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in repository https://gitbox.apache.org/repos/asf/incubator-mxnet-site.git
The following commit(s) were added to refs/heads/asf-site by this push:
new 62c7066 Publish triggered by CI
62c7066 is described below
commit 62c706643c5fb15b71792d6e1668ed232a23a4cc
Author: mxnet-ci <mxnet-ci>
AuthorDate: Thu Oct 8 00:44:43 2020 +0000
Publish triggered by CI
---
api/python/docs/_modules/mxnet/util.html | 90 +++++++++++-----------
.../performance/backend/mkldnn/mkldnn_readme.ipynb | 6 +-
api/python/docs/searchindex.js | 2 +-
.../performance/backend/mkldnn/mkldnn_readme.html | 6 +-
.../backend/mkldnn/mkldnn_readme.html.bak | 6 +-
date.txt | 1 -
feed.xml | 2 +-
.../api/python/docs/_modules/mxnet/util.html | 90 +++++++++++-----------
.../performance/backend/mkldnn/mkldnn_readme.ipynb | 6 +-
versions/master/api/python/docs/searchindex.js | 2 +-
.../performance/backend/mkldnn/mkldnn_readme.html | 6 +-
.../backend/mkldnn/mkldnn_readme.html.bak | 6 +-
versions/master/feed.xml | 2 +-
13 files changed, 112 insertions(+), 113 deletions(-)
diff --git a/api/python/docs/_modules/mxnet/util.html
b/api/python/docs/_modules/mxnet/util.html
index 62f0ebb..be8123b 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/_sources/tutorials/performance/backend/mkldnn/mkldnn_readme.ipynb
b/api/python/docs/_sources/tutorials/performance/backend/mkldnn/mkldnn_readme.ipynb
index b4e8f62..b4219239 100644
---
a/api/python/docs/_sources/tutorials/performance/backend/mkldnn/mkldnn_readme.ipynb
+++
b/api/python/docs/_sources/tutorials/performance/backend/mkldnn/mkldnn_readme.ipynb
@@ -201,7 +201,7 @@
"1. If [Microsoft Visual Studio
2015](https://www.visualstudio.com/vs/older-downloads/) is not already
installed, download and install it. You can download and install the free
community edition.\n",
"2. Download and Install [CMake
3](https://cmake.org/files/v3.14/cmake-3.14.0-win64-x64.msi) if it is not
already installed.\n",
"3. Download [OpenCV
3](https://sourceforge.net/projects/opencvlibrary/files/3.4.5/opencv-3.4.5-vc14_vc15.exe/download),
and unzip the OpenCV package, set the environment variable ```OpenCV_DIR``` to
point to the ```OpenCV build directory``` (e.g.,```OpenCV_DIR =
C:\\opencv\\build ```). Also, add the OpenCV bin directory
(```C:\\opencv\\build\\x64\\vc14\\bin``` for example) to the ``PATH``
variable.\n",
- "4. If you have Intel Math Kernel Library (Intel MKL) installed, set
```MKL_ROOT``` to point to ```MKL``` directory that contains the ```include```
and ```lib```. If you want to use MKL blas, you should set ```-DUSE_BLAS=mkl```
when cmake. Typically, you can find the directory in ```C:\\Program Files
(x86)\\IntelSWTools\\compilers_and_libraries\\windows\\mkl```.\n",
+ "4. If you have Intel Math Kernel Library (Intel MKL) installed, set
```MKLROOT``` environment variable to point to ```MKL``` directory that
contains the ```include``` and ```lib```. If you want to use MKL blas, you
should set ```-DUSE_BLAS=mkl``` when cmake. Typically, you can find the
directory in ```C:\\Program Files
(x86)\\IntelSWTools\\compilers_and_libraries\\windows\\mkl```.\n",
"5. If you don't have the Intel Math Kernel Library (MKL) installed,
download and install
[OpenBLAS](http://sourceforge.net/projects/openblas/files/v0.2.14/), or build
the latest version of OpenBLAS from source. Note that you should also download
```mingw64.dll.zip``` along with openBLAS and add them to PATH.\n",
"6. Set the environment variable ```OpenBLAS_HOME``` to point to the
```OpenBLAS``` directory that contains the ```include``` and ```lib```
directories. Typically, you can find the directory in
```C:\\Downloads\\OpenBLAS\\```.\n",
"\n",
@@ -252,7 +252,7 @@
"source": [
"```\n",
">\"C:\\Program Files
(x86)\\IntelSWTools\\compilers_and_libraries\\windows\\mkl\\bin\\mklvars.bat\"
intel64\n",
- ">cmake -G \"Visual Studio 14 Win64\" .. -DUSE_CUDA=0 -DUSE_CUDNN=0
-DUSE_NVRTC=0 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_PROFILER=1 -DUSE_BLAS=mkl
-DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_NAME=All -DUSE_MKLDNN=1
-DCMAKE_BUILD_TYPE=Release -DMKL_ROOT=\"C:\\Program Files
(x86)\\IntelSWTools\\compilers_and_libraries\\windows\\mkl\"\n",
+ ">cmake -G \"Visual Studio 14 Win64\" .. -DUSE_CUDA=0 -DUSE_CUDNN=0
