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The following commit(s) were added to refs/heads/asf-site by this push:
     new 3af5742e Publish triggered by CI
3af5742e is described below

commit 3af5742e06b0ccb8a53dbd0688168d19f073ab12
Author: mxnet-ci <mxnet-ci>
AuthorDate: Thu Sep 24 18:43:15 2020 +0000

    Publish triggered by CI
---
 api/python/docs/_modules/mxnet/util.html           |  90 ++++++++++-----------
 api/python/docs/api/np/arrays.ndarray.html         |  14 ++--
 .../docs/api/np/generated/mxnet.np.ndarray.html    |  12 +--
 .../docs/api/np/routines.array-manipulation.html   |   2 +-
 api/python/docs/objects.inv                        | Bin 93149 -> 93121 bytes
 api/python/docs/searchindex.js                     |   2 +-
 date.txt                                           |   1 -
 feed.xml                                           |   2 +-
 8 files changed, 61 insertions(+), 62 deletions(-)

diff --git a/api/python/docs/_modules/mxnet/util.html 
b/api/python/docs/_modules/mxnet/util.html
index 435edd8..19d47db 100644
--- a/api/python/docs/_modules/mxnet/util.html
+++ b/api/python/docs/_modules/mxnet/util.html
@@ -1244,7 +1244,7 @@ Edit on Github
     <span class="k">return</span> <span class="n">free_mem</span><span 
class="o">.</span><span class="n">value</span><span class="p">,</span> <span 
class="n">total_mem</span><span class="o">.</span><span class="n">value</span>
 
 
-<div class="viewcode-block" id="set_np_shape"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.set_np_shape">[docs]</a><span 
class="k">def</span> <span class="nf">set_np_shape</span><span 
class="p">(</span><span class="n">active</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">set_np_shape</span><span 
class="p">(</span><span class="n">active</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Turns on/off NumPy shape semantics, in 
which `()` represents the shape of scalar tensors,</span>
 <span class="sd">    and tuples with `0` elements, for example, `(0,)`, `(1, 
0, 2)`, represent the shapes</span>
 <span class="sd">    of zero-size tensors. This is turned off by default for 
keeping backward compatibility.</span>
@@ -1288,10 +1288,10 @@ Edit on Github
                          <span class="s1">&#39; deactivate both of 
them.&#39;</span><span class="p">)</span>
     <span class="n">prev</span> <span class="o">=</span> <span 
class="n">ctypes</span><span class="o">.</span><span 
class="n">c_int</span><span class="p">()</span>
     <span class="n">check_call</span><span class="p">(</span><span 
class="n">_LIB</span><span class="o">.</span><span 
class="n">MXSetIsNumpyShape</span><span class="p">(</span><span 
class="n">ctypes</span><span class="o">.</span><span 
class="n">c_int</span><span class="p">(</span><span 
class="n">active</span><span class="p">),</span> <span 
class="n">ctypes</span><span class="o">.</span><span 
class="n">byref</span><span class="p">(</span><span class="n">prev</span><span 
class="p">)))</span>
-    <span class="k">return</span> <span class="nb">bool</span><span 
class="p">(</span><span class="n">prev</span><span class="o">.</span><span 
class="n">value</span><span class="p">)</span></div>
+    <span class="k">return</span> <span class="nb">bool</span><span 
class="p">(</span><span class="n">prev</span><span class="o">.</span><span 
class="n">value</span><span class="p">)</span>
 
 
-<div class="viewcode-block" id="is_np_shape"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.is_np_shape">[docs]</a><span 
class="k">def</span> <span class="nf">is_np_shape</span><span 
class="p">():</span>
+<span class="k">def</span> <span class="nf">is_np_shape</span><span 
class="p">():</span>
     <span class="sd">&quot;&quot;&quot;Checks whether the NumPy shape 
semantics is currently turned on.</span>
 <span class="sd">    In NumPy shape semantics, `()` represents the shape of 
scalar tensors,</span>
 <span class="sd">    and tuples with `0` elements, for example, `(0,)`, `(1, 
0, 2)`, represent</span>
@@ -1322,7 +1322,7 @@ Edit on Github
 <span class="sd">    &quot;&quot;&quot;</span>
     <span class="n">curr</span> <span class="o">=</span> <span 
class="n">ctypes</span><span class="o">.</span><span 
class="n">c_bool</span><span class="p">()</span>
     <span class="n">check_call</span><span class="p">(</span><span 
class="n">_LIB</span><span class="o">.</span><span 
class="n">MXIsNumpyShape</span><span class="p">(</span><span 
class="n">ctypes</span><span class="o">.</span><span 
class="n">byref</span><span class="p">(</span><span class="n">curr</span><span 
class="p">)))</span>
-    <span class="k">return</span> <span class="n">curr</span><span 
class="o">.</span><span class="n">value</span></div>
+    <span class="k">return</span> <span class="n">curr</span><span 
class="o">.</span><span class="n">value</span>
 
 
 <span class="k">class</span> <span class="nc">_NumpyShapeScope</span><span 
class="p">(</span><span class="nb">object</span><span class="p">):</span>
@@ -1353,7 +1353,7 @@ Edit on Github
             <span class="n">set_np_shape</span><span class="p">(</span><span 
class="bp">self</span><span class="o">.</span><span 
class="n">_prev_is_np_shape</span><span class="p">)</span>
 
 
-<div class="viewcode-block" id="np_shape"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.np_shape">[docs]</a><span 
class="k">def</span> <span class="nf">np_shape</span><span 
class="p">(</span><span class="n">active</span><span class="o">=</span><span 
class="kc">True</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">np_shape</span><span 
class="p">(</span><span class="n">active</span><span class="o">=</span><span 
class="kc">True</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Returns an activated/deactivated NumPy 
shape scope to be used in &#39;with&#39; statement</span>
 <span class="sd">    and captures code that needs the NumPy shape semantics, 
i.e. support of scalar and</span>
 <span class="sd">    zero-size tensors.</span>
@@ -1419,10 +1419,10 @@ Edit on Github
 <span class="sd">            assert arg_shapes[0] == ()</span>
 <span class="sd">            assert out_shapes[0] == ()</span>
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">return</span> <span class="n">_NumpyShapeScope</span><span 
class="p">(</span><span class="n">active</span><span class="p">)</span></div>
+    <span class="k">return</span> <span class="n">_NumpyShapeScope</span><span 
class="p">(</span><span class="n">active</span><span class="p">)</span>
 
