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Posted to commits@mxnet.apache.org by lx...@apache.org on 2017/08/15 21:22:29 UTC
[incubator-mxnet-site] branch asf-site updated: Fix more
This is an automated email from the ASF dual-hosted git repository.
lxn2 pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet-site.git
The following commit(s) were added to refs/heads/asf-site by this push:
new 15141b2 Fix more
15141b2 is described below
commit 15141b2b7083bfb99cf22929ec4723852c3cf39e
Author: Wang <wa...@9801a7a9c287.ant.amazon.com>
AuthorDate: Tue Aug 15 13:38:22 2017 -0700
Fix more
---
get_started/windows_setup.html | 3 +--
versions/master/api/python/ndarray.html | 4 ++--
versions/master/api/python/symbol.html | 4 ++--
versions/master/get_started/windows_setup.html | 3 +--
4 files changed, 6 insertions(+), 8 deletions(-)
diff --git a/get_started/windows_setup.html b/get_started/windows_setup.html
index ff5d687..03afe27 100644
--- a/get_started/windows_setup.html
+++ b/get_started/windows_setup.html
@@ -244,8 +244,7 @@ Previous Navbar Layout End -->
<span id="installing-the-prebuilt-package-on-windows"></span><h3>Installing the Prebuilt Package on Windows<a class="headerlink" href="#installing-the-prebuilt-package-on-windows" title="Permalink to this headline">¶</a></h3>
<p>MXNet provides a prebuilt package for Windows. The prebuilt package includes the MXNet library, all of the dependent third-party libraries, a sample C++ solution for Visual Studio, and the Python installation script. To install the prebuilt package:</p>
<ol class="simple">
-<li>Download the latest prebuilt package from the <a class="reference external" href="https://github.com/dmlc/mxnet/releases">Releases</a> tab of MXNet.
-There are two versions. One with GPU support (using CUDA and CUDNN v3), and one without GPU support. Choose the version that suits your hardware configuration. For more information on which version works on each hardware configuration, see <a class="reference external" href="https://mxnet.incubator.apache.org/get_started/setup.html#requirements-for-using-gpus">Requirements for GPU</a>.</li>
+<li>Download the latest prebuilt package from the <a class="reference external" href="https://github.com/dmlc/mxnet/releases">Releases</a> tab of MXNet.</li>
<li>Unpack the package into a folder, with an appropriate name, such as <code class="docutils literal"><span class="pre">D:\MXNet</span></code>.</li>
<li>Open the folder, and install the package by double-clicking <code class="docutils literal"><span class="pre">setupenv.cmd</span></code>. This sets up all of the environment variables required by MXNet.</li>
<li>Test the installation by opening the provided sample C++ Visual Studio solution and building it.</li>
diff --git a/versions/master/api/python/ndarray.html b/versions/master/api/python/ndarray.html
index d521694..0dbcb5d 100644
--- a/versions/master/api/python/ndarray.html
+++ b/versions/master/api/python/ndarray.html
@@ -1170,7 +1170,7 @@ broadcasting enabled by default.</li>
<td>Compute 2-D deformable convolution on 4-D input.</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#mxnet.contrib.ndarray.DeformablePSROIPooling" title="mxnet.contrib.ndarray.DeformablePSROIPooling"><code class="xref py py-obj docutils literal"><span class="pre">DeformablePSROIPooling</span></code></a></td>
-<td>Performs deformable position-sensitive region-of-interest pooling on inputs.The DeformablePSROIPooling operation is described in <a class="reference external" href="https://arxiv.org/abs/1703.06211.batch_size">https://arxiv.org/abs/1703.06211.batch_size</a> will change to the number of region bounding boxes after DeformablePSROIPooling</td>
+<td>Performs deformable position-sensitive region-of-interest pooling on inputs.The DeformablePSROIPooling operation is described in <a class="reference external" href="https://arxiv.org/abs/1703.06211">https://arxiv.org/abs/1703.06211.</a> Batch size will change to the number of region bounding boxes after DeformablePSROIPooling</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#mxnet.contrib.ndarray.MultiBoxDetection" title="mxnet.contrib.ndarray.MultiBoxDetection"><code class="xref py py-obj docutils literal"><span class="pre">MultiBoxDetection</span></code></a></td>
<td>Convert multibox detection predictions.</td>
@@ -11267,7 +11267,7 @@ The output of this function.</p>
<dl class="function">
<dt id="mxnet.contrib.ndarray.DeformablePSROIPooling">
<code class="descclassname">mxnet.contrib.ndarray.</code><code class="descname">DeformablePSROIPooling</code><span class="sig-paren">(</span><em>data=None</em>, <em>rois=None</em>, <em>trans=None</em>, <em>spatial_scale=_Null</em>, <em>output_dim=_Null</em>, <em>group_size=_Null</em>, <em>pooled_size=_Null</em>, <em>part_size=_Null</em>, <em>sample_per_part=_Null</em>, <em>trans_std=_Null</em>, <em>no_trans=_Null</em>, <em>out=None</em>, <em>name=None</em>, <em>**kwargs</em><span class=" [...]