-DUSE_NVRTC=0 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_PROFILER=1 -DUSE_BLAS=mkl
-DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_NAME=All -DUSE_MKLDNN=1
-DCMAKE_BUILD_TYPE=Release\n",
"```\n"
]
},
@@ -290,7 +290,7 @@
"metadata": {},
"source": [
"```\n",
- ">cmake -G \"Visual Studio 15 Win64\" .. -DUSE_CUDA=0 -DUSE_CUDNN=0
-DUSE_NVRTC=0 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_PROFILER=1 -DUSE_BLAS=mkl
-DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_NAME=All -DUSE_MKLDNN=1
-DCMAKE_BUILD_TYPE=Release -DMKL_ROOT=\"C:\\Program Files
(x86)\\IntelSWTools\\compilers_and_libraries\\windows\\mkl\"\n",
+ ">cmake -G \"Visual Studio 15 Win64\" .. -DUSE_CUDA=0 -DUSE_CUDNN=0
-DUSE_NVRTC=0 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_PROFILER=1 -DUSE_BLAS=mkl
-DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_NAME=All -DUSE_MKLDNN=1
-DCMAKE_BUILD_TYPE=Release\n",
"\n",
"```\n"
]
diff --git a/api/python/docs/searchindex.js b/api/python/docs/searchindex.js
index 404bbbc..ae392ca 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/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html
b/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html
index feb72da..4462a4a 100644
--- a/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html
+++ b/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html
@@ -1291,7 +1291,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
<li><p>If <a class="reference external"
href="https://www.visualstudio.com/vs/older-downloads/";>Microsoft Visual Studio
2015</a> is not already installed, download and install it. You can download
and install the free community edition.</p></li>
<li><p>Download and Install <a class="reference external"
href="https://cmake.org/files/v3.14/cmake-3.14.0-win64-x64.msi";>CMake 3</a> if
it is not already installed.</p></li>
<li><p>Download <a class="reference external"
href="https://sourceforge.net/projects/opencvlibrary/files/3.4.5/opencv-3.4.5-vc14_vc15.exe/download";>OpenCV
3</a>, and unzip the OpenCV package, set the environment variable <code
class="docutils literal notranslate"><span class="pre">OpenCV_DIR</span></code>
to point to the <code class="docutils literal notranslate"><span
class="pre">OpenCV</span> <span class="pre">build</span> <span
class="pre">directory</span></code> (e.g.,``OpenCV_DIR = [...]
-<li><p>If you have Intel Math Kernel Library (Intel MKL) installed, set <code
class="docutils literal notranslate"><span class="pre">MKL_ROOT</span></code>
to point to <code class="docutils literal notranslate"><span
class="pre">MKL</span></code> directory that contains the <code class="docutils
literal notranslate"><span class="pre">include</span></code> and <code
class="docutils literal notranslate"><span class="pre">lib</span></code>. If
you want to use MKL blas, you should set <code [...]
+<li><p>If you have Intel Math Kernel Library (Intel MKL) installed, set <code
class="docutils literal notranslate"><span class="pre">MKLROOT</span></code>
environment variable to point to <code class="docutils literal
notranslate"><span class="pre">MKL</span></code> directory that contains the
<code class="docutils literal notranslate"><span
class="pre">include</span></code> and <code class="docutils literal
notranslate"><span class="pre">lib</span></code>. If you want to use MKL blas,
y [...]
<li><p>If you don’t have the Intel Math Kernel Library (MKL) installed,
download and install <a class="reference external"
href="http://sourceforge.net/projects/openblas/files/v0.2.14/";>OpenBLAS</a>, or
build the latest version of OpenBLAS from source. Note that you should also
download <code class="docutils literal notranslate"><span
class="pre">mingw64.dll.zip</span></code> along with openBLAS and add them to
PATH.</p></li>
<li><p>Set the environment variable <code class="docutils literal
notranslate"><span class="pre">OpenBLAS_HOME</span></code> to point to the
<code class="docutils literal notranslate"><span
class="pre">OpenBLAS</span></code> directory that contains the <code
class="docutils literal notranslate"><span class="pre">include</span></code>
and <code class="docutils literal notranslate"><span
class="pre">lib</span></code> directories. Typically, you can find the
directory in <code class="docuti [...]