 
-<div class="viewcode-block" id="use_np_shape"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.use_np_shape">[docs]</a><span 
class="k">def</span> <span class="nf">use_np_shape</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">use_np_shape</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;A decorator wrapping a function or 
class with activated NumPy-shape semantics.</span>
 <span class="sd">    When `func` is a function, this ensures that the 
execution of the function is scoped with NumPy</span>
 <span class="sd">    shape semantics, such as the support for zero-dim and 
zero size tensors. When</span>
@@ -1493,7 +1493,7 @@ Edit on Github
         <span class="k">return</span> <span class="n">_with_np_shape</span>
     <span class="k">else</span><span class="p">:</span>
         <span class="k">raise</span> <span class="ne">TypeError</span><span 
class="p">(</span><span class="s1">&#39;use_np_shape can only decorate classes 
and callable objects, &#39;</span>
-                        <span class="s1">&#39;while received a </span><span 
class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span 
class="n">format</span><span class="p">(</span><span class="nb">str</span><span 
class="p">(</span><span class="nb">type</span><span class="p">(</span><span 
class="n">func</span><span class="p">))))</span></div>
+                        <span class="s1">&#39;while received a </span><span 
class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span 
class="n">format</span><span class="p">(</span><span class="nb">str</span><span 
class="p">(</span><span class="nb">type</span><span class="p">(</span><span 
class="n">func</span><span class="p">))))</span>
 
 
 <span class="k">def</span> <span class="nf">_sanity_check_params</span><span 
class="p">(</span><span class="n">func_name</span><span class="p">,</span> 
<span class="n">unsupported_params</span><span class="p">,</span> <span 
class="n">param_dict</span><span class="p">):</span>
@@ -1503,7 +1503,7 @@ Edit on Github
                                       <span class="o">.</span><span 
class="n">format</span><span class="p">(</span><span 
class="n">func_name</span><span class="p">,</span> <span 
class="n">param_name</span><span class="p">))</span>
 
 
-<div class="viewcode-block" id="set_module"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.set_module">[docs]</a><span 
class="k">def</span> <span class="nf">set_module</span><span 
class="p">(</span><span class="n">module</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">set_module</span><span 
class="p">(</span><span class="n">module</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Decorator for overriding __module__ on 
a function or class.</span>
 
 <span class="sd">    Example usage::</span>
@@ -1518,7 +1518,7 @@ Edit on Github
         <span class="k">if</span> <span class="n">module</span> <span 
class="ow">is</span> <span class="ow">not</span> <span 
class="kc">None</span><span class="p">:</span>
             <span class="n">func</span><span class="o">.</span><span 
class="vm">__module__</span> <span class="o">=</span> <span 
class="n">module</span>
         <span class="k">return</span> <span class="n">func</span>
-    <span class="k">return</span> <span class="n">decorator</span></div>
+    <span class="k">return</span> <span class="n">decorator</span>
 
 
 <span class="k">class</span> <span class="nc">_NumpyArrayScope</span><span 
class="p">(</span><span class="nb">object</span><span class="p">):</span>
@@ -1546,7 +1546,7 @@ Edit on Github
         <span class="n">_NumpyArrayScope</span><span class="o">.</span><span 
class="n">_current</span><span class="o">.</span><span class="n">value</span> 
<span class="o">=</span> <span class="bp">self</span><span 
class="o">.</span><span class="n">_old_scope</span>
 
 
-<div class="viewcode-block" id="np_array"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.np_array">[docs]</a><span 
class="k">def</span> <span class="nf">np_array</span><span 
class="p">(</span><span class="n">active</span><span class="o">=</span><span 
class="kc">True</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">np_array</span><span 
class="p">(</span><span class="n">active</span><span class="o">=</span><span 
class="kc">True</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Returns an activated/deactivated 
NumPy-array scope to be used in &#39;with&#39; statement</span>
 <span class="sd">    and captures code that needs the NumPy-array 
semantics.</span>
 
@@ -1572,10 +1572,10 @@ Edit on Github
 <span class="sd">    _NumpyShapeScope</span>
 <span class="sd">        A scope object for wrapping the code w/ or w/o 
NumPy-shape semantics.</span>
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">return</span> <span class="n">_NumpyArrayScope</span><span 
class="p">(</span><span class="n">active</span><span class="p">)</span></div>
+    <span class="k">return</span> <span class="n">_NumpyArrayScope</span><span 
class="p">(</span><span class="n">active</span><span class="p">)</span>
 
 
-<div class="viewcode-block" id="is_np_array"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.is_np_array">[docs]</a><span 
class="k">def</span> <span class="nf">is_np_array</span><span 
class="p">():</span>
+<div class="viewcode-block" id="is_np_array"><a class="viewcode-back" 
href="../../api/legacy/image/index.html#mxnet.image.is_np_array">[docs]</a><span
 class="k">def</span> <span class="nf">is_np_array</span><span 
class="p">():</span>
     <span class="sd">&quot;&quot;&quot;Checks whether the NumPy-array 
semantics is currently turned on.</span>
 <span class="sd">    This is currently used in Gluon for checking whether an 
array of type `mxnet.numpy.ndarray`</span>
 <span class="sd">    or `mx.nd.NDArray` should be created. For example, at the 
time when a parameter</span>
@@ -1598,7 +1598,7 @@ Edit on Github
         <span class="n">_NumpyArrayScope</span><span class="o">.</span><span 
class="n">_current</span><span class="p">,</span> <span 
class="s2">&quot;value&quot;</span><span class="p">)</span> <span 
class="k">else</span> <span class="kc">False</span></div>
 
 
-<div class="viewcode-block" id="use_np_array"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.use_np_array">[docs]</a><span 
class="k">def</span> <span class="nf">use_np_array</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">use_np_array</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;A decorator wrapping Gluon `Block`s and 
all its methods, properties, and static functions</span>
 <span class="sd">    with the semantics of NumPy-array, which means that where 
ndarrays are created,</span>
 <span class="sd">    `mxnet.numpy.ndarray`s should be created, instead of 
legacy ndarrays of type `mx.nd.NDArray`.</span>
@@ -1677,10 +1677,10 @@ Edit on Github
         <span class="k">return</span> <span class="n">_with_np_array</span>
     <span class="k">else</span><span class="p">:</span>
         <span class="k">raise</span> <span class="ne">TypeError</span><span 
class="p">(</span><span class="s1">&#39;use_np_array can only decorate classes 
and callable objects, &#39;</span>
-                        <span class="s1">&#39;while received a </span><span 
class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span 
class="n">format</span><span class="p">(</span><span class="nb">str</span><span 
class="p">(</span><span class="nb">type</span><span class="p">(</span><span 
class="n">func</span><span class="p">))))</span></div>
+                        <span class="s1">&#39;while received a </span><span 
class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span 
class="n">format</span><span class="p">(</span><span class="nb">str</span><span 
class="p">(</span><span class="nb">type</span><span class="p">(</span><span 
class="n">func</span><span class="p">))))</span>
 
