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The following commit(s) were added to refs/heads/asf-site by this push:
new 372ab04 Publish triggered by CI
372ab04 is described below
commit 372ab043f9943da136561d41ab6aa37b8b05389f
Author: mxnet-ci <mxnet-ci>
AuthorDate: Sun Aug 23 18:46:03 2020 +0000
Publish triggered by CI
---
api/python/docs/_modules/mxnet/util.html | 90 ++++++++++-----------
api/python/docs/api/np/arrays.indexing.html | 8 +-
api/python/docs/api/np/arrays.ndarray.html | 22 ++---
.../docs/api/np/generated/mxnet.np.ndarray.html | 28 +++----
.../api/np/generated/mxnet.np.ndarray.take.html | 4 +-
.../docs/api/np/generated/mxnet.np.nonzero.html | 2 +-
.../docs/api/np/generated/mxnet.np.reshape.html | 2 +-
api/python/docs/objects.inv | Bin 93352 -> 93309 bytes
api/python/docs/searchindex.js | 2 +-
date.txt | 1 -
feed.xml | 2 +-
11 files changed, 80 insertions(+), 81 deletions(-)
diff --git a/api/python/docs/_modules/mxnet/util.html
b/api/python/docs/_modules/mxnet/util.html
index ea46682..8b5aa0f 100644
--- a/api/python/docs/_modules/mxnet/util.html
+++ b/api/python/docs/_modules/mxnet/util.html
@@ -1236,7 +1236,7 @@
<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">"""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>
@@ -1280,10 +1280,10 @@
<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></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">"""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>
@@ -1314,7 +1314,7 @@
<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></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>
@@ -1345,7 +1345,7 @@
<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">"""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>
@@ -1411,10 +1411,10 @@
<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></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">"""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>
@@ -1485,7 +1485,7 @@
<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></div>
+ <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="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>
@@ -1495,7 +1495,7 @@
<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">"""Decorator for overriding __module__ on
a function or class.</span>
<span class="sd"> Example usage::</span>
@@ -1510,7 +1510,7 @@
<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>
@@ -1538,7 +1538,7 @@
<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">"""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>
@@ -1564,10 +1564,10 @@
<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></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">"""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>
@@ -1590,7 +1590,7 @@
<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>
-<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">"""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>
@@ -1669,10 +1669,10 @@
<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></div>
+ <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 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">"""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>
@@ -1732,10 +1732,10 @@
<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></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">"""Checking if ufunc arguments are legal
inputs</span>
<span class="sd"> Parameters</span>
@@ -1767,10 +1767,10 @@
<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></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">"""A convenience decorator for wrapping
numpy-compatible unary ufuncs to provide uniform</span>
<span class="sd"> error handling.</span>
@@ -1800,10 +1800,10 @@
<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></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">"""A convenience decorator for wrapping
numpy-compatible binary ufuncs to provide uniform</span>
<span class="sd"> error handling.</span>
@@ -1831,11 +1831,11 @@
<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></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">"""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>
@@ -1917,7 +1917,7 @@
<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>
@@ -1947,7 +1947,7 @@
<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">"""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>
@@ -2031,18 +2031,18 @@
<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></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">"""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></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">"""Returns the cuda compute capability of
the input `ctx`.</span>
<span class="sd"> Parameters</span>
@@ -2097,10 +2097,10 @@
<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></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">"""Creates an array from any object
exposing the default(nd or np) array interface.</span>
<span class="sd"> Parameters</span>
@@ -2124,7 +2124,7 @@
<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">"""Scope for managing NumPy default dtype
semantics.</span>
@@ -2154,7 +2154,7 @@