</ol>
@@ -1315,7 +1315,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
<li><p>Enable Intel MKL-DNN and Intel MKL as BLAS library by the
command:</p></li>
</ol>
<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="s2">"C:\Program Files
(x86)\IntelSWTools\compilers_and_libraries\windows\mkl</span><span
class="se">\b</span><span class="s2">in\mklvars.bat"</span> <span
class="n">intel64</span>
-<span class="o">></span><span class="n">cmake</span> <span
class="o">-</span><span class="n">G</span> <span class="s2">"Visual Studio
14 Win64"</span> <span class="o">..</span> <span class="o">-</span><span
class="n">DUSE_CUDA</span><span class="o">=</span><span class="mi">0</span>
<span class="o">-</span><span class="n">DUSE_CUDNN</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_NVRTC</span><span class="o">=</span><span cl [...]
+<span class="o">></span><span class="n">cmake</span> <span
class="o">-</span><span class="n">G</span> <span class="s2">"Visual Studio
14 Win64"</span> <span class="o">..</span> <span class="o">-</span><span
class="n">DUSE_CUDA</span><span class="o">=</span><span class="mi">0</span>
<span class="o">-</span><span class="n">DUSE_CUDNN</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_NVRTC</span><span class="o">=</span><span cl [...]
</pre></div>
</div>
<ol class="arabic simple" start="4">
@@ -1330,7 +1330,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
</ol>
<p><strong>Visual Studio 2017</strong></p>
<p>User can follow the same steps of Visual Studio 2015 to build MXNET with
MKL-DNN, but change the version related command, for example,<code
class="docutils literal notranslate"><span
class="pre">C:\opencv\build\x64\vc15\bin</span></code> and build command is as
below:</p>
-<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="n">cmake</span> <span class="o">-</span><span class="n">G</span> <span
class="s2">"Visual Studio 15 Win64"</span> <span class="o">..</span>
<span class="o">-</span><span class="n">DUSE_CUDA</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_CUDNN</span><span class="o">=</span><span class="mi">0</span>
<span [...]
+<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="n">cmake</span> <span class="o">-</span><span class="n">G</span> <span
class="s2">"Visual Studio 15 Win64"</span> <span class="o">..</span>
<span class="o">-</span><span class="n">DUSE_CUDA</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_CUDNN</span><span class="o">=</span><span class="mi">0</span>
<span [...]
</pre></div>
</div>
<h2 id="4"><p>Verify MXNet with python</p>
diff --git
a/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html.bak
b/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html.bak
index 9377698..d41cd62 100644
---
a/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html.bak
+++
b/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html.bak
@@ -1291,7 +1291,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
<li><p>If <a class="reference external"
href="https://www.visualstudio.com/vs/older-downloads/";>Microsoft Visual Studio
2015</a> is not already installed, download and install it. You can download
and install the free community edition.</p></li>
<li><p>Download and Install <a class="reference external"
href="https://cmake.org/files/v3.14/cmake-3.14.0-win64-x64.msi";>CMake 3</a> if
it is not already installed.</p></li>
<li><p>Download <a class="reference external"
href="https://sourceforge.net/projects/opencvlibrary/files/3.4.5/opencv-3.4.5-vc14_vc15.exe/download";>OpenCV
3</a>, and unzip the OpenCV package, set the environment variable <code
class="docutils literal notranslate"><span class="pre">OpenCV_DIR</span></code>
to point to the <code class="docutils literal notranslate"><span
class="pre">OpenCV</span> <span class="pre">build</span> <span
class="pre">directory</span></code> (e.g.,``OpenCV_DIR = [...]
-<li><p>If you have Intel Math Kernel Library (Intel MKL) installed, set <code
class="docutils literal notranslate"><span class="pre">MKL_ROOT</span></code>
to point to <code class="docutils literal notranslate"><span
class="pre">MKL</span></code> directory that contains the <code class="docutils
literal notranslate"><span class="pre">include</span></code> and <code
class="docutils literal notranslate"><span class="pre">lib</span></code>. If
you want to use MKL blas, you should set <code [...]
