提交 9535b59f authored 作者: Frederic's avatar Frederic

better doc

上级 666e371d
......@@ -6,31 +6,33 @@
.. moduleauthor:: LISA
Normally you should not call directly GPU Ops, but the CPU interface
currently do not allow all options supported by cuDNN ops. So it is
possible that you need to call them manually.
`cuDNN <https://developer.nvidia.com/cuDNN>`_ is NVIDIA library with
functionality used by deep neural network. It provide faster
implementation of some operation like the convolution. cuDNN currently
is not installed with CUDA 6.5. You must download it and install it
`cuDNN <https://developer.nvidia.com/cuDNN>`_ is an NVIDIA library with
functionality used by deep neural network. It provides optimized versions
of some operations like the convolution. cuDNN is not currently
installed with CUDA 6.5. You must download and install it
yourself.
To install it, decompress the downloaded file and make the ``*.h`` and
``*.so*`` files available to the compilation environment. On Linux,
this can be done by setting the environment variable
this can be done by setting the environment variables
``LD_LIBRARY_PATH``, ``LIBRARY_PATH`` and ``CPATH`` to the
uncompressed directory path. They work the same way as ``PATH``. Or
you can copy the ``*.h`` files to ``/usr/include`` and the files
``*.so*`` to ``/lib64``.
uncompressed directory path. Separate multiple directory with ``:`` as
the ``PATH`` environment variable. Or you can copy the ``*.h`` files
to ``/usr/include`` and the ``*.so*`` files to ``/lib64``.
By default, Theano will detect if it can use cuDNN. If so, it will use
it. If not, Theano optimization will not introduce cuDNN op. So
it. If not, Theano optimizations will not introduce cuDNN ops. So
Theano will still work if the user did not introduce them manually.
To get an error if Theano can not use cuDNN, use this Theano flags:
To get an error if Theano can not use cuDNN, use this Theano flag:
``optimizer_including=cudnn``.
.. note::
Normally you should not call GPU Ops directly, but the CPU interface
currently does not allow all options supported by cuDNN ops. So it is
possible that you will need to call them manually.
Functions
=========
......
......@@ -90,12 +90,13 @@ if ((err = cudnnCreate(&_handle)) != CUDNN_STATUS_SUCCESS) {
class GpuDnnConvDesc(GpuOp):
"""
The convolution description.
"""This Op builds a convolution descriptor for use in the other
convolution operations.
:param border_mode: 'valid' or 'full'
:param subsample: The subsample, tuple like (dx, dy)
:param conv_mode: 'conv' or 'cross'
"""
__props__ = ('border_mode', 'subsample', 'conv_mode')
......@@ -446,7 +447,8 @@ def dnn_conv(img, kerns, border_mode='valid', subsample=(1, 1),
class GpuDnnPoolDesc(GpuOp):
"""
The pooling descriptor.
This Op builds a pooling descriptor for use in the other
pooling operations.
:param ws: windows size
:param stride: (dx, dy)
......
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