[GitHub] szha closed pull request #34: fixed broken links

[GitBox <gi...@apache.org>]

szha closed pull request #34: fixed broken links
URL: https://github.com/apache/incubator-mxnet-site/pull/34
 
 
   

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diff --git a/api/python/ndarray/sparse.html b/api/python/ndarray/sparse.html
index e98297ca..a28d6079 100644
--- a/api/python/ndarray/sparse.html
+++ b/api/python/ndarray/sparse.html
@@ -271,7 +271,7 @@ <h1 id="logo-wrap">
 </pre></div>
 </div>
 <p>A detailed tutorial is available at
-<a class="reference external" href="https:https://mxnet.incubator.apache.org/versions/master/tutorials/sparse/csr.html">CSRNDArray - NDArray in Compressed Sparse Row Storage Format</a>.
+<a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/tutorials/sparse/csr.html">CSRNDArray - NDArray in Compressed Sparse Row Storage Format</a>.
 <br/></p>
 <p>An <code class="docutils literal"><span class="pre">RowSparseNDArray</span></code> inherits from <code class="docutils literal"><span class="pre">NDArray</span></code>, and represents a multi-dimensional, fixed-size array in row sparse format.</p>
 <div class="highlight-python"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">nd</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]])</span>
diff --git a/versions/0.11.0.rc3/_static/mxnet.png b/versions/0.11.0.rc3/_static/mxnet.png
new file mode 100644
index 00000000..523676ce
Binary files /dev/null and b/versions/0.11.0.rc3/_static/mxnet.png differ
diff --git a/versions/0.11.0/gluon/index.html b/versions/0.11.0/gluon/index.html
index a461cfa0..7b5f84c6 100644
--- a/versions/0.11.0/gluon/index.html
+++ b/versions/0.11.0/gluon/index.html
@@ -62,7 +62,7 @@ <h1 id="logo-wrap">
 <span id="dropdown-menu-position-anchor">
 <a aria-expanded="true" aria-haspopup="true" class="main-nav-link dropdown-toggle" data-toggle="dropdown" href="#" role="button">Gluon <span class="caret"></span></a>
 <ul class="dropdown-menu" id="package-dropdown-menu">
-<li><a class="main-nav-link" href="../../gluon/index.html">About</a></li>
+<li><a class="main-nav-link" href="../gluon/index.html">About</a></li>
 <li><a class="main-nav-link" href="http://gluon.mxnet.io/">Tutorials</a></li>
 </ul>
 </span>
diff --git a/versions/0.11.0/index.html b/versions/0.11.0/index.html
index ea064689..14d5aa55 100644
--- a/versions/0.11.0/index.html
+++ b/versions/0.11.0/index.html
@@ -61,7 +61,7 @@ <h1 id="logo-wrap">
 <span id="dropdown-menu-position-anchor">
 <a aria-expanded="true" aria-haspopup="true" class="main-nav-link dropdown-toggle" data-toggle="dropdown" href="#" role="button">Gluon <span class="caret"></span></a>
 <ul class="dropdown-menu" id="package-dropdown-menu">
-<li><a class="main-nav-link" href="../gluon/index.html">About</a></li>
+<li><a class="main-nav-link" href="./gluon/index.html">About</a></li>
 <li><a class="main-nav-link" href="http://gluon.mxnet.io/">Tutorials</a></li>
 </ul>
 </span>
diff --git a/versions/0.11.0/tutorials/index.html b/versions/0.11.0/tutorials/index.html
index 40428f82..b839b7d7 100644
--- a/versions/0.11.0/tutorials/index.html
+++ b/versions/0.11.0/tutorials/index.html
@@ -64,7 +64,7 @@ <h1 id="logo-wrap">
 <span id="dropdown-menu-position-anchor">
 <a aria-expanded="true" aria-haspopup="true" class="main-nav-link dropdown-toggle" data-toggle="dropdown" href="#" role="button">Gluon <span class="caret"></span></a>
 <ul class="dropdown-menu" id="package-dropdown-menu">
-<li><a class="main-nav-link" href="../../gluon/index.html">About</a></li>
+<li><a class="main-nav-link" href="../gluon/index.html">About</a></li>
 <li><a class="main-nav-link" href="http://gluon.mxnet.io/">Tutorials</a></li>
 </ul>
 </span>
diff --git a/versions/master/api/python/symbol_in_pictures.html b/versions/master/api/python/symbol_in_pictures.html
index 25e6e0f4..ac2fb77f 100644
--- a/versions/master/api/python/symbol_in_pictures.html
+++ b/versions/master/api/python/symbol_in_pictures.html
@@ -253,7 +253,7 @@ <h1 id="logo-wrap">
 </div>
 <div class="section" id="next-steps">
 <span id="next-steps"></span><h2>Next Steps<a class="headerlink" href="#next-steps" title="Permalink to this headline">?</a></h2>
-<p>See <a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/api/python/symbol.md">Symbolic API</a> and <a class="reference internal" href="index.html"><em>Python Documentation</em></a>.</p>
+<p>See <a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/api/python/symbol.html">Symbolic API</a> and <a class="reference internal" href="index.html"><em>Python Documentation</em></a>.</p>
 </div>
 </div>
 </div>
diff --git a/versions/master/tutorials/sparse/row_sparse.html b/versions/master/tutorials/sparse/row_sparse.html