-<dd><p>Performs deformable position-sensitive region-of-interest pooling on inputs.The DeformablePSROIPooling operation is described in <a class="reference external" href="https://arxiv.org/abs/1703.06211.batch_size">https://arxiv.org/abs/1703.06211.batch_size</a> will change to the number of region bounding boxes after DeformablePSROIPooling</p>
+<dd><p>Performs deformable position-sensitive region-of-interest pooling on inputs.The DeformablePSROIPooling operation is described in <a class="reference external" href="https://arxiv.org/abs/1703.06211">https://arxiv.org/abs/1703.06211.</a> Batch size will change to the number of region bounding boxes after DeformablePSROIPooling</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
diff --git a/versions/master/api/python/symbol.html b/versions/master/api/python/symbol.html
index 2dce732..3e3cd52 100644
--- a/versions/master/api/python/symbol.html
+++ b/versions/master/api/python/symbol.html
@@ -1212,7 +1212,7 @@ explicitly.</li>
<td>Compute 2-D deformable convolution on 4-D input.</td>
</tr>
<tr class="row-odd"><td><a class="reference internal" href="#mxnet.contrib.symbol.DeformablePSROIPooling" title="mxnet.contrib.symbol.DeformablePSROIPooling"><code class="xref py py-obj docutils literal"><span class="pre">DeformablePSROIPooling</span></code></a></td>
-<td>Performs deformable position-sensitive region-of-interest pooling on inputs.The DeformablePSROIPooling operation is described in <a class="reference external" href="https://arxiv.org/abs/1703.06211.batch_size">https://arxiv.org/abs/1703.06211.batch_size</a> will change to the number of region bounding boxes after DeformablePSROIPooling</td>
+<td>Performs deformable position-sensitive region-of-interest pooling on inputs.The DeformablePSROIPooling operation is described in <a class="reference external" href="https://arxiv.org/abs/1703.06211">https://arxiv.org/abs/1703.06211.</a> Batch size will change to the number of region bounding boxes after DeformablePSROIPooling</td>
</tr>
<tr class="row-even"><td><a class="reference internal" href="#mxnet.contrib.symbol.MultiBoxDetection" title="mxnet.contrib.symbol.MultiBoxDetection"><code class="xref py py-obj docutils literal"><span class="pre">MultiBoxDetection</span></code></a></td>
<td>Convert multibox detection predictions.</td>
@@ -10852,7 +10852,7 @@ default layout: NCW for 1d, NCHW for 2d and NCDHW for 3d.</li>
<dl class="function">
<dt id="mxnet.contrib.symbol.DeformablePSROIPooling">
<code class="descclassname">mxnet.contrib.symbol.</code><code class="descname">DeformablePSROIPooling</code><span class="sig-paren">(</span><em>data=None</em>, <em>rois=None</em>, <em>trans=None</em>, <em>spatial_scale=_Null</em>, <em>output_dim=_Null</em>, <em>group_size=_Null</em>, <em>pooled_size=_Null</em>, <em>part_size=_Null</em>, <em>sample_per_part=_Null</em>, <em>trans_std=_Null</em>, <em>no_trans=_Null</em>, <em>name=None</em>, <em>attr=None</em>, <em>out=None</em>, <em>**kwarg [...]
-<dd><p>Performs deformable position-sensitive region-of-interest pooling on inputs.The DeformablePSROIPooling operation is described in <a class="reference external" href="https://arxiv.org/abs/1703.06211.batch_size">https://arxiv.org/abs/1703.06211.batch_size</a> will change to the number of region bounding boxes after DeformablePSROIPooling</p>
+<dd><p>Performs deformable position-sensitive region-of-interest pooling on inputs.The DeformablePSROIPooling operation is described in <a class="reference external" href="https://arxiv.org/abs/1703.06211">https://arxiv.org/abs/1703.06211.</a> Batch size will change to the number of region bounding boxes after DeformablePSROIPooling</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name"/>
<col class="field-body"/>
diff --git a/versions/master/get_started/windows_setup.html b/versions/master/get_started/windows_setup.html
index bc91c0d..132abc9 100644
--- a/versions/master/get_started/windows_setup.html
+++ b/versions/master/get_started/windows_setup.html
@@ -242,8 +242,7 @@ Previous Navbar Layout End -->
<span id="installing-the-prebuilt-package-on-windows"></span><h3>Installing the Prebuilt Package on Windows<a class="headerlink" href="#installing-the-prebuilt-package-on-windows" title="Permalink to this headline">¶</a></h3>
<p>MXNet provides a prebuilt package for Windows. The prebuilt package includes the MXNet library, all of the dependent third-party libraries, a sample C++ solution for Visual Studio, and the Python installation script. To install the prebuilt package:</p>
<ol class="simple">
-<li>Download the latest prebuilt package from the <a class="reference external" href="https://github.com/dmlc/mxnet/releases">Releases</a> tab of MXNet.
-There are two versions. One with GPU support (using CUDA and CUDNN v3), and one without GPU support. Choose the version that suits your hardware configuration. For more information on which version works on each hardware configuration, see <a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/get_started/setup.html#requirements-for-using-gpus">Requirements for GPU</a>.</li>
+<li>Download the latest prebuilt package from the <a class="reference external" href="https://github.com/dmlc/mxnet/releases">Releases</a> tab of MXNet.</li>
<li>Unpack the package into a folder, with an appropriate name, such as <code class="docutils literal"><span class="pre">D:\MXNet</span></code>.</li>
<li>Open the folder, and install the package by double-clicking <code class="docutils literal"><span class="pre">setupenv.cmd</span></code>. This sets up all of the environment variables required by MXNet.</li>
<li>Test the installation by opening the provided sample C++ Visual Studio solution and building it.</li>
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