 
-<div class="viewcode-block" id="use_np"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.use_np">[docs]</a><span 
class="k">def</span> <span class="nf">use_np</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">use_np</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;A convenience decorator for wrapping 
user provided functions and classes in the scope of</span>
 <span class="sd">    both NumPy-shape and NumPy-array semantics, which means 
that (1) empty tuples `()` and tuples</span>
 <span class="sd">    with zeros, such as `(0, 1)`, `(1, 0, 2)`, will be 
treated as scalar tensors&#39; shapes and</span>
@@ -1740,10 +1740,10 @@ Edit on Github
 <span class="sd">    Function or class</span>
 <span class="sd">        A function or class wrapped in the Numpy-shape and 
NumPy-array scope.</span>
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">return</span> <span class="n">use_np_shape</span><span 
class="p">(</span><span class="n">use_np_array</span><span 
class="p">(</span><span class="n">func</span><span class="p">))</span></div>
+    <span class="k">return</span> <span class="n">use_np_shape</span><span 
class="p">(</span><span class="n">use_np_array</span><span 
class="p">(</span><span class="n">func</span><span class="p">))</span>
 
 
-<div class="viewcode-block" id="np_ufunc_legal_option"><a 
class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.np_ufunc_legal_option">[docs]</a><span
 class="k">def</span> <span class="nf">np_ufunc_legal_option</span><span 
class="p">(</span><span class="n">key</span><span class="p">,</span> <span 
class="n">value</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">np_ufunc_legal_option</span><span 
class="p">(</span><span class="n">key</span><span class="p">,</span> <span 
class="n">value</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Checking if ufunc arguments are legal 
inputs</span>
 
 <span class="sd">    Parameters</span>
@@ -1775,10 +1775,10 @@ Edit on Github
                               <span class="s1">&#39;float16&#39;</span><span 
class="p">,</span> <span class="s1">&#39;float32&#39;</span><span 
class="p">,</span> <span class="s1">&#39;float64&#39;</span><span 
class="p">]))</span>
     <span class="k">elif</span> <span class="n">key</span> <span 
class="o">==</span> <span class="s1">&#39;subok&#39;</span><span 
class="p">:</span>
         <span class="k">return</span> <span class="nb">isinstance</span><span 
class="p">(</span><span class="n">value</span><span class="p">,</span> <span 
class="nb">bool</span><span class="p">)</span>
-    <span class="k">return</span> <span class="kc">False</span></div>
+    <span class="k">return</span> <span class="kc">False</span>
 
 
-<div class="viewcode-block" id="wrap_np_unary_func"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.wrap_np_unary_func">[docs]</a><span 
class="k">def</span> <span class="nf">wrap_np_unary_func</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">wrap_np_unary_func</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;A convenience decorator for wrapping 
numpy-compatible unary ufuncs to provide uniform</span>
 <span class="sd">    error handling.</span>
 
@@ -1808,10 +1808,10 @@ Edit on Github
                     <span class="k">raise</span> <span 
class="ne">TypeError</span><span class="p">(</span><span 
class="s2">&quot;</span><span class="si">{}</span><span 
class="s2">=</span><span class="si">{}</span><span class="s2"> not understood 
for operator </span><span class="si">{}</span><span class="s2">&quot;</span>
                                     <span class="o">.</span><span 
class="n">format</span><span class="p">(</span><span class="n">key</span><span 
class="p">,</span> <span class="n">value</span><span class="p">,</span> <span 
class="n">func</span><span class="o">.</span><span 
class="vm">__name__</span><span class="p">))</span>
         <span class="k">return</span> <span class="n">func</span><span 
class="p">(</span><span class="n">x</span><span class="p">,</span> <span 
class="n">out</span><span class="o">=</span><span class="n">out</span><span 
class="p">)</span>
-    <span class="k">return</span> <span 
class="n">_wrap_np_unary_func</span></div>
+    <span class="k">return</span> <span class="n">_wrap_np_unary_func</span>
 
 
-<div class="viewcode-block" id="wrap_np_binary_func"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.wrap_np_binary_func">[docs]</a><span 
class="k">def</span> <span class="nf">wrap_np_binary_func</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">wrap_np_binary_func</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;A convenience decorator for wrapping 
numpy-compatible binary ufuncs to provide uniform</span>
 <span class="sd">    error handling.</span>
 
@@ -1839,11 +1839,11 @@ Edit on Github
                     <span class="c1"># otherwise raise TypeError with not 
understood error message</span>
                     <span class="k">raise</span> <span 
class="ne">TypeError</span><span class="p">(</span><span 
class="s2">&quot;</span><span class="si">{}</span><span class="s2"> 
</span><span class="si">{}</span><span class="s2"> not 
understood&quot;</span><span class="o">.</span><span 
class="n">format</span><span class="p">(</span><span class="n">key</span><span 
class="p">,</span> <span class="n">value</span><span class="p">))</span>
         <span class="k">return</span> <span class="n">func</span><span 
class="p">(</span><span class="n">x1</span><span class="p">,</span> <span 
class="n">x2</span><span class="p">,</span> <span class="n">out</span><span 
class="o">=</span><span class="n">out</span><span class="p">)</span>
-    <span class="k">return</span> <span 
class="n">_wrap_np_binary_func</span></div>
+    <span class="k">return</span> <span class="n">_wrap_np_binary_func</span>
 
 
 <span class="c1"># pylint: disable=exec-used</span>
-<div class="viewcode-block" id="numpy_fallback"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.numpy_fallback">[docs]</a><span 
class="k">def</span> <span class="nf">numpy_fallback</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">numpy_fallback</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;decorator for falling back to offical 
numpy for a specific function&quot;&quot;&quot;</span>
     <span class="k">def</span> <span class="nf">get_ctx</span><span 
class="p">(</span><span class="n">ctx</span><span class="p">,</span> <span 
class="n">new_ctx</span><span class="p">):</span>
         <span class="k">if</span> <span class="n">ctx</span> <span 
class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
@@ -1925,7 +1925,7 @@ Edit on Github
         <span class="n">ret</span> <span class="o">=</span> <span 
class="n">_as_mx_np_array</span><span class="p">(</span><span 
class="n">ret</span><span class="p">,</span> <span class="n">ctx</span><span 
class="o">=</span><span class="n">ctx</span><span class="p">)</span>
         <span class="k">return</span> <span class="n">ret</span>
 
