提交 39bfada8 authored 作者: Frederic Bastien's avatar Frederic Bastien

Small doc fix

上级 c3731688
.. _libdoc_gpuarray_dnn: .. _libdoc_gpuarray_dnn:
=========================================== ===========================================
:mod:`gpuarray.dnn` -- cuDNN :mod:`theano.gpuarray.dnn` -- cuDNN
=========================================== ===========================================
.. moduleauthor:: LISA .. moduleauthor:: LISA
...@@ -173,7 +173,7 @@ Batch Normalization ...@@ -173,7 +173,7 @@ Batch Normalization
RNN RNN
=== ===
New back-end only! Without dropout support. Without dropout support.
.. automodule:: theano.gpuarray.dnn .. automodule:: theano.gpuarray.dnn
:noindex: :noindex:
......
.. _libdoc_cuda_dnn: .. _libdoc_cuda_dnn:
================================ =======================================
:mod:`sandbox.cuda.dnn` -- cuDNN :mod:`theano.sandbox.cuda.dnn` -- cuDNN
================================ =======================================
.. moduleauthor:: LISA .. moduleauthor:: LISA
...@@ -192,8 +192,8 @@ RNN ...@@ -192,8 +192,8 @@ RNN
Softmax Softmax
======= =======
You can manually use the op `GpuDnnSoftmax You can manually use the op :class:`GpuDnnSoftmax
<theano.sandbox.cuda.dnn.GpuDnnSoftmax>`_ to use its extra feature. <theano.sandbox.cuda.dnn.GpuDnnSoftmax>` to use its extra feature.
.. _libdoc_cuda_dnn_internal_ops: .. _libdoc_cuda_dnn_internal_ops:
......
...@@ -2339,12 +2339,13 @@ class GpuDnnRNNGradWeights(DnnBase): ...@@ -2339,12 +2339,13 @@ class GpuDnnRNNGradWeights(DnnBase):
class RNNBlock(object): class RNNBlock(object):
""" """
An object that allow us to use CuDNN v5 RNN implementation. An object that allow us to use CuDNN v5 RNN implementation.
TODO: make an example how to use. You can check that test until we have it. TODO: make an example how to use. You can check Theano tests
test_dnn_rnn_gru() and test_dnn_rnn_lstm() in the file
theano/gpuarray/tests/test_dnn.py for now.
Parameters Parameters
---------- ----------
dtype : data type of computation dtype : data type of computation
hidden_size : int hidden_size : int
num_layers : int num_layers : int
......
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