<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">"""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>
@@ -2186,9 +2186,9 @@
<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></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">"""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>
@@ -2258,9 +2258,9 @@
<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></div>
+ <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 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">"""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>
@@ -2290,9 +2290,9 @@
<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></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">"""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>
@@ -2330,10 +2330,10 @@
<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">"""Get the setting of an environment
variable from the C Runtime.</span>
<span class="sd"> Parameters</span>
@@ -2348,10 +2348,10 @@
<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></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">"""Set an environment variable in the C
Runtime.</span>
<span class="sd"> Parameters</span>
@@ -2362,7 +2362,7 @@
<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></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.indexing.html
b/api/python/docs/api/np/arrays.indexing.html
index cd42535..55c071d 100644
--- a/api/python/docs/api/np/arrays.indexing.html
+++ b/api/python/docs/api/np/arrays.indexing.html
@@ -1454,7 +1454,7 @@ shape (10,2,3,4,30) because the (20,)-shaped subspace has
been
replaced with a (2,3,4)-shaped broadcasted indexing subspace. If
we let <em>i, j, k</em> loop over the (2,3,4)-shaped subspace then
<code class="docutils literal notranslate"><span
class="pre">result[...,i,j,k,:]</span> <span class="pre">=</span> <span
class="pre">x[...,ind[i,j,k],:]</span></code>. This example
-produces the same result as <a class="reference internal"
href="generated/mxnet.np.ndarray.take.html#mxnet.np.ndarray.take"
title="mxnet.np.ndarray.take"><code class="xref py py-meth docutils literal
notranslate"><span class="pre">x.take(ind,</span> <span
class="pre">axis=-2)</span></code></a>.</p>
+produces the same result as <a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.take"
title="mxnet.np.ndarray.take"><code class="xref py py-meth docutils literal
notranslate"><span class="pre">x.take(ind,</span> <span
class="pre">axis=-2)</span></code></a>.</p>
</div>
<div class="admonition-example admonition">
<p class="admonition-title">Example</p>
@@ -1466,7 +1466,7 @@ and <code class="docutils literal notranslate"><span
class="pre">ind_2</span></c
<code class="docutils literal notranslate"><span
class="pre">x[:,ind_1,:,ind_2]</span></code> has shape (2,3,4,10,30,50) because
there
is no unambiguous place to drop in the indexing subspace, thus
it is tacked-on to the beginning. It is always possible to use
-<a class="reference internal"
href="generated/mxnet.np.ndarray.transpose.html#mxnet.np.ndarray.transpose"
title="mxnet.np.ndarray.transpose"><code class="xref py py-meth docutils
literal notranslate"><span class="pre">.transpose()</span></code></a> to move
the subspace
+<a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.transpose"
title="mxnet.np.ndarray.transpose"><code class="xref py py-meth docutils
literal notranslate"><span class="pre">.transpose()</span></code></a> to move
the subspace
anywhere desired. Note that this example cannot be replicated
using <code class="xref py py-func docutils literal notranslate"><span
class="pre">take()</span></code>.</p>
</div>
@@ -1477,8 +1477,8 @@ using <code class="xref py py-func docutils literal
notranslate"><span class="pr
<p>This advanced indexing occurs when obj is an array object of Boolean
type, such as may be returned from comparison operators. A single
boolean index array is practically identical to <code class="docutils literal
notranslate"><span class="pre">x[obj.nonzero()]</span></code> where,
-as described above, <a class="reference internal"
href="generated/mxnet.np.ndarray.nonzero.html#mxnet.np.ndarray.nonzero"
title="mxnet.np.ndarray.nonzero"><code class="xref py py-meth docutils literal
notranslate"><span class="pre">obj.nonzero()</span></code></a> returns a
-tuple (of length <a class="reference internal"
href="generated/mxnet.np.ndarray.ndim.html#mxnet.np.ndarray.ndim"
title="mxnet.np.ndarray.ndim"><code class="xref py py-attr docutils literal
notranslate"><span class="pre">obj.ndim</span></code></a>) of integer index
+as described above, <a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.nonzero"
title="mxnet.np.ndarray.nonzero"><code class="xref py py-meth docutils literal
notranslate"><span class="pre">obj.nonzero()</span></code></a> returns a
+tuple (of length <a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.ndim"
title="mxnet.np.ndarray.ndim"><code class="xref py py-attr docutils literal
notranslate"><span class="pre">obj.ndim</span></code></a>) of integer index
arrays showing the <code class="xref py py-const docutils literal
notranslate"><span class="pre">True</span></code> elements of <em>obj</em>.