-    <span class="k">return</span> <span 
class="n">_fallback_to_official_np</span></div>
+    <span class="k">return</span> <span 
class="n">_fallback_to_official_np</span>
 <span class="c1"># pylint: enable=exec-used</span>
 
 
@@ -1955,7 +1955,7 @@ Edit on Github
     <span class="k">return</span> <span class="n">cur_state</span>
 
 
-<div class="viewcode-block" id="set_np"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.set_np">[docs]</a><span 
class="k">def</span> <span class="nf">set_np</span><span 
class="p">(</span><span class="n">shape</span><span class="o">=</span><span 
class="kc">True</span><span class="p">,</span> <span 
class="n">array</span><span class="o">=</span><span class="kc">True</span><span 
class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span 
class="kc">False< [...]
+<span class="k">def</span> <span class="nf">set_np</span><span 
class="p">(</span><span class="n">shape</span><span class="o">=</span><span 
class="kc">True</span><span class="p">,</span> <span 
class="n">array</span><span class="o">=</span><span class="kc">True</span><span 
class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span 
class="kc">False</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Setting NumPy shape and array semantics 
at the same time.</span>
 <span class="sd">    It is required to keep NumPy shape semantics active while 
activating NumPy array semantics.</span>
 <span class="sd">    Deactivating NumPy shape semantics while NumPy array 
semantics is still active is not allowed.</span>
@@ -2039,18 +2039,18 @@ Edit on Github
         <span class="k">raise</span> <span class="ne">ValueError</span><span 
class="p">(</span><span class="s1">&#39;NumPy Shape semantics is required in 
using NumPy array semantics.&#39;</span><span class="p">)</span>
     <span class="n">_set_np_array</span><span class="p">(</span><span 
class="n">array</span><span class="p">)</span>
     <span class="n">set_np_shape</span><span class="p">(</span><span 
class="n">shape</span><span class="p">)</span>
-    <span class="n">set_np_default_dtype</span><span class="p">(</span><span 
class="n">dtype</span><span class="p">)</span></div>
+    <span class="n">set_np_default_dtype</span><span class="p">(</span><span 
class="n">dtype</span><span class="p">)</span>
 
 
-<div class="viewcode-block" id="reset_np"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.reset_np">[docs]</a><span 
class="k">def</span> <span class="nf">reset_np</span><span class="p">():</span>
+<span class="k">def</span> <span class="nf">reset_np</span><span 
class="p">():</span>
     <span class="sd">&quot;&quot;&quot;Deactivate NumPy shape and array and 
deafult dtype semantics at the same time.&quot;&quot;&quot;</span>
-    <span class="n">set_np</span><span class="p">(</span><span 
class="n">shape</span><span class="o">=</span><span 
class="kc">False</span><span class="p">,</span> <span 
class="n">array</span><span class="o">=</span><span 
class="kc">False</span><span class="p">,</span> <span 
class="n">dtype</span><span class="o">=</span><span 
class="kc">False</span><span class="p">)</span></div>
+    <span class="n">set_np</span><span class="p">(</span><span 
class="n">shape</span><span class="o">=</span><span 
class="kc">False</span><span class="p">,</span> <span 
class="n">array</span><span class="o">=</span><span 
class="kc">False</span><span class="p">,</span> <span 
class="n">dtype</span><span class="o">=</span><span 
class="kc">False</span><span class="p">)</span>
 
 
 <span class="n">_CUDA_SUCCESS</span> <span class="o">=</span> <span 
class="mi">0</span>
 
 
-<div class="viewcode-block" id="get_cuda_compute_capability"><a 
class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.get_cuda_compute_capability">[docs]</a><span
 class="k">def</span> <span class="nf">get_cuda_compute_capability</span><span 
class="p">(</span><span class="n">ctx</span><span class="p">):</span>
+<span class="k">def</span> <span 
class="nf">get_cuda_compute_capability</span><span class="p">(</span><span 
class="n">ctx</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Returns the cuda compute capability of 
the input `ctx`.</span>
 
 <span class="sd">    Parameters</span>
@@ -2105,10 +2105,10 @@ Edit on Github
         <span class="n">cuda</span><span class="o">.</span><span 
class="n">cuGetErrorString</span><span class="p">(</span><span 
class="n">ret</span><span class="p">,</span> <span class="n">ctypes</span><span 
class="o">.</span><span class="n">byref</span><span class="p">(</span><span 
class="n">error_str</span><span class="p">))</span>
         <span class="k">raise</span> <span class="ne">RuntimeError</span><span 
class="p">(</span><span class="s1">&#39;cuDeviceComputeCapability failed with 
error code </span><span class="si">{}</span><span class="s1">: </span><span 
class="si">{}</span><span class="s1">&#39;</span>
                            <span class="o">.</span><span 
class="n">format</span><span class="p">(</span><span class="n">ret</span><span 
class="p">,</span> <span class="n">error_str</span><span 
class="o">.</span><span class="n">value</span><span class="o">.</span><span 
class="n">decode</span><span class="p">()))</span>
-    <span class="k">return</span> <span class="n">cc_major</span><span 
class="o">.</span><span class="n">value</span> <span class="o">*</span> <span 
class="mi">10</span> <span class="o">+</span> <span 
class="n">cc_minor</span><span class="o">.</span><span 
class="n">value</span></div>
+    <span class="k">return</span> <span class="n">cc_major</span><span 
class="o">.</span><span class="n">value</span> <span class="o">*</span> <span 
class="mi">10</span> <span class="o">+</span> <span 
class="n">cc_minor</span><span class="o">.</span><span class="n">value</span>
 
 
-<div class="viewcode-block" id="default_array"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.default_array">[docs]</a><span 
class="k">def</span> <span class="nf">default_array</span><span 
class="p">(</span><span class="n">source_array</span><span class="p">,</span> 
<span class="n">ctx</span><span class="o">=</span><span 
class="kc">None</span><span class="p">,</span> <span 
class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span 
class="p">):</span>
+<span class="k">def</span> <span class="nf">default_array</span><span 
class="p">(</span><span class="n">source_array</span><span class="p">,</span> 
<span class="n">ctx</span><span class="o">=</span><span 
class="kc">None</span><span class="p">,</span> <span 
class="n">dtype</span><span class="o">=</span><span class="kc">None</span><span 
class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Creates an array from any object 
exposing the default(nd or np) array interface.</span>
 