+<li><p>If you have Intel Math Kernel Library (Intel MKL) installed, set <code
class="docutils literal notranslate"><span class="pre">MKLROOT</span></code>
environment variable to point to <code class="docutils literal
notranslate"><span class="pre">MKL</span></code> directory that contains the
<code class="docutils literal notranslate"><span
class="pre">include</span></code> and <code class="docutils literal
notranslate"><span class="pre">lib</span></code>. If you want to use MKL blas,
y [...]
<li><p>If you don’t have the Intel Math Kernel Library (MKL) installed,
download and install <a class="reference external"
href="http://sourceforge.net/projects/openblas/files/v0.2.14/";>OpenBLAS</a>, or
build the latest version of OpenBLAS from source. Note that you should also
download <code class="docutils literal notranslate"><span
class="pre">mingw64.dll.zip</span></code> along with openBLAS and add them to
PATH.</p></li>
<li><p>Set the environment variable <code class="docutils literal
notranslate"><span class="pre">OpenBLAS_HOME</span></code> to point to the
<code class="docutils literal notranslate"><span
class="pre">OpenBLAS</span></code> directory that contains the <code
class="docutils literal notranslate"><span class="pre">include</span></code>
and <code class="docutils literal notranslate"><span
class="pre">lib</span></code> directories. Typically, you can find the
directory in <code class="docuti [...]
</ol>
@@ -1315,7 +1315,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
<li><p>Enable Intel MKL-DNN and Intel MKL as BLAS library by the
command:</p></li>
</ol>
<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="s2">"C:\Program Files
(x86)\IntelSWTools\compilers_and_libraries\windows\mkl</span><span
class="se">\b</span><span class="s2">in\mklvars.bat"</span> <span
class="n">intel64</span>
-<span class="o">></span><span class="n">cmake</span> <span
class="o">-</span><span class="n">G</span> <span class="s2">"Visual Studio
14 Win64"</span> <span class="o">..</span> <span class="o">-</span><span
class="n">DUSE_CUDA</span><span class="o">=</span><span class="mi">0</span>
<span class="o">-</span><span class="n">DUSE_CUDNN</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_NVRTC</span><span class="o">=</span><span cl [...]
+<span class="o">></span><span class="n">cmake</span> <span
class="o">-</span><span class="n">G</span> <span class="s2">"Visual Studio
14 Win64"</span> <span class="o">..</span> <span class="o">-</span><span
class="n">DUSE_CUDA</span><span class="o">=</span><span class="mi">0</span>
<span class="o">-</span><span class="n">DUSE_CUDNN</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_NVRTC</span><span class="o">=</span><span cl [...]
</pre></div>
</div>
<ol class="arabic simple" start="4">
@@ -1330,7 +1330,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
</ol>
<p><strong>Visual Studio 2017</strong></p>
<p>User can follow the same steps of Visual Studio 2015 to build MXNET with
MKL-DNN, but change the version related command, for example,<code
class="docutils literal notranslate"><span
class="pre">C:\opencv\build\x64\vc15\bin</span></code> and build command is as
below:</p>
-<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="n">cmake</span> <span class="o">-</span><span class="n">G</span> <span
class="s2">"Visual Studio 15 Win64"</span> <span class="o">..</span>
<span class="o">-</span><span class="n">DUSE_CUDA</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_CUDNN</span><span class="o">=</span><span class="mi">0</span>
<span [...]
+<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="n">cmake</span> <span class="o">-</span><span class="n">G</span> <span
class="s2">"Visual Studio 15 Win64"</span> <span class="o">..</span>
<span class="o">-</span><span class="n">DUSE_CUDA</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_CUDNN</span><span class="o">=</span><span class="mi">0</span>
<span [...]
</pre></div>
</div>
<h2 id="4"><p>Verify MXNet with python</p>
diff --git a/date.txt b/date.txt
deleted file mode 100644
index 4696e05..0000000
--- a/date.txt
+++ /dev/null
@@ -1 +0,0 @@
-Wed Oct 7 18:51:32 UTC 2020
diff --git a/feed.xml b/feed.xml
index 42fd0acf..472b204 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/versions/master/feed.xml"; rel="self"
type="application/atom+xml" /><link
href="https://mxnet.apache.org/versions/master/"; rel="alternate"
type="text/html"
/><updated>2020-10-07T18:39:56+00:00</updated><id>https://mxnet.apache.org/versions/master/feed.xml</id><title
type="html">Apache MXNet</title><su [...]
