOS 6 Installation Instructions
from GitHub, please make sure you are reading `the latest version of this
page <http://deeplearning.net/software/theano_versions/dev/install_centos6.html>`_.
.. include:: requirements.txt
.. |PlatformCompiler| replace:: ``python-dev``, ``g++`` >= 4.2
.. include:: requirements.inc
.. include:: install_generic.inc
:start-line: 5
......
doc/install_macos.txt
浏览文件 @ 754f3b72
......@@ -19,7 +19,9 @@ alternative instructions here.
.. _theano-users: http://groups.google.com/group/theano-users?pli=1
.. include:: requirements.txt
.. |PlatformCompiler| replace:: ``clang`` (the system version)
.. include:: requirements.inc
.. _gpu_macos:
......
doc/install_ubuntu.txt
浏览文件 @ 754f3b72
......@@ -13,7 +13,9 @@ Ubuntu Installation Instructions
.. _gpu_linux:
.. include:: requirements.txt
.. |PlatformCompiler| replace:: ``python-dev``, ``g++`` >= 4.2
.. include:: requirements.inc
.. include:: install_generic.inc
:start-line: 5
......
doc/requirements.inc 0 → 100644
浏览文件 @ 754f3b72
Requirements
============
.. note::
We only support the installation of the requirements through conda.
.. _BLAS: http://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms
.. _Python: http://www.python.org/
Python_ >= 2.7 or >= 3.3 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
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.
* Alternatively, we suggest to install OpenBLAS, with the development headers (``-dev``, ``-devel``, depending on your Linux distribution).
**Optional requirements**
|PlatformCompiler|
**Highly recommended.** Theano can fall back on a NumPy-based Python execution model, but a C compiler allows for vastly faster execution.
`nose <http://nose.readthedocs.io/en/latest/>`_ >= 1.3.0
Recommended, to run Theano's test-suite.
`Sphinx <http://sphinx.pocoo.org/>`_ >= 0.5.1, `pygments <http://pygments.org/>`_
For building the documentation. LaTeX_ and dvipng_ are also necessary for math to show up as images.
`pydot-ng <https://github.com/pydot/pydot-ng>`_
To handle large picture for gif/images.
`NVIDIA CUDA drivers and SDK`_
**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`.)
Requirements installation through Conda (recommended)
-----------------------------------------------------
Install Miniconda
^^^^^^^^^^^^^^^^^
Follow this `link <http://conda.pydata.org/miniconda.html>`__ to install Miniconda.
.. note::
If you want fast compiled code (recommended), make sure you have g++ (Windows/Linux) or Clang (OS X) installed.
Install requirements and optional packages
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.. code-block:: bash
conda install numpy scipy mkl <nose> <sphinx> <pydot-ng>
* Arguments between <...> are optional.
Install and configure the GPU drivers (recommended)
---------------------------------------------------
.. warning::
OpenCL support is still minimal for now.
1. Install CUDA drivers
* Follow `this link <https://developer.nvidia.com/cuda-downloads>`__
to install the CUDA driver and the CUDA Toolkit.
* You must reboot the computer after the driver installation.
* Test that it was loaded correctly after the reboot, executing the
command `nvidia-smi` from the command line.
.. note::
Sanity check: The *bin* subfolder should contain an *nvcc*
program. This folder is called the *cuda root* directory.
2. Fix 'lib' path
* Add the 'lib' subdirectory (and/or 'lib64' subdirectory if you have a
64-bit OS) to your ``$LD_LIBRARY_PATH`` environment
variable.
3. Set Theano's config flags
To use the GPU you need to define the *cuda root*. You can do it in one
of the following ways:
* Define a $CUDA_ROOT environment variable to equal the cuda root directory, as in ``CUDA_ROOT=/path/to/cuda/root``, or
* 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
doc/requirements.txt
浏览文件 @ 754f3b72
Requirements
============
.. |PlatformCompiler| replace:: ``g++`` (Linux and Windows), ``clang`` (OS X)
.. note::
We only support the installation of the requirements through conda.
.. _BLAS: http://en.wikipedia.org/wiki/Basic_Linear_Algebra_Subprograms
.. _Python: http://www.python.org/
Python_ >= 2.7 or >= 3.3 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
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.
* Alternatively, we suggest to install OpenBLAS, with the development headers (``-dev``, ``-devel``, depending on your Linux distribution).
**Optional requirements**
``python-dev``, ``g++`` >= 4.2
**Highly recommended.** Theano can fall back on a NumPy-based Python execution model, but a C compiler allows for vastly faster execution.
`nose <http://nose.readthedocs.io/en/latest/>`_ >= 1.3.0
Recommended, to run Theano's test-suite.
`Sphinx <http://sphinx.pocoo.org/>`_ >= 0.5.1, `pygments <http://pygments.org/>`_
For building the documentation. LaTeX_ and dvipng_ are also necessary for math to show up as images.
`pydot-ng <https://github.com/pydot/pydot-ng>`_
To handle large picture for gif/images.
`NVIDIA CUDA drivers and SDK`_
**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`.)
Requirements installation through Conda (recommended)
-----------------------------------------------------
Install Miniconda
^^^^^^^^^^^^^^^^^
Follow this `link <http://conda.pydata.org/miniconda.html>`__ to install Miniconda.
.. note::
If you want fast compiled code (recommended), make sure you have g++ (Windows/Linux) or Clang (OS X) installed.
Install requirements and optional packages
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
.. code-block:: bash
conda install numpy scipy mkl <nose> <sphinx> <pydot-ng>
* Arguments between <...> are optional.
Install and configure the GPU drivers (recommended)
---------------------------------------------------
.. warning::
OpenCL support is still minimal for now.
1. Install CUDA drivers
* Follow `this link <https://developer.nvidia.com/cuda-downloads>`__
to install the CUDA driver and the CUDA Toolkit.
* You must reboot the computer after the driver installation.
* Test that it was loaded correctly after the reboot, executing the
command `nvidia-smi` from the command line.
.. note::
Sanity check: The *bin* subfolder should contain an *nvcc*
program. This folder is called the *cuda root* directory.
2. Fix 'lib' path
* Add the 'lib' subdirectory (and/or 'lib64' subdirectory if you have a
64-bit OS) to your ``$LD_LIBRARY_PATH`` environment
variable.
3. Set Theano's config flags
To use the GPU you need to define the *cuda root*. You can do it in one
of the following ways:
* Define a $CUDA_ROOT environment variable to equal the cuda root directory, as in ``CUDA_ROOT=/path/to/cuda/root``, or
* 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
.. include:: requirements.inc
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