However, it is
faster when <code class="docutils literal notranslate"><span
class="pre">obj.shape</span> <span class="pre">==</span> <span
class="pre">x.shape</span></code>.</p>
<p>If <code class="docutils literal notranslate"><span
class="pre">obj.ndim</span> <span class="pre">==</span> <span
class="pre">x.ndim</span></code>, <code class="docutils literal
notranslate"><span class="pre">x[obj]</span></code> returns a 1-dimensional
array
diff --git a/api/python/docs/api/np/arrays.ndarray.html
b/api/python/docs/api/np/arrays.ndarray.html
index 665da0a..829695b 100644
--- a/api/python/docs/api/np/arrays.ndarray.html
+++ b/api/python/docs/api/np/arrays.ndarray.html
@@ -1375,7 +1375,7 @@ of the array:</p>
<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.shape"
title="mxnet.np.ndarray.shape"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.shape</span></code></a></p></td>
<td><p>Tuple of array dimensions.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.ndim.html#mxnet.np.ndarray.ndim"
title="mxnet.np.ndarray.ndim"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.ndim</span></code></a></p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.ndim"
title="mxnet.np.ndarray.ndim"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.ndim</span></code></a></p></td>
<td><p>Number of array dimensions.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.size"
title="mxnet.np.ndarray.size"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.size</span></code></a></p></td>
@@ -1496,13 +1496,13 @@ replaced with <code class="docutils literal
notranslate"><span class="pre">n</sp
<col style="width: 90%" />
</colgroup>
<tbody>
-<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.reshape.html#mxnet.np.ndarray.reshape"
title="mxnet.np.ndarray.reshape"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.reshape</span></code></a>(*args,
**kwargs)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.reshape"
title="mxnet.np.ndarray.reshape"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.reshape</span></code></a>(*args,
**kwargs)</p></td>
<td><p>Returns a copy of the array with a new shape.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.transpose.html#mxnet.np.ndarray.transpose"
title="mxnet.np.ndarray.transpose"><code class="xref py py-obj docutils literal
notranslate"><span
class="pre">ndarray.transpose</span></code></a>(*axes)</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.transpose"
title="mxnet.np.ndarray.transpose"><code class="xref py py-obj docutils literal
notranslate"><span
class="pre">ndarray.transpose</span></code></a>(*axes)</p></td>
<td><p>Permute the dimensions of an array.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.swapaxes.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>
+<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.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>
@@ -1530,13 +1530,13 @@ the operation should proceed.</p>
<col style="width: 90%" />
</colgroup>
<tbody>
-<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.nonzero.html#mxnet.np.ndarray.nonzero"
title="mxnet.np.ndarray.nonzero"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.nonzero</span></code></a>()</p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.nonzero"
title="mxnet.np.ndarray.nonzero"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.nonzero</span></code></a>()</p></td>
<td><p>Return the indices of the elements that are non-zero.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.take.html#mxnet.np.ndarray.take"
title="mxnet.np.ndarray.take"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.take</span></code></a>(indices[, axis,
mode])</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.take"
title="mxnet.np.ndarray.take"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.take</span></code></a>(indices[, axis,
mode])</p></td>
<td><p>Convenience fluent method for <code class="xref py py-func docutils
literal notranslate"><span class="pre">take()</span></code>.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.repeat.html#mxnet.np.ndarray.repeat"
title="mxnet.np.ndarray.repeat"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.repeat</span></code></a>(repeats[,
axis])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.repeat"
title="mxnet.np.ndarray.repeat"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.repeat</span></code></a>(repeats[,
axis])</p></td>
<td><p>Repeat elements of an array.</p></td>