\ 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/versions/master/feed.xml"; rel="self"
type="application/atom+xml" /><link
href="https://mxnet.apache.org/versions/master/"; rel="alternate"
type="text/html"
/><updated>2020-10-08T00:33:13+00:00</updated><id>https://mxnet.apache.org/versions/master/feed.xml</id><title
type="html">Apache MXNet</title><su [...]
\ No newline at end of file
diff --git a/versions/master/api/python/docs/_modules/mxnet/util.html
b/versions/master/api/python/docs/_modules/mxnet/util.html
index 62f0ebb..be8123b 100644
--- a/versions/master/api/python/docs/_modules/mxnet/util.html
+++ b/versions/master/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/versions/master/api/python/docs/_sources/tutorials/performance/backend/mkldnn/mkldnn_readme.ipynb
b/versions/master/api/python/docs/_sources/tutorials/performance/backend/mkldnn/mkldnn_readme.ipynb
index b4e8f62..b4219239 100644
---
a/versions/master/api/python/docs/_sources/tutorials/performance/backend/mkldnn/mkldnn_readme.ipynb
+++
b/versions/master/api/python/docs/_sources/tutorials/performance/backend/mkldnn/mkldnn_readme.ipynb
@@ -201,7 +201,7 @@
"1. If [Microsoft Visual Studio
2015](https://www.visualstudio.com/vs/older-downloads/) is not already
installed, download and install it. You can download and install the free
community edition.\n",
"2. Download and Install [CMake
3](https://cmake.org/files/v3.14/cmake-3.14.0-win64-x64.msi) if it is not
already installed.\n",
"3. Download [OpenCV
3](https://sourceforge.net/projects/opencvlibrary/files/3.4.5/opencv-3.4.5-vc14_vc15.exe/download),
and unzip the OpenCV package, set the environment variable ```OpenCV_DIR``` to
point to the ```OpenCV build directory``` (e.g.,```OpenCV_DIR =
C:\\opencv\\build ```). Also, add the OpenCV bin directory
(```C:\\opencv\\build\\x64\\vc14\\bin``` for example) to the ``PATH``
variable.\n",
- "4. If you have Intel Math Kernel Library (Intel MKL) installed, set
```MKL_ROOT``` to point to ```MKL``` directory that contains the ```include```
and ```lib```. If you want to use MKL blas, you should set ```-DUSE_BLAS=mkl```
when cmake. Typically, you can find the directory in ```C:\\Program Files
(x86)\\IntelSWTools\\compilers_and_libraries\\windows\\mkl```.\n",
+ "4. If you have Intel Math Kernel Library (Intel MKL) installed, set
```MKLROOT``` environment variable to point to ```MKL``` directory that
contains the ```include``` and ```lib```. If you want to use MKL blas, you
should set ```-DUSE_BLAS=mkl``` when cmake. Typically, you can find the
directory in ```C:\\Program Files
(x86)\\IntelSWTools\\compilers_and_libraries\\windows\\mkl```.\n",
"5. If you don't have the Intel Math Kernel Library (MKL) installed,
download and install
[OpenBLAS](http://sourceforge.net/projects/openblas/files/v0.2.14/), or build
the latest version of OpenBLAS from source. Note that you should also download
```mingw64.dll.zip``` along with openBLAS and add them to PATH.\n",
"6. Set the environment variable ```OpenBLAS_HOME``` to point to the
```OpenBLAS``` directory that contains the ```include``` and ```lib```
directories. Typically, you can find the directory in
```C:\\Downloads\\OpenBLAS\\```.\n",
"\n",
@@ -252,7 +252,7 @@
"source": [
"```\n",
">\"C:\\Program Files
(x86)\\IntelSWTools\\compilers_and_libraries\\windows\\mkl\\bin\\mklvars.bat\"
intel64\n",
- ">cmake -G \"Visual Studio 14 Win64\" .. -DUSE_CUDA=0 -DUSE_CUDNN=0
-DUSE_NVRTC=0 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_PROFILER=1 -DUSE_BLAS=mkl
-DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_NAME=All -DUSE_MKLDNN=1
-DCMAKE_BUILD_TYPE=Release -DMKL_ROOT=\"C:\\Program Files
(x86)\\IntelSWTools\\compilers_and_libraries\\windows\\mkl\"\n",
+ ">cmake -G \"Visual Studio 14 Win64\" .. -DUSE_CUDA=0 -DUSE_CUDNN=0
-DUSE_NVRTC=0 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_PROFILER=1 -DUSE_BLAS=mkl
-DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_NAME=All -DUSE_MKLDNN=1
-DCMAKE_BUILD_TYPE=Release\n",
"```\n"
]
},
@@ -290,7 +290,7 @@
"metadata": {},
"source": [
"```\n",
- ">cmake -G \"Visual Studio 15 Win64\" .. -DUSE_CUDA=0 -DUSE_CUDNN=0