index d3fe9d18..2049f846 100644
--- a/versions/master/tutorials/sparse/row_sparse.html
+++ b/versions/master/tutorials/sparse/row_sparse.html
@@ -452,7 +452,7 @@ <h1 id="logo-wrap">
 </div>
 <div class="section" id="sparse-operators-and-storage-type-inference">
 <span id="sparse-operators-and-storage-type-inference"></span><h2>Sparse Operators and Storage Type Inference<a class="headerlink" href="#sparse-operators-and-storage-type-inference" title="Permalink to this headline">?</a></h2>
-<p>Operators that have specialized implementation for sparse arrays can be accessed in <code class="docutils literal"><span class="pre">mx.nd.sparse</span></code>. You can read the <a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/versions/master/api/python/ndarray/sparse.html">mxnet.ndarray.sparse API documentation</a> to find what sparse operators are available.</p>
+<p>Operators that have specialized implementation for sparse arrays can be accessed in <code class="docutils literal"><span class="pre">mx.nd.sparse</span></code>. You can read the <a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/api/python/ndarray/sparse.html">mxnet.ndarray.sparse API documentation</a> to find what sparse operators are available.</p>
 <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">shape</span> <span class="o">=</span> <span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">)</span>
 <span class="n">data</span> <span class="o">=</span> <span class="p">[</span><span class="mi">7</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">9</span><span class="p">]</span>
 <span class="n">indptr</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]</span>
diff --git a/versions/master/tutorials/sparse/train.html b/versions/master/tutorials/sparse/train.html
index ae8ab626..bcef9906 100644
--- a/versions/master/tutorials/sparse/train.html
+++ b/versions/master/tutorials/sparse/train.html
@@ -308,7 +308,7 @@ <h1 id="logo-wrap">
 <div class="section" id="storage-type-inference">
 <span id="storage-type-inference"></span><h3>Storage Type Inference<a class="headerlink" href="#storage-type-inference" title="Permalink to this headline">?</a></h3>
 <p>What will be the output storage types of sparse symbols? In MXNet, for any sparse symbol, the result storage types are inferred based on storage types of inputs.
-You can read the <a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/versions/master/api/python/symbol/sparse.html">Sparse Symbol API</a> documentation to find what output storage types are. In the example below we will try out the storage types introduced in the Row Sparse and Compressed Sparse Row tutorials: <code class="docutils literal"><span class="pre">default</span></code> (dense), <code class="docutils literal"><span class="pre">csr</span></code>, and <code class="docutils literal"><span class="pre">row_sparse</span></code>.</p>
+You can read the <a class="reference external" href="https://mxnet.incubator.apache.org/versions/master/api/python/symbol/sparse.html">Sparse Symbol API</a> documentation to find what output storage types are. In the example below we will try out the storage types introduced in the Row Sparse and Compressed Sparse Row tutorials: <code class="docutils literal"><span class="pre">default</span></code> (dense), <code class="docutils literal"><span class="pre">csr</span></code>, and <code class="docutils literal"><span class="pre">row_sparse</span></code>.</p>
 <div class="highlight-python"><div class="highlight"><pre><span></span><span class="n">add_exec</span> <span class="o">=</span> <span class="n">mx</span><span class="o">.</span><span class="n">sym</span><span class="o">.</span><span class="n">Group</span><span class="p">([</span><span class="n">d</span><span class="p">,</span> <span class="n">e</span><span class="p">,</span> <span class="n">f</span><span class="p">])</span><span class="o">.</span><span class="n">simple_bind</span><span class="p">(</span><span class="n">ctx</span><span class="o">=</span><span class="n">mx</span><span class="o">.</span><span class="n">cpu</span><span class="p">(),</span> <span class="n">a</span><span class="o">=</span><span class="n">shape</span><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="n">shape</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="n">shape</span><span class="p">)</span>
 <span class="n">add_exec</span><span class="o">.</span><span class="n">forward</span><span class="p">()</span>
 <span class="n">dense_add</span> <span class="o">=</span> <span class="n">add_exec</span><span class="o">.</span><span class="n">outputs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>


 

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