</tr>
</tbody>
@@ -1620,7 +1620,7 @@ be performed.</p>
<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.min.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>
+<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.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>
@@ -1629,19 +1629,19 @@ be performed.</p>
<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.sum.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>
+<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.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.prod.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>
+<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.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.var.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>
+<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>
<td><p>Returns the variance of the array elements, along given axis.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal"
href="generated/mxnet.np.ndarray.html#mxnet.np.ndarray.std"
title="mxnet.np.ndarray.std"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndarray.std</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 6585b70..388c4fb 100644
--- a/api/python/docs/api/np/generated/mxnet.np.ndarray.html
+++ b/api/python/docs/api/np/generated/mxnet.np.ndarray.html
@@ -1462,7 +1462,7 @@ methods and attributes of an array.</p>
<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.html#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>
+<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>
<td><p>Convenience fluent method for <a class="reference internal"
href="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="#mxnet.np.ndarray.nanprod" title="mxnet.np.ndarray.nanprod"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">nanprod</span></code></a>(*args, **kwargs)</p></td>
@@ -1471,7 +1471,7 @@ methods and attributes of an array.</p>
<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.nansum" title="mxnet.np.ndarray.nansum"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">nansum</span></code></a>(*args, **kwargs)</p></td>
<td><p>Convenience fluent method for <a class="reference internal"
href="#mxnet.np.ndarray.nansum" title="mxnet.np.ndarray.nansum"><code
class="xref py py-func docutils literal notranslate"><span
class="pre">nansum()</span></code></a>.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="mxnet.np.ndarray.nonzero.html#mxnet.np.ndarray.nonzero"
title="mxnet.np.ndarray.nonzero"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">nonzero</span></code></a>()</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.nonzero" title="mxnet.np.ndarray.nonzero"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">nonzero</span></code></a>()</p></td>
<td><p>Return the indices of the elements that are non-zero.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.norm" title="mxnet.np.ndarray.norm"><code class="xref
py py-obj docutils literal notranslate"><span
class="pre">norm</span></code></a>(*args, **kwargs)</p></td>
@@ -1489,7 +1489,7 @@ methods and attributes of an array.</p>
<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.pick" title="mxnet.np.ndarray.pick"><code class="xref
py py-obj docutils literal notranslate"><span
class="pre">pick</span></code></a>(*args, **kwargs)</p></td>
<td><p>Convenience fluent method for <a class="reference internal"
href="#mxnet.np.ndarray.pick" title="mxnet.np.ndarray.pick"><code class="xref
py py-func docutils literal notranslate"><span
class="pre">pick()</span></code></a>.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="mxnet.np.ndarray.prod.html#mxnet.np.ndarray.prod"
title="mxnet.np.ndarray.prod"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">prod</span></code></a>([axis, dtype, out,
keepdims])</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.prod" title="mxnet.np.ndarray.prod"><code class="xref
py py-obj docutils literal notranslate"><span
class="pre">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="#mxnet.np.ndarray.radians" title="mxnet.np.ndarray.radians"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">radians</span></code></a>(*args, **kwargs)</p></td>
@@ -1504,10 +1504,10 @@ methods and attributes of an array.</p>
<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.relu" title="mxnet.np.ndarray.relu"><code class="xref
py py-obj docutils literal notranslate"><span
class="pre">relu</span></code></a>(*args, **kwargs)</p></td>