-DUSE_NVRTC=0 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_PROFILER=1 -DUSE_BLAS=mkl
-DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_NAME=All -DUSE_MKLDNN=1
-DCMAKE_BUILD_TYPE=Release -DMKL_ROOT=\"C:\\Program Files
(x86)\\IntelSWTools\\compilers_and_libraries\\windows\\mkl\"\n",
+ ">cmake -G \"Visual Studio 15 Win64\" .. -DUSE_CUDA=0 -DUSE_CUDNN=0
-DUSE_NVRTC=0 -DUSE_OPENCV=1 -DUSE_OPENMP=1 -DUSE_PROFILER=1 -DUSE_BLAS=mkl
-DUSE_LAPACK=1 -DUSE_DIST_KVSTORE=0 -DCUDA_ARCH_NAME=All -DUSE_MKLDNN=1
-DCMAKE_BUILD_TYPE=Release\n",
"\n",
"```\n"
]
diff --git a/versions/master/api/python/docs/searchindex.js
b/versions/master/api/python/docs/searchindex.js
index 404bbbc..ae392ca 100644
--- a/versions/master/api/python/docs/searchindex.js
+++ b/versions/master/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/versions/master/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html
b/versions/master/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html
index feb72da..4462a4a 100644
---
a/versions/master/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html
+++
b/versions/master/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html
@@ -1291,7 +1291,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
<li><p>If <a class="reference external"
href="https://www.visualstudio.com/vs/older-downloads/";>Microsoft Visual Studio
2015</a> is not already installed, download and install it. You can download
and install the free community edition.</p></li>
<li><p>Download and Install <a class="reference external"
href="https://cmake.org/files/v3.14/cmake-3.14.0-win64-x64.msi";>CMake 3</a> if
it is not already installed.</p></li>
<li><p>Download <a class="reference external"
href="https://sourceforge.net/projects/opencvlibrary/files/3.4.5/opencv-3.4.5-vc14_vc15.exe/download";>OpenCV
3</a>, and unzip the OpenCV package, set the environment variable <code
class="docutils literal notranslate"><span class="pre">OpenCV_DIR</span></code>
to point to the <code class="docutils literal notranslate"><span
class="pre">OpenCV</span> <span class="pre">build</span> <span
class="pre">directory</span></code> (e.g.,``OpenCV_DIR = [...]
-<li><p>If you have Intel Math Kernel Library (Intel MKL) installed, set <code
class="docutils literal notranslate"><span class="pre">MKL_ROOT</span></code>
to point to <code class="docutils literal notranslate"><span
class="pre">MKL</span></code> directory that contains the <code class="docutils
literal notranslate"><span class="pre">include</span></code> and <code
class="docutils literal notranslate"><span class="pre">lib</span></code>. If
you want to use MKL blas, you should set <code [...]
+<li><p>If you have Intel Math Kernel Library (Intel MKL) installed, set <code
class="docutils literal notranslate"><span class="pre">MKLROOT</span></code>
environment variable to point to <code class="docutils literal
notranslate"><span class="pre">MKL</span></code> directory that contains the
<code class="docutils literal notranslate"><span
class="pre">include</span></code> and <code class="docutils literal
notranslate"><span class="pre">lib</span></code>. If you want to use MKL blas,
y [...]
<li><p>If you don’t have the Intel Math Kernel Library (MKL) installed,
download and install <a class="reference external"
href="http://sourceforge.net/projects/openblas/files/v0.2.14/";>OpenBLAS</a>, or
build the latest version of OpenBLAS from source. Note that you should also
download <code class="docutils literal notranslate"><span
class="pre">mingw64.dll.zip</span></code> along with openBLAS and add them to
PATH.</p></li>
<li><p>Set the environment variable <code class="docutils literal
notranslate"><span class="pre">OpenBLAS_HOME</span></code> to point to the
<code class="docutils literal notranslate"><span
class="pre">OpenBLAS</span></code> directory that contains the <code
class="docutils literal notranslate"><span class="pre">include</span></code>
and <code class="docutils literal notranslate"><span
class="pre">lib</span></code> directories. Typically, you can find the
directory in <code class="docuti [...]