 <span class="sd">    Parameters</span>
@@ -2132,7 +2132,7 @@ Edit on Github
     <span class="k">if</span> <span class="n">is_np_array</span><span 
class="p">():</span>
         <span class="k">return</span> <span class="n">_mx_np</span><span 
class="o">.</span><span class="n">array</span><span class="p">(</span><span 
class="n">source_array</span><span class="p">,</span> <span 
class="n">ctx</span><span class="o">=</span><span class="n">ctx</span><span 
class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span 
class="n">dtype</span><span class="p">)</span>
     <span class="k">else</span><span class="p">:</span>
-        <span class="k">return</span> <span class="n">_mx_nd</span><span 
class="o">.</span><span class="n">array</span><span class="p">(</span><span 
class="n">source_array</span><span class="p">,</span> <span 
class="n">ctx</span><span class="o">=</span><span class="n">ctx</span><span 
class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span 
class="n">dtype</span><span class="p">)</span></div>
+        <span class="k">return</span> <span class="n">_mx_nd</span><span 
class="o">.</span><span class="n">array</span><span class="p">(</span><span 
class="n">source_array</span><span class="p">,</span> <span 
class="n">ctx</span><span class="o">=</span><span class="n">ctx</span><span 
class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span 
class="n">dtype</span><span class="p">)</span>
 
 <span class="k">class</span> <span 
class="nc">_NumpyDefaultDtypeScope</span><span class="p">(</span><span 
class="nb">object</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Scope for managing NumPy default dtype 
semantics.</span>
@@ -2162,7 +2162,7 @@ Edit on Github
            <span class="bp">self</span><span class="o">.</span><span 
class="n">_prev_is_np_default_dtype</span> <span class="o">!=</span> <span 
class="bp">self</span><span class="o">.</span><span 
class="n">_enter_is_np_default_dtype</span><span class="p">:</span>
             <span class="n">set_np_default_dtype</span><span 
class="p">(</span><span class="bp">self</span><span class="o">.</span><span 
class="n">_prev_is_np_default_dtype</span><span class="p">)</span>
 
-<div class="viewcode-block" id="np_default_dtype"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.np_default_dtype">[docs]</a><span 
class="k">def</span> <span class="nf">np_default_dtype</span><span 
class="p">(</span><span class="n">active</span><span class="o">=</span><span 
class="kc">True</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">np_default_dtype</span><span 
class="p">(</span><span class="n">active</span><span class="o">=</span><span 
class="kc">True</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Returns an activated/deactivated 
NumPy-default_dtype scope to be used in &#39;with&#39; statement</span>
 <span class="sd">    and captures code that needs the NumPy default dtype 
semantics. i.e. default dtype is float64.</span>
 
@@ -2194,9 +2194,9 @@ Edit on Github
 <span class="sd">            assert arr.dtype == &#39;float32&#39;</span>
 
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">return</span> <span 
class="n">_NumpyDefaultDtypeScope</span><span class="p">(</span><span 
class="n">active</span><span class="p">)</span></div>
+    <span class="k">return</span> <span 
class="n">_NumpyDefaultDtypeScope</span><span class="p">(</span><span 
class="n">active</span><span class="p">)</span>
 
-<div class="viewcode-block" id="use_np_default_dtype"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.use_np_default_dtype">[docs]</a><span
 class="k">def</span> <span class="nf">use_np_default_dtype</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">use_np_default_dtype</span><span 
class="p">(</span><span class="n">func</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;A decorator wrapping a function or 
class with activated NumPy-default_dtype semantics.</span>
 <span class="sd">    When `func` is a function, this ensures that the 
execution of the function is scoped with NumPy</span>
 <span class="sd">    default dtype semantics, with the support for float64 as 
default dtype.</span>
@@ -2266,9 +2266,9 @@ Edit on Github
         <span class="k">return</span> <span 
class="n">_with_np_default_dtype</span>
     <span class="k">else</span><span class="p">:</span>
         <span class="k">raise</span> <span class="ne">TypeError</span><span 
class="p">(</span><span class="s1">&#39;use_np_default_dtype can only decorate 
classes and callable objects, &#39;</span>
-                        <span class="s1">&#39;while received a </span><span 
class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span 
class="n">format</span><span class="p">(</span><span class="nb">str</span><span 
class="p">(</span><span class="nb">type</span><span class="p">(</span><span 
class="n">func</span><span class="p">))))</span></div>
+                        <span class="s1">&#39;while received a </span><span 
class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span 
class="n">format</span><span class="p">(</span><span class="nb">str</span><span 
class="p">(</span><span class="nb">type</span><span class="p">(</span><span 
class="n">func</span><span class="p">))))</span>
 
-<div class="viewcode-block" id="is_np_default_dtype"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.is_np_default_dtype">[docs]</a><span 
class="k">def</span> <span class="nf">is_np_default_dtype</span><span 
class="p">():</span>
+<span class="k">def</span> <span class="nf">is_np_default_dtype</span><span 
class="p">():</span>
     <span class="sd">&quot;&quot;&quot;Checks whether the NumPy default dtype 
semantics is currently turned on.</span>
 <span class="sd">    In NumPy default dtype semantics, default dtype is 
float64.</span>
 
@@ -2298,9 +2298,9 @@ Edit on Github
 <span class="sd">    &quot;&quot;&quot;</span>
     <span class="n">curr</span> <span class="o">=</span> <span 
class="n">ctypes</span><span class="o">.</span><span 
class="n">c_bool</span><span class="p">()</span>
     <span class="n">check_call</span><span class="p">(</span><span 
class="n">_LIB</span><span class="o">.</span><span 
class="n">MXIsNumpyDefaultDtype</span><span class="p">(</span><span 
class="n">ctypes</span><span class="o">.</span><span 
class="n">byref</span><span class="p">(</span><span class="n">curr</span><span 
class="p">)))</span>
-    <span class="k">return</span> <span class="n">curr</span><span 
class="o">.</span><span class="n">value</span></div>
+    <span class="k">return</span> <span class="n">curr</span><span 
class="o">.</span><span class="n">value</span>
 