<td><p>Convenience fluent method for <a class="reference internal"
href="#mxnet.np.ndarray.relu" title="mxnet.np.ndarray.relu"><code class="xref
py py-func docutils literal notranslate"><span
class="pre">relu()</span></code></a>.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal"
href="mxnet.np.ndarray.repeat.html#mxnet.np.ndarray.repeat"
title="mxnet.np.ndarray.repeat"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">repeat</span></code></a>(repeats[,
axis])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.repeat" title="mxnet.np.ndarray.repeat"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">repeat</span></code></a>(repeats[, axis])</p></td>
<td><p>Repeat elements of an array.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="mxnet.np.ndarray.reshape.html#mxnet.np.ndarray.reshape"
title="mxnet.np.ndarray.reshape"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">reshape</span></code></a>(*args,
**kwargs)</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.reshape" title="mxnet.np.ndarray.reshape"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">reshape</span></code></a>(*args, **kwargs)</p></td>
<td><p>Returns a copy of the array with a new shape.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.reshape_like"
title="mxnet.np.ndarray.reshape_like"><code class="xref py py-obj docutils
literal notranslate"><span class="pre">reshape_like</span></code></a>(*args,
**kwargs)</p></td>
@@ -1588,14 +1588,14 @@ methods and attributes of an array.</p>
<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.std" title="mxnet.np.ndarray.std"><code class="xref py
py-obj docutils literal notranslate"><span
class="pre">std</span></code></a>([axis, dtype, out, ddof, keepdims])</p></td>
<td><p>Returns the standard deviation of the array elements along given
axis.</p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal"
href="mxnet.np.ndarray.sum.html#mxnet.np.ndarray.sum"
title="mxnet.np.ndarray.sum"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">sum</span></code></a>([axis, dtype, out,
keepdims])</p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.sum" title="mxnet.np.ndarray.sum"><code class="xref py
py-obj docutils literal notranslate"><span
class="pre">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-even"><td><p><a class="reference internal"
href="mxnet.np.ndarray.swapaxes.html#mxnet.np.ndarray.swapaxes"
title="mxnet.np.ndarray.swapaxes"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">swapaxes</span></code></a>(axis1, axis2)</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.swapaxes" title="mxnet.np.ndarray.swapaxes"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">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-odd"><td><p><a class="reference internal"
href="mxnet.np.ndarray.take.html#mxnet.np.ndarray.take"
title="mxnet.np.ndarray.take"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">take</span></code></a>(indices[, axis,
mode])</p></td>
-<td><p>Convenience fluent method for <a class="reference internal"
href="mxnet.np.ndarray.take.html#mxnet.np.ndarray.take"
title="mxnet.np.ndarray.take"><code class="xref py py-func docutils literal
notranslate"><span class="pre">take()</span></code></a>.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.take" title="mxnet.np.ndarray.take"><code class="xref
py py-obj docutils literal notranslate"><span
class="pre">take</span></code></a>(indices[, axis, mode])</p></td>
+<td><p>Convenience fluent method for <a class="reference internal"
href="#mxnet.np.ndarray.take" title="mxnet.np.ndarray.take"><code class="xref
py py-func docutils literal notranslate"><span
class="pre">take()</span></code></a>.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.tan" title="mxnet.np.ndarray.tan"><code class="xref py
py-obj docutils literal notranslate"><span
class="pre">tan</span></code></a>(*args, **kwargs)</p></td>
<td><p>Convenience fluent method for <a class="reference internal"
href="mxnet.np.tan.html#mxnet.np.tan" title="mxnet.np.tan"><code class="xref py
py-func docutils literal notranslate"><span
class="pre">tan()</span></code></a>.</p></td>
@@ -1621,13 +1621,13 @@ methods and attributes of an array.</p>
<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.tostype" title="mxnet.np.ndarray.tostype"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">tostype</span></code></a>(stype)</p></td>