</ol>
@@ -1315,7 +1315,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
<li><p>Enable Intel MKL-DNN and Intel MKL as BLAS library by the
command:</p></li>
</ol>
<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="s2">"C:\Program Files
(x86)\IntelSWTools\compilers_and_libraries\windows\mkl</span><span
class="se">\b</span><span class="s2">in\mklvars.bat"</span> <span
class="n">intel64</span>
-<span class="o">></span><span class="n">cmake</span> <span
class="o">-</span><span class="n">G</span> <span class="s2">"Visual Studio
14 Win64"</span> <span class="o">..</span> <span class="o">-</span><span
class="n">DUSE_CUDA</span><span class="o">=</span><span class="mi">0</span>
<span class="o">-</span><span class="n">DUSE_CUDNN</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_NVRTC</span><span class="o">=</span><span cl [...]
+<span class="o">></span><span class="n">cmake</span> <span
class="o">-</span><span class="n">G</span> <span class="s2">"Visual Studio
14 Win64"</span> <span class="o">..</span> <span class="o">-</span><span
class="n">DUSE_CUDA</span><span class="o">=</span><span class="mi">0</span>
<span class="o">-</span><span class="n">DUSE_CUDNN</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_NVRTC</span><span class="o">=</span><span cl [...]
</pre></div>
</div>
<ol class="arabic simple" start="4">
@@ -1330,7 +1330,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
</ol>
<p><strong>Visual Studio 2017</strong></p>
<p>User can follow the same steps of Visual Studio 2015 to build MXNET with
MKL-DNN, but change the version related command, for example,<code
class="docutils literal notranslate"><span
class="pre">C:\opencv\build\x64\vc15\bin</span></code> and build command is as
below:</p>
-<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="n">cmake</span> <span class="o">-</span><span class="n">G</span> <span
class="s2">"Visual Studio 15 Win64"</span> <span class="o">..</span>
<span class="o">-</span><span class="n">DUSE_CUDA</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_CUDNN</span><span class="o">=</span><span class="mi">0</span>
<span [...]
+<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="n">cmake</span> <span class="o">-</span><span class="n">G</span> <span
class="s2">"Visual Studio 15 Win64"</span> <span class="o">..</span>
<span class="o">-</span><span class="n">DUSE_CUDA</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_CUDNN</span><span class="o">=</span><span class="mi">0</span>
<span [...]
</pre></div>
</div>
<h2 id="4"><p>Verify MXNet with python</p>
diff --git
a/versions/master/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html.bak
b/versions/master/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html.bak
index 9377698..d41cd62 100644
---
a/versions/master/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html.bak
+++
b/versions/master/api/python/docs/tutorials/performance/backend/mkldnn/mkldnn_readme.html.bak
@@ -1291,7 +1291,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
<li><p>If <a class="reference external"
href="https://www.visualstudio.com/vs/older-downloads/";>Microsoft Visual Studio
2015</a> is not already installed, download and install it. You can download
and install the free community edition.</p></li>
<li><p>Download and Install <a class="reference external"
href="https://cmake.org/files/v3.14/cmake-3.14.0-win64-x64.msi";>CMake 3</a> if
it is not already installed.</p></li>
<li><p>Download <a class="reference external"
href="https://sourceforge.net/projects/opencvlibrary/files/3.4.5/opencv-3.4.5-vc14_vc15.exe/download";>OpenCV
3</a>, and unzip the OpenCV package, set the environment variable <code
class="docutils literal notranslate"><span class="pre">OpenCV_DIR</span></code>
to point to the <code class="docutils literal notranslate"><span
class="pre">OpenCV</span> <span class="pre">build</span> <span
class="pre">directory</span></code> (e.g.,``OpenCV_DIR = [...]
-<li><p>If you have Intel Math Kernel Library (Intel MKL) installed, set <code
class="docutils literal notranslate"><span class="pre">MKL_ROOT</span></code>
to point to <code class="docutils literal notranslate"><span
class="pre">MKL</span></code> directory that contains the <code class="docutils
literal notranslate"><span class="pre">include</span></code> and <code
class="docutils literal notranslate"><span class="pre">lib</span></code>. If
you want to use MKL blas, you should set <code [...]
+<li><p>If you have Intel Math Kernel Library (Intel MKL) installed, set <code
class="docutils literal notranslate"><span class="pre">MKLROOT</span></code>
environment variable to point to <code class="docutils literal
notranslate"><span class="pre">MKL</span></code> directory that contains the
<code class="docutils literal notranslate"><span
class="pre">include</span></code> and <code class="docutils literal
notranslate"><span class="pre">lib</span></code>. If you want to use MKL blas,
y [...]
