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The following commit(s) were added to refs/heads/asf-site by this push:
new 1516ef2 Publish triggered by CI
1516ef2 is described below
commit 1516ef268a448287cf03787a4681cd9af7650506
Author: mxnet-ci <mxnet-ci>
AuthorDate: Mon Sep 14 12:59:49 2020 +0000
Publish triggered by CI
---
api/python/docs/_modules/mxnet/util.html | 90 ++++++++++-----------
api/python/docs/api/np/arrays.ndarray.html | 10 +--
.../docs/api/np/generated/mxnet.np.ndarray.html | 12 +--
api/python/docs/objects.inv | Bin 93157 -> 93121 bytes
api/python/docs/searchindex.js | 2 +-
date.txt | 1 -
feed.xml | 2 +-
7 files changed, 58 insertions(+), 59 deletions(-)
diff --git a/api/python/docs/_modules/mxnet/util.html
b/api/python/docs/_modules/mxnet/util.html
index 19d47db..435edd8 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>
-<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>
+<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="sd">"""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">' deactivate both of
them.'</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>
+ <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">def</span> <span class="nf">is_np_shape</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="sd">"""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"> """</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>
+ <span class="k">return</span> <span class="n">curr</span><span
class="o">.</span><span class="n">value</span></div>
<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>
-<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>
+<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="sd">"""Returns an activated/deactivated NumPy
shape scope to be used in 'with' 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"> """</span>
- <span class="k">return</span> <span class="n">_NumpyShapeScope</span><span
class="p">(</span><span class="n">active</span><span class="p">)</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">def</span> <span class="nf">use_np_shape</span><span
class="p">(</span><span class="n">func</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="sd">"""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">'use_np_shape can only decorate classes
and callable objects, '</span>
- <span class="s1">'while received a </span><span
class="si">{}</span><span class="s1">'</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="s1">'while received a </span><span
class="si">{}</span><span class="s1">'</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="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>
-<span class="k">def</span> <span class="nf">set_module</span><span
class="p">(</span><span class="n">module</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="sd">"""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>
+ <span class="k">return</span> <span class="n">decorator</span></div>
<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>
-<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>
+<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="sd">"""Returns an activated/deactivated
NumPy-array scope to be used in 'with' 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"> """</span>
- <span class="k">return</span> <span class="n">_NumpyArrayScope</span><span
class="p">(</span><span class="n">active</span><span class="p">)</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>
-<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>
+<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>
<span class="sd">"""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">"value"</span><span class="p">)</span> <span
class="k">else</span> <span class="kc">False</span></div>
-<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>
+<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="sd">"""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">'use_np_array can only decorate classes
and callable objects, '</span>
- <span class="s1">'while received a </span><span
class="si">{}</span><span class="s1">'</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="s1">'while received a </span><span
class="si">{}</span><span class="s1">'</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="k">def</span> <span class="nf">use_np</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="sd">"""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' 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"> """</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>
+ <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">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>
+<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="sd">"""Checking if ufunc arguments are legal
inputs</span>
<span class="sd"> Parameters</span>
@@ -1775,10 +1775,10 @@ Edit on Github
<span class="s1">'float16'</span><span
class="p">,</span> <span class="s1">'float32'</span><span
class="p">,</span> <span class="s1">'float64'</span><span
class="p">]))</span>
<span class="k">elif</span> <span class="n">key</span> <span
class="o">==</span> <span class="s1">'subok'</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>
+ <span class="k">return</span> <span class="kc">False</span></div>
-<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>
+<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="sd">"""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">"</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">"</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>
+ <span class="k">return</span> <span
class="n">_wrap_np_unary_func</span></div>
-<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>
+<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="sd">"""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">"</span><span class="si">{}</span><span class="s2">
</span><span class="si">{}</span><span class="s2"> not
understood"</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>
+ <span class="k">return</span> <span
class="n">_wrap_np_binary_func</span></div>
<span class="c1"># pylint: disable=exec-used</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>
+<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="sd">"""decorator for falling back to offical
numpy for a specific function"""</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>
+ <span class="k">return</span> <span
class="n">_fallback_to_official_np</span></div>
<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>
-<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>
+<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="sd">"""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">'NumPy Shape semantics is required in
using NumPy array semantics.'</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>