<td><p>Return a copy of the array with chosen storage type.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="mxnet.np.ndarray.transpose.html#mxnet.np.ndarray.transpose"
title="mxnet.np.ndarray.transpose"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">transpose</span></code></a>(*axes)</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.transpose" title="mxnet.np.ndarray.transpose"><code
class="xref py py-obj docutils literal notranslate"><span
class="pre">transpose</span></code></a>(*axes)</p></td>
<td><p>Permute the dimensions of an array.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.trunc" title="mxnet.np.ndarray.trunc"><code class="xref
py py-obj docutils literal notranslate"><span
class="pre">trunc</span></code></a>(*args, **kwargs)</p></td>
<td><p>Convenience fluent method for <a class="reference internal"
href="mxnet.np.trunc.html#mxnet.np.trunc" title="mxnet.np.trunc"><code
class="xref py py-func docutils literal notranslate"><span
class="pre">trunc()</span></code></a>.</p></td>
</tr>
-<tr class="row-even"><td><p><a class="reference internal"
href="mxnet.np.ndarray.var.html#mxnet.np.ndarray.var"
title="mxnet.np.ndarray.var"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">var</span></code></a>([axis, dtype, out, ddof,
keepdims])</p></td>
+<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.var" title="mxnet.np.ndarray.var"><code class="xref py
py-obj docutils literal notranslate"><span
class="pre">var</span></code></a>([axis, dtype, out, ddof, keepdims])</p></td>
<td><p>Returns the variance of the array elements, along given axis.</p></td>
</tr>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal
notranslate"><span class="pre">wait_to_read</span></code>()</p></td>
@@ -1663,7 +1663,7 @@ methods and attributes of an array.</p>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal
notranslate"><span class="pre">handle</span></code></p></td>
<td><p></p></td>
</tr>
-<tr class="row-odd"><td><p><a class="reference internal"
href="mxnet.np.ndarray.ndim.html#mxnet.np.ndarray.ndim"
title="mxnet.np.ndarray.ndim"><code class="xref py py-obj docutils literal
notranslate"><span class="pre">ndim</span></code></a></p></td>
+<tr class="row-odd"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.ndim" title="mxnet.np.ndarray.ndim"><code class="xref
py py-obj docutils literal notranslate"><span
class="pre">ndim</span></code></a></p></td>
<td><p>Number of array dimensions.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal"
href="#mxnet.np.ndarray.shape" title="mxnet.np.ndarray.shape"><code class="xref
py py-obj docutils literal notranslate"><span
class="pre">shape</span></code></a></p></td>
@@ -2765,8 +2765,8 @@ Refer to <cite>mxnet.numpy.swapaxes</cite> for full
documentation.</p>
<dl class="method">
<dt id="mxnet.np.ndarray.take">
<code class="sig-name descname">take</code><span class="sig-paren">(</span><em
class="sig-param">indices</em>, <em class="sig-param">axis=None</em>, <em
class="sig-param">mode='raise'</em><span class="sig-paren">)</span><a
class="headerlink" href="#mxnet.np.ndarray.take" title="Permalink to this
definition">¶</a></dt>
-<dd><p>Convenience fluent method for <a class="reference internal"
href="mxnet.np.ndarray.take.html#mxnet.np.ndarray.take"
title="mxnet.np.ndarray.take"><code class="xref py py-func docutils literal
notranslate"><span class="pre">take()</span></code></a>.</p>
-<p>The arguments are the same as for <a class="reference internal"
href="mxnet.np.ndarray.take.html#mxnet.np.ndarray.take"
title="mxnet.np.ndarray.take"><code class="xref py py-func docutils literal
notranslate"><span class="pre">take()</span></code></a>, with
+<dd><p>Convenience fluent method for <a class="reference internal"
href="#mxnet.np.ndarray.take" title="mxnet.np.ndarray.take"><code class="xref
py py-func docutils literal notranslate"><span
class="pre">take()</span></code></a>.</p>
+<p>The arguments are the same as for <a class="reference internal"
href="#mxnet.np.ndarray.take" title="mxnet.np.ndarray.take"><code class="xref
py py-func docutils literal notranslate"><span
class="pre">take()</span></code></a>, with
this array as data.</p>
</dd></dl>
diff --git a/api/python/docs/api/np/generated/mxnet.np.ndarray.take.html
b/api/python/docs/api/np/generated/mxnet.np.ndarray.take.html
index 770affa..9bfb0c6 100644
--- a/api/python/docs/api/np/generated/mxnet.np.ndarray.take.html
+++ b/api/python/docs/api/np/generated/mxnet.np.ndarray.take.html
@@ -1201,8 +1201,8 @@ Show Source
<dl class="method">