-<div class="viewcode-block" id="set_np_default_dtype"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.set_np_default_dtype">[docs]</a><span
 class="k">def</span> <span class="nf">set_np_default_dtype</span><span 
class="p">(</span><span class="n">is_np_default_dtype</span><span 
class="o">=</span><span class="kc">True</span><span class="p">):</span>  <span 
class="c1"># pylint: disable=redefined-outer-name</span>
+<span class="k">def</span> <span class="nf">set_np_default_dtype</span><span 
class="p">(</span><span class="n">is_np_default_dtype</span><span 
class="o">=</span><span class="kc">True</span><span class="p">):</span>  <span 
class="c1"># pylint: disable=redefined-outer-name</span>
     <span class="sd">&quot;&quot;&quot;Turns on/off NumPy default dtype 
semantics, because mxnet.numpy.ndarray use</span>
 <span class="sd">    32 bit data storage as default (e.g. float32 and int 32) 
while offical NumPy use</span>
 <span class="sd">    64 bit data storage as default (e.g. float64 and 
int64).</span>
@@ -2338,10 +2338,10 @@ Edit on Github
             <span class="n">_set_np_default_dtype_logged</span> <span 
class="o">=</span> <span class="kc">True</span>
     <span class="n">prev</span> <span class="o">=</span> <span 
class="n">ctypes</span><span class="o">.</span><span 
class="n">c_bool</span><span class="p">()</span>
     <span class="n">check_call</span><span class="p">(</span><span 
class="n">_LIB</span><span class="o">.</span><span 
class="n">MXSetIsNumpyDefaultDtype</span><span class="p">(</span><span 
class="n">ctypes</span><span class="o">.</span><span 
class="n">c_bool</span><span class="p">(</span><span 
class="n">is_np_default_dtype</span><span class="p">),</span> <span 
class="n">ctypes</span><span class="o">.</span><span 
class="n">byref</span><span class="p">(</span><span class="n">prev</span><sp 
[...]
-    <span class="k">return</span> <span class="n">prev</span><span 
class="o">.</span><span class="n">value</span></div>
+    <span class="k">return</span> <span class="n">prev</span><span 
class="o">.</span><span class="n">value</span>
 
 
-<div class="viewcode-block" id="getenv"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.getenv">[docs]</a><span 
class="k">def</span> <span class="nf">getenv</span><span 
class="p">(</span><span class="n">name</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">getenv</span><span 
class="p">(</span><span class="n">name</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Get the setting of an environment 
variable from the C Runtime.</span>
 
 <span class="sd">    Parameters</span>
@@ -2356,10 +2356,10 @@ Edit on Github
 <span class="sd">    &quot;&quot;&quot;</span>
     <span class="n">ret</span> <span class="o">=</span> <span 
class="n">ctypes</span><span class="o">.</span><span 
class="n">c_char_p</span><span class="p">()</span>
     <span class="n">check_call</span><span class="p">(</span><span 
class="n">_LIB</span><span class="o">.</span><span 
class="n">MXGetEnv</span><span class="p">(</span><span 
class="n">c_str</span><span class="p">(</span><span class="n">name</span><span 
class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span 
class="n">byref</span><span class="p">(</span><span class="n">ret</span><span 
class="p">)))</span>
-    <span class="k">return</span> <span class="kc">None</span> <span 
class="k">if</span> <span class="n">ret</span><span class="o">.</span><span 
class="n">value</span> <span class="ow">is</span> <span class="kc">None</span> 
<span class="k">else</span> <span class="n">py_str</span><span 
class="p">(</span><span class="n">ret</span><span class="o">.</span><span 
class="n">value</span><span class="p">)</span></div>
+    <span class="k">return</span> <span class="kc">None</span> <span 
class="k">if</span> <span class="n">ret</span><span class="o">.</span><span 
class="n">value</span> <span class="ow">is</span> <span class="kc">None</span> 
<span class="k">else</span> <span class="n">py_str</span><span 
class="p">(</span><span class="n">ret</span><span class="o">.</span><span 
class="n">value</span><span class="p">)</span>
 
 
-<div class="viewcode-block" id="setenv"><a class="viewcode-back" 
href="../../api/util/index.html#mxnet.util.setenv">[docs]</a><span 
class="k">def</span> <span class="nf">setenv</span><span 
class="p">(</span><span class="n">name</span><span class="p">,</span> <span 
class="n">value</span><span class="p">):</span>
+<span class="k">def</span> <span class="nf">setenv</span><span 
class="p">(</span><span class="n">name</span><span class="p">,</span> <span 
class="n">value</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Set an environment variable in the C 
Runtime.</span>
 
 <span class="sd">    Parameters</span>
@@ -2370,7 +2370,7 @@ Edit on Github
 <span class="sd">        The desired value to set the environment value 
to</span>
 <span class="sd">    &quot;&quot;&quot;</span>
     <span class="n">passed_value</span> <span class="o">=</span> <span 
class="kc">None</span> <span class="k">if</span> <span class="n">value</span> 
<span class="ow">is</span> <span class="kc">None</span> <span 
class="k">else</span> <span class="n">c_str</span><span class="p">(</span><span 
class="n">value</span><span class="p">)</span>
-    <span class="n">check_call</span><span class="p">(</span><span 
class="n">_LIB</span><span class="o">.</span><span 
class="n">MXSetEnv</span><span class="p">(</span><span 
class="n">c_str</span><span class="p">(</span><span class="n">name</span><span 
class="p">),</span> <span class="n">passed_value</span><span 
class="p">))</span></div>
+    <span class="n">check_call</span><span class="p">(</span><span 
class="n">_LIB</span><span class="o">.</span><span 
class="n">MXSetEnv</span><span class="p">(</span><span 
class="n">c_str</span><span class="p">(</span><span class="n">name</span><span 
class="p">),</span> <span class="n">passed_value</span><span class="p">))</span>
 </pre></div>
 