+ <span class="n">set_np_default_dtype</span><span class="p">(</span><span
class="n">dtype</span><span class="p">)</span></div>
-<span class="k">def</span> <span class="nf">reset_np</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="sd">"""Deactivate NumPy shape and array and
deafult dtype semantics at the same time."""</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>
+ <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">_CUDA_SUCCESS</span> <span class="o">=</span> <span
class="mi">0</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>
+<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="sd">"""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">'cuDeviceComputeCapability failed with
error code </span><span class="si">{}</span><span class="s1">: </span><span
class="si">{}</span><span class="s1">'</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>
+ <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">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>
+<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="sd">"""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>
+ <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">class</span> <span
class="nc">_NumpyDefaultDtypeScope</span><span class="p">(</span><span
class="nb">object</span><span class="p">):</span>
<span class="sd">"""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>
-<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>
+<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="sd">"""Returns an activated/deactivated
NumPy-default_dtype scope to be used in 'with' 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 == 'float32'</span>
<span class="sd"> """</span>
- <span class="k">return</span> <span
class="n">_NumpyDefaultDtypeScope</span><span class="p">(</span><span
class="n">active</span><span class="p">)</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">def</span> <span class="nf">use_np_default_dtype</span><span
class="p">(</span><span class="n">func</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="sd">"""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">'use_np_default_dtype can only decorate
classes and callable objects, '</span>
- <span class="s1">'while received a </span><span
class="si">{}</span><span class="s1">'</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="s1">'while received a </span><span
class="si">{}</span><span class="s1">'</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="k">def</span> <span class="nf">is_np_default_dtype</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="sd">"""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"> """</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>
+ <span class="k">return</span> <span class="n">curr</span><span
class="o">.</span><span class="n">value</span></div>
-<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>
+<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="sd">"""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>
+ <span class="k">return</span> <span class="n">prev</span><span
class="o">.</span><span class="n">value</span></div>
-<span class="k">def</span> <span class="nf">getenv</span><span
class="p">(</span><span class="n">name</span><span class="p">):</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="sd">"""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"> """</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>
+ <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">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>
+<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="sd">"""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"> """</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>
+ <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>
</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 d956394..f25dd8d 100644
--- a/api/python/docs/api/np/arrays.ndarray.html
+++ b/api/python/docs/api/np/arrays.ndarray.html
@@ -1461,13 +1461,13 @@ more complete description.)</p>
<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.copy.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>
+<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>
<td><p>Return a coyp of the array, keeping the same context.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.tolist.html#mxnet.np.ndarray.tolist"
title="mxnet.np.ndarray.tolist"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.tolist</span></code></a>()</p></td>
<td><p></p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.astype.html#mxnet.np.ndarray.astype"
title="mxnet.np.ndarray.astype"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.astype</span></code></a>(dtype[, order,
casting, …])</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.astype"
title="mxnet.np.ndarray.astype"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.astype</span></code></a>(dtype[, order,
casting, …])</p></td>
<td><p>Copy of the array, cast to a specified type.</p></td>
</tr>
</tbody>
@@ -1617,16 +1617,16 @@ be performed.</p>
<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.argmax.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>
+<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>
<td><p>Return indices of the maximum values along the given axis.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.min"
title="mxnet.np.ndarray.min"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.min</span></code></a>([axis, out,
keepdims])</p></td>
<td><p>Convenience fluent method for <a class="reference internal"
href="generated/mxnet.np.min.html#mxnet.np.min" title="mxnet.np.min"><code
class="xref py py-func docutils literal notranslate"><span
class="pre">min()</span></code></a>.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.argmin.html#mxnet.np.ndarray.argmin"
title="mxnet.np.ndarray.argmin"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.argmin</span></code></a>([axis,
out])</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.argmin"
title="mxnet.np.ndarray.argmin"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.argmin</span></code></a>([axis,
out])</p></td>
<td><p>Return indices of the minium values along the given axis.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.clip.html#mxnet.np.ndarray.clip"
title="mxnet.np.ndarray.clip"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.clip</span></code></a>([min, max,
out])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.clip"
title="mxnet.np.ndarray.clip"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.clip</span></code></a>([min, max,
out])</p></td>
<td><p>Return an array whose values are limited to [min, max].</p></td>
</tr>
<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>
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 61c993f..5cec6d2 100644
--- a/api/python/docs/api/np/generated/mxnet.np.ndarray.html