<dt id="mxnet.np.ndarray.take">
<code class="sig-prename descclassname">ndarray.</code><code class="sig-name
descname">take</code><span class="sig-paren">(</span><em
class="sig-param">indices</em>, <em class="sig-param">axis=None</em>, <em
class="sig-param">mode='raise'</em><span class="sig-paren">)</span><a
class="headerlink" href="#mxnet.np.ndarray.take" title="Permalink to this
definition">¶</a></dt>
-<dd><p>Convenience fluent method for <a class="reference internal"
href="#mxnet.np.ndarray.take" title="mxnet.np.ndarray.take"><code class="xref
py py-func docutils literal notranslate"><span
class="pre">take()</span></code></a>.</p>
-<p>The arguments are the same as for <a class="reference internal"
href="#mxnet.np.ndarray.take" title="mxnet.np.ndarray.take"><code class="xref
py py-func docutils literal notranslate"><span
class="pre">take()</span></code></a>, with
+<dd><p>Convenience fluent method for <a class="reference internal"
href="mxnet.np.ndarray.html#mxnet.np.ndarray.take"
title="mxnet.np.ndarray.take"><code class="xref py py-func docutils literal
notranslate"><span class="pre">take()</span></code></a>.</p>
+<p>The arguments are the same as for <a class="reference internal"
href="mxnet.np.ndarray.html#mxnet.np.ndarray.take"
title="mxnet.np.ndarray.take"><code class="xref py py-func docutils literal
notranslate"><span class="pre">take()</span></code></a>, with
this array as data.</p>
</dd></dl>
diff --git a/api/python/docs/api/np/generated/mxnet.np.nonzero.html
b/api/python/docs/api/np/generated/mxnet.np.nonzero.html
index 09bc010..ab9e166 100644
--- a/api/python/docs/api/np/generated/mxnet.np.nonzero.html
+++ b/api/python/docs/api/np/generated/mxnet.np.nonzero.html
@@ -1216,7 +1216,7 @@ which returns a row for each non-zero element.</p>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
-<dt><a class="reference internal"
href="mxnet.np.ndarray.nonzero.html#mxnet.np.ndarray.nonzero"
title="mxnet.np.ndarray.nonzero"><code class="xref py py-func docutils literal
notranslate"><span
class="pre">ndarray.nonzero()</span></code></a></dt><dd><p>Equivalent ndarray
method.</p>
+<dt><a class="reference internal"
href="mxnet.np.ndarray.html#mxnet.np.ndarray.nonzero"
title="mxnet.np.ndarray.nonzero"><code class="xref py py-func docutils literal
notranslate"><span
class="pre">ndarray.nonzero()</span></code></a></dt><dd><p>Equivalent ndarray
method.</p>
</dd>
</dl>
</div>
diff --git a/api/python/docs/api/np/generated/mxnet.np.reshape.html
b/api/python/docs/api/np/generated/mxnet.np.reshape.html
index 96e4e4c..5df70c2 100644
--- a/api/python/docs/api/np/generated/mxnet.np.reshape.html
+++ b/api/python/docs/api/np/generated/mxnet.np.reshape.html
@@ -1232,7 +1232,7 @@ generated.</p>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
-<dt><a class="reference internal"
href="mxnet.np.ndarray.reshape.html#mxnet.np.ndarray.reshape"
title="mxnet.np.ndarray.reshape"><code class="xref py py-func docutils literal
notranslate"><span
class="pre">ndarray.reshape()</span></code></a></dt><dd><p>Equivalent
method.</p>
+<dt><a class="reference internal"
href="mxnet.np.ndarray.html#mxnet.np.ndarray.reshape"
title="mxnet.np.ndarray.reshape"><code class="xref py py-func docutils literal
notranslate"><span
class="pre">ndarray.reshape()</span></code></a></dt><dd><p>Equivalent
method.</p>
</dd>
</dl>
</div>
diff --git a/api/python/docs/objects.inv b/api/python/docs/objects.inv
index 2b6b8d35..77ba1e9 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 19a66b2..65125ae 100644
--- a/api/python/docs/searchindex.js
+++ b/api/python/docs/searchindex.js
@@ -1 +1 @@
-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
[...]
\ No newline at end of file
+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
[...]
\ No newline at end of file
diff --git a/date.txt b/date.txt
deleted file mode 100644
index 8bbeea0..0000000
--- a/date.txt
+++ /dev/null
@@ -1 +0,0 @@
-Sun Aug 23 12:43:43 UTC 2020
diff --git a/feed.xml b/feed.xml
index 50ef6ec..ebe3493 100644
--- a/feed.xml
+++ b/feed.xml
@@ -1 +1 @@
-<?xml version="1.0" encoding="utf-8"?><feed
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>2020-08-23T12:34:14+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 [...]
\ No newline at end of file
+<?xml version="1.0" encoding="utf-8"?><feed
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>2020-08-23T18:35:07+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 [...]
\ No newline at end of file