<li><p>If you don’t have the Intel Math Kernel Library (MKL) installed,
download and install <a class="reference external"
href="http://sourceforge.net/projects/openblas/files/v0.2.14/";>OpenBLAS</a>, or
build the latest version of OpenBLAS from source. Note that you should also
download <code class="docutils literal notranslate"><span
class="pre">mingw64.dll.zip</span></code> along with openBLAS and add them to
PATH.</p></li>
<li><p>Set the environment variable <code class="docutils literal
notranslate"><span class="pre">OpenBLAS_HOME</span></code> to point to the
<code class="docutils literal notranslate"><span
class="pre">OpenBLAS</span></code> directory that contains the <code
class="docutils literal notranslate"><span class="pre">include</span></code>
and <code class="docutils literal notranslate"><span
class="pre">lib</span></code> directories. Typically, you can find the
directory in <code class="docuti [...]
</ol>
@@ -1315,7 +1315,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
<li><p>Enable Intel MKL-DNN and Intel MKL as BLAS library by the
command:</p></li>
</ol>
<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="s2">"C:\Program Files
(x86)\IntelSWTools\compilers_and_libraries\windows\mkl</span><span
class="se">\b</span><span class="s2">in\mklvars.bat"</span> <span
class="n">intel64</span>
-<span class="o">></span><span class="n">cmake</span> <span
class="o">-</span><span class="n">G</span> <span class="s2">"Visual Studio
14 Win64"</span> <span class="o">..</span> <span class="o">-</span><span
class="n">DUSE_CUDA</span><span class="o">=</span><span class="mi">0</span>
<span class="o">-</span><span class="n">DUSE_CUDNN</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_NVRTC</span><span class="o">=</span><span cl [...]
+<span class="o">></span><span class="n">cmake</span> <span
class="o">-</span><span class="n">G</span> <span class="s2">"Visual Studio
14 Win64"</span> <span class="o">..</span> <span class="o">-</span><span
class="n">DUSE_CUDA</span><span class="o">=</span><span class="mi">0</span>
<span class="o">-</span><span class="n">DUSE_CUDNN</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_NVRTC</span><span class="o">=</span><span cl [...]
</pre></div>
</div>
<ol class="arabic simple" start="4">
@@ -1330,7 +1330,7 @@ make -j $(nproc) USE_OPENCV=1 USE_MKLDNN=1
USE_BLAS=openblas
</ol>
<p><strong>Visual Studio 2017</strong></p>
<p>User can follow the same steps of Visual Studio 2015 to build MXNET with
MKL-DNN, but change the version related command, for example,<code
class="docutils literal notranslate"><span
class="pre">C:\opencv\build\x64\vc15\bin</span></code> and build command is as
below:</p>
-<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="n">cmake</span> <span class="o">-</span><span class="n">G</span> <span
class="s2">"Visual Studio 15 Win64"</span> <span class="o">..</span>
<span class="o">-</span><span class="n">DUSE_CUDA</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_CUDNN</span><span class="o">=</span><span class="mi">0</span>
<span [...]
+<div class="highlight-default notranslate"><div
class="highlight"><pre><span></span><span class="o">></span><span
class="n">cmake</span> <span class="o">-</span><span class="n">G</span> <span
class="s2">"Visual Studio 15 Win64"</span> <span class="o">..</span>
<span class="o">-</span><span class="n">DUSE_CUDA</span><span
class="o">=</span><span class="mi">0</span> <span class="o">-</span><span
class="n">DUSE_CUDNN</span><span class="o">=</span><span class="mi">0</span>
<span [...]
</pre></div>
</div>
<h2 id="4"><p>Verify MXNet with python</p>
diff --git a/versions/master/feed.xml b/versions/master/feed.xml
index 42fd0acf..472b204 100644
--- a/versions/master/feed.xml
+++ b/versions/master/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/versions/master/feed.xml"; rel="self"
type="application/atom+xml" /><link
href="https://mxnet.apache.org/versions/master/"; rel="alternate"
type="text/html"
/><updated>2020-10-07T18:39:56+00:00</updated><id>https://mxnet.apache.org/versions/master/feed.xml</id><title
type="html">Apache MXNet</title><su [...]
\ 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/versions/master/feed.xml"; rel="self"
type="application/atom+xml" /><link
href="https://mxnet.apache.org/versions/master/"; rel="alternate"
type="text/html"
/><updated>2020-10-08T00:33:13+00:00</updated><id>https://mxnet.apache.org/versions/master/feed.xml</id><title
type="html">Apache MXNet</title><su [...]
\ No newline at end of file