+++ b/api/python/docs/api/np/generated/mxnet.np.ndarray.html
@@ -1330,16 +1330,16 @@ methods and attributes of an array.</p>
<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.arctanh" title="mxnet.np.ndarray.arctanh"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">arctanh</span></code></a>(*args, **kwargs)</p></td>
<td><p>Convenience fluent method for <a class="reference internal"
href="mxnet.np.arctanh.html#mxnet.np.arctanh" title="mxnet.np.arctanh"><code
class="xref py py-func docutils literal notranslate"><span
class="pre">arctanh()</span></code></a>.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal"
href="mxnet.np.ndarray.argmax.html#mxnet.np.ndarray.argmax"
title="mxnet.np.ndarray.argmax"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">argmax</span></code></a>([axis, out])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.argmax" title="mxnet.np.ndarray.argmax"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">argmax</span></code></a>([axis, out])</p></td>
<td><p>Return indices of the maximum values along the given axis.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.argmax_channel"
title="mxnet.np.ndarray.argmax_channel"><code class="xref py py-obj docutils
literal notranslate"><span class="pre">argmax_channel</span></code></a>(*args,
**kwargs)</p></td>
<td><p>Convenience fluent method for <a class="reference internal"
href="#mxnet.np.ndarray.argmax_channel"
title="mxnet.np.ndarray.argmax_channel"><code class="xref py py-func docutils
literal notranslate"><span
class="pre">argmax_channel()</span></code></a>.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal"
href="mxnet.np.ndarray.argmin.html#mxnet.np.ndarray.argmin"
title="mxnet.np.ndarray.argmin"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">argmin</span></code></a>([axis, out])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.argmin" title="mxnet.np.ndarray.argmin"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">argmin</span></code></a>([axis, out])</p></td>
<td><p>Return indices of the minium values along the given axis.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="mxnet.np.ndarray.argsort.html#mxnet.np.ndarray.argsort"
title="mxnet.np.ndarray.argsort"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">argsort</span></code></a>([axis, kind,
order])</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.argsort" title="mxnet.np.ndarray.argsort"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">argsort</span></code></a>([axis, kind, order])</p></td>
<td><p>Convenience fluent method for <a class="reference internal"
href="mxnet.np.argsort.html#mxnet.np.argsort" title="mxnet.np.argsort"><code
class="xref py py-func docutils literal notranslate"><span
class="pre">argsort()</span></code></a>.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.as_in_context"
title="mxnet.np.ndarray.as_in_context"><code class="xref py py-obj docutils
literal notranslate"><span
class="pre">as_in_context</span></code></a>(context)</p></td>
@@ -1360,7 +1360,7 @@ methods and attributes of an array.</p>
<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.asscalar" title="mxnet.np.ndarray.asscalar"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">asscalar</span></code></a>()</p></td>
<td><p>Returns a scalar whose value is copied from this array.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal"
href="mxnet.np.ndarray.astype.html#mxnet.np.ndarray.astype"
title="mxnet.np.ndarray.astype"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">astype</span></code></a>(dtype[, order, casting,
subok, copy])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.astype" title="mxnet.np.ndarray.astype"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">astype</span></code></a>(dtype[, order, casting, subok,
copy])</p></td>
<td><p>Copy of the array, cast to a specified type.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.attach_grad" title="mxnet.np.ndarray.attach_grad"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">attach_grad</span></code></a>([grad_req])</p></td>
@@ -1384,10 +1384,10 @@ methods and attributes of an array.</p>
<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.ceil" title="mxnet.np.ndarray.ceil"><code class="xref
py py-obj docutils literal notranslate"><span
class="pre">ceil</span></code></a>(*args, **kwargs)</p></td>
<td><p>Convenience fluent method for <a class="reference internal"
href="mxnet.np.ceil.html#mxnet.np.ceil" title="mxnet.np.ceil"><code class="xref
py py-func docutils literal notranslate"><span
class="pre">ceil()</span></code></a>.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal"
href="mxnet.np.ndarray.clip.html#mxnet.np.ndarray.clip"
title="mxnet.np.ndarray.clip"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">clip</span></code></a>([min, max, out])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.clip" title="mxnet.np.ndarray.clip"><code class="xref
py py-obj docutils literal notranslate"><span
class="pre">clip</span></code></a>([min, max, out])</p></td>
<td><p>Return an array whose values are limited to [min, max].</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="mxnet.np.ndarray.copy.html#mxnet.np.ndarray.copy"
title="mxnet.np.ndarray.copy"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">copy</span></code></a>([order])</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.copy" title="mxnet.np.ndarray.copy"><code class="xref
py py-obj docutils literal notranslate"><span
class="pre">copy</span></code></a>([order])</p></td>
<td><p>Return a coyp of the array, keeping the same context.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.copyto" title="mxnet.np.ndarray.copyto"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">copyto</span></code></a>(other)</p></td>
diff --git a/api/python/docs/objects.inv b/api/python/docs/objects.inv
index 0446986..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 cf4f34f..edfdea9 100644
--- a/api/python/docs/searchindex.js
+++ b/api/python/docs/searchindex.js
@@ -1 +1 @@
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\ No newline at end of file
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diff --git a/date.txt b/date.txt
deleted file mode 100644
index 4cdcb88..0000000
--- a/date.txt
+++ /dev/null
@@ -1 +0,0 @@
-Mon Sep 14 06:46:25 UTC 2020
diff --git a/feed.xml b/feed.xml
index 5dc1d0b..fe29f7d 100644
--- a/feed.xml
+++ b/feed.xml
@@ -1 +1 @@
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/><link href="https://mxnet.apache.org/"; rel="alternate" type="text/html"
/><updated>2020-09-14T06:36:01+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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+<?xml version="1.0" encoding="utf-8"?><feed
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deep [...]
\ No newline at end of file