         <hr class="feedback-hr-top" />
diff --git a/api/python/docs/api/np/arrays.ndarray.html 
b/api/python/docs/api/np/arrays.ndarray.html
index be53fca..f25dd8d 100644
--- a/api/python/docs/api/np/arrays.ndarray.html
+++ b/api/python/docs/api/np/arrays.ndarray.html
@@ -1399,14 +1399,14 @@ of the array:</p>
 <p><span class="xref std std-ref">Data type objects</span></p>
 </div>
 <p>The data type object associated with the array can be found in the
-<a class="reference internal" 
href="generated/mxnet.np.ndarray.dtype.html#mxnet.np.ndarray.dtype" 
title="mxnet.np.ndarray.dtype"><code class="xref py py-attr docutils literal 
notranslate"><span class="pre">dtype</span></code></a> attribute:</p>
+<a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.dtype" 
title="mxnet.np.ndarray.dtype"><code class="xref py py-attr docutils literal 
notranslate"><span class="pre">dtype</span></code></a> attribute:</p>
 <table class="longtable docutils align-default">
 <colgroup>
 <col style="width: 10%" />
 <col style="width: 90%" />
 </colgroup>
 <tbody>
-<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.dtype.html#mxnet.np.ndarray.dtype" 
title="mxnet.np.ndarray.dtype"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.dtype</span></code></a></p></td>
+<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.dtype" 
title="mxnet.np.ndarray.dtype"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.dtype</span></code></a></p></td>
 <td><p>Data-type of the array’s elements.</p></td>
 </tr>
 </tbody>
@@ -1458,7 +1458,7 @@ more complete description.)</p>
 <col style="width: 90%" />
 </colgroup>
 <tbody>
-<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.item.html#mxnet.np.ndarray.item" 
title="mxnet.np.ndarray.item"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.item</span></code></a>(*args)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.item" 
title="mxnet.np.ndarray.item"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.item</span></code></a>(*args)</p></td>
 <td><p>Copy an element of an array to a standard Python scalar and return 
it.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.copy" 
title="mxnet.np.ndarray.copy"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.copy</span></code></a>([order])</p></td>
@@ -1505,7 +1505,7 @@ replaced with <code class="docutils literal 
notranslate"><span class="pre">n</sp
 <tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.swapaxes" 
title="mxnet.np.ndarray.swapaxes"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.swapaxes</span></code></a>(axis1, 
axis2)</p></td>
 <td><p>Return a copy of the array with axis1 and axis2 interchanged.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.flatten.html#mxnet.np.ndarray.flatten" 
title="mxnet.np.ndarray.flatten"><code class="xref py py-obj docutils literal 
notranslate"><span 
class="pre">ndarray.flatten</span></code></a>([order])</p></td>
+<tr class="row-even"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.flatten" 
title="mxnet.np.ndarray.flatten"><code class="xref py py-obj docutils literal 
notranslate"><span 
class="pre">ndarray.flatten</span></code></a>([order])</p></td>
 <td><p>Return a copy of the array collapsed into one dimension.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.squeeze" 
title="mxnet.np.ndarray.squeeze"><code class="xref py py-obj docutils literal 
notranslate"><span 
class="pre">ndarray.squeeze</span></code></a>([axis])</p></td>
@@ -1614,7 +1614,7 @@ be performed.</p>
 <col style="width: 90%" />
 </colgroup>
 <tbody>
-<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.max.html#mxnet.np.ndarray.max" 
title="mxnet.np.ndarray.max"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.max</span></code></a>([axis, out, 
keepdims])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.max" 
title="mxnet.np.ndarray.max"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.max</span></code></a>([axis, out, 
keepdims])</p></td>
 <td><p>Return the maximum along a given axis.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.argmax" 
title="mxnet.np.ndarray.argmax"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.argmax</span></code></a>([axis, 
out])</p></td>
@@ -1632,13 +1632,13 @@ be performed.</p>
 <tr class="row-even"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.sum" 
title="mxnet.np.ndarray.sum"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.sum</span></code></a>([axis, dtype, out, 
keepdims])</p></td>
 <td><p>Return the sum of the array elements over the given axis.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.mean.html#mxnet.np.ndarray.mean" 
title="mxnet.np.ndarray.mean"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.mean</span></code></a>([axis, dtype, 
out, keepdims])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.mean" 
title="mxnet.np.ndarray.mean"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.mean</span></code></a>([axis, dtype, 
out, keepdims])</p></td>
 <td><p>Returns the average of the array elements along given axis.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.prod" 
title="mxnet.np.ndarray.prod"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.prod</span></code></a>([axis, dtype, 
out, keepdims])</p></td>
 <td><p>Return the product of the array elements over the given axis.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.cumsum.html#mxnet.np.ndarray.cumsum" 
title="mxnet.np.ndarray.cumsum"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.cumsum</span></code></a>([axis, dtype, 
out])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.cumsum" 
title="mxnet.np.ndarray.cumsum"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.cumsum</span></code></a>([axis, dtype, 
out])</p></td>
 <td><p>Return the cumulative sum of the elements along the given axis.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.var" 
title="mxnet.np.ndarray.var"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ndarray.var</span></code></a>([axis, dtype, out, 
ddof, keepdims])</p></td>
diff --git a/api/python/docs/api/np/generated/mxnet.np.ndarray.html 
b/api/python/docs/api/np/generated/mxnet.np.ndarray.html
index fa70632..5cec6d2 100644
--- a/api/python/docs/api/np/generated/mxnet.np.ndarray.html
+++ b/api/python/docs/api/np/generated/mxnet.np.ndarray.html
@@ -1399,7 +1399,7 @@ methods and attributes of an array.</p>
 <tr class="row-odd"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.cosh" title="mxnet.np.ndarray.cosh"><code class="xref 
py py-obj docutils literal notranslate"><span 
class="pre">cosh</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" 
href="mxnet.np.cosh.html#mxnet.np.cosh" title="mxnet.np.cosh"><code class="xref 
py py-func docutils literal notranslate"><span 
class="pre">cosh()</span></code></a>.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" 
href="mxnet.np.ndarray.cumsum.html#mxnet.np.ndarray.cumsum" 
title="mxnet.np.ndarray.cumsum"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">cumsum</span></code></a>([axis, dtype, 
out])</p></td>
+<tr class="row-even"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.cumsum" title="mxnet.np.ndarray.cumsum"><code 
class="xref py py-obj docutils literal notranslate"><span 
class="pre">cumsum</span></code></a>([axis, dtype, out])</p></td>
 <td><p>Return the cumulative sum of the elements along the given axis.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.degrees" title="mxnet.np.ndarray.degrees"><code 
class="xref py py-obj docutils literal notranslate"><span 
class="pre">degrees</span></code></a>(*args, **kwargs)</p></td>
@@ -1429,7 +1429,7 @@ methods and attributes of an array.</p>
 <tr class="row-odd"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.fix" title="mxnet.np.ndarray.fix"><code class="xref py 
py-obj docutils literal notranslate"><span 
class="pre">fix</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" 
href="mxnet.np.fix.html#mxnet.np.fix" title="mxnet.np.fix"><code class="xref py 
py-func docutils literal notranslate"><span 
