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...@@ -3751,14 +3751,6 @@ Classification (CTC) loss. Besides, another <a class="reference external" href=" ...@@ -3751,14 +3751,6 @@ Classification (CTC) loss. Besides, another <a class="reference external" href="
the official one, is maintained to enable more compiling options. During the the official one, is maintained to enable more compiling options. During the
building process, PaddlePaddle will clone the source codes, build and building process, PaddlePaddle will clone the source codes, build and
install it to <code class="code docutils literal"><span class="pre">third_party/install/warpctc</span></code> directory.</p> install it to <code class="code docutils literal"><span class="pre">third_party/install/warpctc</span></code> directory.</p>
<p>To use warp_ctc layer, you need to specify the path of <code class="code docutils literal"><span class="pre">libwarpctc.so</span></code>,
using following methods:</p>
<p>1. Set it in <code class="code docutils literal"><span class="pre">paddle.init</span></code> (python api) or <code class="code docutils literal"><span class="pre">paddle_init</span></code> (c api),
such as <code class="code docutils literal"><span class="pre">paddle.init(use_gpu=True,</span>
<span class="pre">warpctc_dir=your_paddle_source_dir/third_party/install/warpctc/lib)</span></code>.</p>
<p>2. Set environment variable LD_LIBRARY_PATH on Linux or DYLD_LIBRARY_PATH
on Mac OS. For instance, <code class="code docutils literal"><span class="pre">export</span>
<span class="pre">LD_LIBRARY_PATH=your_paddle_source_dir/third_party/install/warpctc/lib:$LD_LIBRARY_PATH</span></code>.</p>
<p>More details of CTC can be found by referring to <a class="reference external" href="http://machinelearning.wustl.edu/mlpapers/paper_files/icml2006_GravesFGS06.pdf">Connectionist Temporal <p>More details of CTC can be found by referring to <a class="reference external" href="http://machinelearning.wustl.edu/mlpapers/paper_files/icml2006_GravesFGS06.pdf">Connectionist Temporal
Classification: Labelling Unsegmented Sequence Data with Recurrent Classification: Labelling Unsegmented Sequence Data with Recurrent
Neural Networks</a>.</p> Neural Networks</a>.</p>
......
因为 它太大了无法显示 source diff 。你可以改为 查看blob
...@@ -3758,14 +3758,6 @@ Classification (CTC) loss. Besides, another <a class="reference external" href=" ...@@ -3758,14 +3758,6 @@ Classification (CTC) loss. Besides, another <a class="reference external" href="
the official one, is maintained to enable more compiling options. During the the official one, is maintained to enable more compiling options. During the
building process, PaddlePaddle will clone the source codes, build and building process, PaddlePaddle will clone the source codes, build and
install it to <code class="code docutils literal"><span class="pre">third_party/install/warpctc</span></code> directory.</p> install it to <code class="code docutils literal"><span class="pre">third_party/install/warpctc</span></code> directory.</p>
<p>To use warp_ctc layer, you need to specify the path of <code class="code docutils literal"><span class="pre">libwarpctc.so</span></code>,
using following methods:</p>
<p>1. Set it in <code class="code docutils literal"><span class="pre">paddle.init</span></code> (python api) or <code class="code docutils literal"><span class="pre">paddle_init</span></code> (c api),
such as <code class="code docutils literal"><span class="pre">paddle.init(use_gpu=True,</span>
<span class="pre">warpctc_dir=your_paddle_source_dir/third_party/install/warpctc/lib)</span></code>.</p>
<p>2. Set environment variable LD_LIBRARY_PATH on Linux or DYLD_LIBRARY_PATH
on Mac OS. For instance, <code class="code docutils literal"><span class="pre">export</span>
<span class="pre">LD_LIBRARY_PATH=your_paddle_source_dir/third_party/install/warpctc/lib:$LD_LIBRARY_PATH</span></code>.</p>
<p>More details of CTC can be found by referring to <a class="reference external" href="http://machinelearning.wustl.edu/mlpapers/paper_files/icml2006_GravesFGS06.pdf">Connectionist Temporal <p>More details of CTC can be found by referring to <a class="reference external" href="http://machinelearning.wustl.edu/mlpapers/paper_files/icml2006_GravesFGS06.pdf">Connectionist Temporal
Classification: Labelling Unsegmented Sequence Data with Recurrent Classification: Labelling Unsegmented Sequence Data with Recurrent
Neural Networks</a>.</p> Neural Networks</a>.</p>
......
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