class="pre">fix()</span></code></a>.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" 
href="mxnet.np.ndarray.flatten.html#mxnet.np.ndarray.flatten" 
title="mxnet.np.ndarray.flatten"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">flatten</span></code></a>([order])</p></td>
+<tr class="row-even"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.flatten" title="mxnet.np.ndarray.flatten"><code 
class="xref py py-obj docutils literal notranslate"><span 
class="pre">flatten</span></code></a>([order])</p></td>
 <td><p>Return a copy of the array collapsed into one dimension.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.flip" title="mxnet.np.ndarray.flip"><code class="xref 
py py-obj docutils literal notranslate"><span 
class="pre">flip</span></code></a>(*args, **kwargs)</p></td>
@@ -1438,7 +1438,7 @@ methods and attributes of an array.</p>
 <tr class="row-even"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.floor" title="mxnet.np.ndarray.floor"><code class="xref 
py py-obj docutils literal notranslate"><span 
class="pre">floor</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" 
href="mxnet.np.floor.html#mxnet.np.floor" title="mxnet.np.floor"><code 
class="xref py py-func docutils literal notranslate"><span 
class="pre">floor()</span></code></a>.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" 
href="mxnet.np.ndarray.item.html#mxnet.np.ndarray.item" 
title="mxnet.np.ndarray.item"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">item</span></code></a>(*args)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.item" title="mxnet.np.ndarray.item"><code class="xref 
py py-obj docutils literal notranslate"><span 
class="pre">item</span></code></a>(*args)</p></td>
 <td><p>Copy an element of an array to a standard Python scalar and return 
it.</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.log" title="mxnet.np.ndarray.log"><code class="xref py 
py-obj docutils literal notranslate"><span 
class="pre">log</span></code></a>(*args, **kwargs)</p></td>
@@ -1456,10 +1456,10 @@ methods and attributes of an array.</p>
 <tr class="row-even"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.log_softmax" title="mxnet.np.ndarray.log_softmax"><code 
class="xref py py-obj docutils literal notranslate"><span 
class="pre">log_softmax</span></code></a>(*args, **kwargs)</p></td>
 <td><p>Convenience fluent method for <a class="reference internal" 
href="#mxnet.np.ndarray.log_softmax" title="mxnet.np.ndarray.log_softmax"><code 
class="xref py py-func docutils literal notranslate"><span 
class="pre">log_softmax()</span></code></a>.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" 
href="mxnet.np.ndarray.max.html#mxnet.np.ndarray.max" 
title="mxnet.np.ndarray.max"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">max</span></code></a>([axis, out, 
keepdims])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.max" title="mxnet.np.ndarray.max"><code class="xref py 
py-obj docutils literal notranslate"><span 
class="pre">max</span></code></a>([axis, out, keepdims])</p></td>
 <td><p>Return the maximum along a given axis.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" 
href="mxnet.np.ndarray.mean.html#mxnet.np.ndarray.mean" 
title="mxnet.np.ndarray.mean"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">mean</span></code></a>([axis, dtype, out, 
keepdims])</p></td>
+<tr class="row-even"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.mean" title="mxnet.np.ndarray.mean"><code class="xref 
py py-obj docutils literal notranslate"><span 
class="pre">mean</span></code></a>([axis, dtype, out, keepdims])</p></td>
 <td><p>Returns the average of the array elements along given axis.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.min" title="mxnet.np.ndarray.min"><code class="xref py 
py-obj docutils literal notranslate"><span 
class="pre">min</span></code></a>([axis, out, keepdims])</p></td>
@@ -1654,7 +1654,7 @@ methods and attributes of an array.</p>
 <tr class="row-odd"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.ctx" title="mxnet.np.ndarray.ctx"><code class="xref py 
py-obj docutils literal notranslate"><span 
class="pre">ctx</span></code></a></p></td>
 <td><p>Device context of the array.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" 
href="mxnet.np.ndarray.dtype.html#mxnet.np.ndarray.dtype" 
title="mxnet.np.ndarray.dtype"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">dtype</span></code></a></p></td>
+<tr class="row-even"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.dtype" title="mxnet.np.ndarray.dtype"><code class="xref 
py py-obj docutils literal notranslate"><span 
class="pre">dtype</span></code></a></p></td>
 <td><p>Data-type of the array’s elements.</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" 
href="#mxnet.np.ndarray.grad" title="mxnet.np.ndarray.grad"><code class="xref 
py py-obj docutils literal notranslate"><span 
class="pre">grad</span></code></a></p></td>
diff --git a/api/python/docs/api/np/routines.array-manipulation.html 
b/api/python/docs/api/np/routines.array-manipulation.html
index 0b3a64b..190503d 100644
--- a/api/python/docs/api/np/routines.array-manipulation.html
+++ b/api/python/docs/api/np/routines.array-manipulation.html
@@ -1225,7 +1225,7 @@ Edit on Github
 <tr class="row-even"><td><p><a class="reference internal" 
href="generated/mxnet.np.ravel.html#mxnet.np.ravel" 
title="mxnet.np.ravel"><code class="xref py py-obj docutils literal 
notranslate"><span class="pre">ravel</span></code></a>(x)</p></td>
 <td><p>Return a contiguous flattened array.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.flatten.html#mxnet.np.ndarray.flatten" 
title="mxnet.np.ndarray.flatten"><code class="xref py py-obj docutils literal 
notranslate"><span 
class="pre">ndarray.flatten</span></code></a>([order])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" 
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.flatten" 
title="mxnet.np.ndarray.flatten"><code class="xref py py-obj docutils literal 
notranslate"><span 
class="pre">ndarray.flatten</span></code></a>([order])</p></td>
 <td><p>Return a copy of the array collapsed into one dimension.</p></td>
 </tr>
 </tbody>
diff --git a/api/python/docs/objects.inv b/api/python/docs/objects.inv
index cf4cc3d..5a05b64 100644
Binary files a/api/python/docs/objects.inv and b/api/python/docs/objects.inv 
differ
diff --git a/api/python/docs/searchindex.js b/api/python/docs/searchindex.js
index 82a994e..edfdea9 100644
--- a/api/python/docs/searchindex.js
+++ b/api/python/docs/searchindex.js
@@ -1 +1 @@
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+Search.setIndex({docnames:["api/autograd/index","api/context/index","api/contrib/autograd/index","api/contrib/index","api/contrib/io/index","api/contrib/ndarray/index","api/contrib/onnx/index","api/contrib/quantization/index","api/contrib/symbol/index","api/contrib/tensorboard/index","api/contrib/tensorrt/index","api/contrib/text/index","api/engine/index","api/executor/index","api/gluon/block","api/gluon/constant","api/gluon/contrib/index","api/gluon/data/index","api/gluon/data/vision/da
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diff --git a/date.txt b/date.txt
deleted file mode 100644
index 147540d..0000000
--- a/date.txt
+++ /dev/null
@@ -1 +0,0 @@
-Thu Sep 24 12:42:39 UTC 2020
diff --git a/feed.xml b/feed.xml
index b121f39..74aa40d 100644
--- a/feed.xml
+++ b/feed.xml
@@ -1 +1 @@
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xmlns="http://www.w3.org/2005/Atom"; ><generator uri="https://jekyllrb.com/"; 
version="4.0.0">Jekyll</generator><link 
href="https://mxnet.apache.org/feed.xml"; rel="self" type="application/atom+xml" 
/><link href="https://mxnet.apache.org/"; rel="alternate" type="text/html" 
/><updated>2020-09-24T12:32:45+00:00</updated><id>https://mxnet.apache.org/feed.xml</id><title
 type="html">Apache MXNet</title><subtitle>A flexible and efficient library for 
deep [...]
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