Publish triggered by CI
diff --git a/.htaccess b/.htaccess
index b296604..4df2acf 100644
--- a/.htaccess
+++ b/.htaccess
@@ -22,12 +22,12 @@
 
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-# Set default website version to current stable (v1.7)
+# Set default website version to old stable (v1.7)
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 RewriteCond %{HTTP_REFERER} !mxnet.incubator.apache.org
 RewriteCond %{HTTP_REFERER} !mxnet.cdn.apache.org
-RewriteRule ^(.*)$ /versions/1.6/$1 [r=307,L]
+RewriteRule ^(.*)$ /versions/1.7/$1 [r=307,L]
 
 # Redirect Chinese visitors to Chinese CDN, temporary solution for slow site speed in China
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index 86aa2cf..10c110c 100644
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index 4f82602..9828d56 100644
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diff --git a/api/faq/add_op_in_backend.html b/api/faq/add_op_in_backend.html
index aa0fce2..8dd3c24 100644
--- a/api/faq/add_op_in_backend.html
+++ b/api/faq/add_op_in_backend.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/cloud.html b/api/faq/cloud.html
index 34dbe2a..d10a02f 100644
--- a/api/faq/cloud.html
+++ b/api/faq/cloud.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/distributed_training.html b/api/faq/distributed_training.html
index 6aadebf..61e3f32 100644
--- a/api/faq/distributed_training.html
+++ b/api/faq/distributed_training.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
+              
+            
+              
                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/env_var.html b/api/faq/env_var.html
index 6dd0054..97eeec7 100644
--- a/api/faq/env_var.html
+++ b/api/faq/env_var.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/float16.html b/api/faq/float16.html
index 08b6fe0..c13b9fb 100644
--- a/api/faq/float16.html
+++ b/api/faq/float16.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/gradient_compression.html b/api/faq/gradient_compression.html
index 7c6c883..a885cf2 100644
--- a/api/faq/gradient_compression.html
+++ b/api/faq/gradient_compression.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/large_tensor_support.html b/api/faq/large_tensor_support.html
index 976a486..8ca2802 100644
--- a/api/faq/large_tensor_support.html
+++ b/api/faq/large_tensor_support.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
+              
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/model_parallel_lstm.html b/api/faq/model_parallel_lstm.html
index e18051f..e04a14d 100644
--- a/api/faq/model_parallel_lstm.html
+++ b/api/faq/model_parallel_lstm.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
+              
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/new_op.html b/api/faq/new_op.html
index 9d92739..f6e7207 100644
--- a/api/faq/new_op.html
+++ b/api/faq/new_op.html
@@ -89,6 +89,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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+              
+                
                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
+              
+            
+              
                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/perf.html b/api/faq/perf.html
index 6bf97d0..9a21340 100644
--- a/api/faq/perf.html
+++ b/api/faq/perf.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
+              
+            
+              
                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/recordio.html b/api/faq/recordio.html
index e737663..99351a3 100644
--- a/api/faq/recordio.html
+++ b/api/faq/recordio.html
@@ -89,6 +89,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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+                
                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
+              
+            
+              
                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/s3_integration.html b/api/faq/s3_integration.html
index 57a05bc..6925464 100644
--- a/api/faq/s3_integration.html
+++ b/api/faq/s3_integration.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
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                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/security.html b/api/faq/security.html
index 4ad90f6..8bfc14d 100644
--- a/api/faq/security.html
+++ b/api/faq/security.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
+              
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+              
                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/tensor_inspector_tutorial.html b/api/faq/tensor_inspector_tutorial.html
index 883391a..cb09bc3 100644
--- a/api/faq/tensor_inspector_tutorial.html
+++ b/api/faq/tensor_inspector_tutorial.html
@@ -89,6 +89,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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+                
                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
+              
+            
+              
                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/using_rtc.html b/api/faq/using_rtc.html
index e667a65..91bc3ab 100644
--- a/api/faq/using_rtc.html
+++ b/api/faq/using_rtc.html
@@ -89,6 +89,10 @@
                 
               
                 
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                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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+              
                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/faq/why_mxnet.html b/api/faq/why_mxnet.html
index b941f2c..c185ab6 100644
--- a/api/faq/why_mxnet.html
+++ b/api/faq/why_mxnet.html
@@ -89,6 +89,10 @@
                 
               
                 
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                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
+                
+              
+                
                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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+            
+              
                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/index.html b/api/index.html
index ec38836..8e084d2 100644
--- a/api/index.html
+++ b/api/index.html
@@ -89,6 +89,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
+              
+            
+              
                 <a href="/versions/1.6/">1.6</a>
               
             
@@ -302,7 +314,7 @@
 <div class="row">
   <div class="language-binding-banner">
     <h4>Call for Contribution</h4>
-    The Clojure, Java, Julia, R, and Scala language bindings of <a href="/versions/1.6/api">MXNet v1.x</a> were removed in v2.x due to some <a href="https://github.com/apache/incubator-mxnet/issues/17676">C APIs being deprecated</a> and the bindings rely on the deprecated APIs. You can still use these language bindings in v1.x.
+    The Clojure, Java, Julia, R, and Scala language bindings of <a href="/versions/1.7/api">MXNet v1.x</a> were removed in v2.x due to some <a href="https://github.com/apache/incubator-mxnet/issues/17676">C APIs being deprecated</a> and the bindings rely on the deprecated APIs. You can still use these language bindings in v1.x.
     MXNet's new C APIs in v2.x can be used to reestablish your preferred language binding. Your contribution is welcome!
   </div>
 </div>
diff --git a/api/java.html b/api/java.html
index 42555a7..099f605 100644
--- a/api/java.html
+++ b/api/java.html
@@ -89,6 +89,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
+              
+            
+              
                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/java/docs/tutorials.html b/api/java/docs/tutorials.html
index 87e1026..14969f6 100644
--- a/api/java/docs/tutorials.html
+++ b/api/java/docs/tutorials.html
@@ -89,6 +89,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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+              
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                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
+              
+            
+              
                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/java/docs/tutorials/ssd_inference.html b/api/java/docs/tutorials/ssd_inference.html
index 6df7e1c..ee406c5 100644
--- a/api/java/docs/tutorials/ssd_inference.html
+++ b/api/java/docs/tutorials/ssd_inference.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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+              
                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/julia.html b/api/julia.html
index eaf0067..4f22764 100644
--- a/api/julia.html
+++ b/api/julia.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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                   <li class="gs-opt gs-versions">1.6</li>
                 
               
@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/perl.html b/api/perl.html
index 7eeffcf..008e16d 100644
--- a/api/perl.html
+++ b/api/perl.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/perl/docs/tutorials.html b/api/perl/docs/tutorials.html
index 4d8efe8..f78b4f7 100644
--- a/api/perl/docs/tutorials.html
+++ b/api/perl/docs/tutorials.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/perl/docs/tutorials/io.html b/api/perl/docs/tutorials/io.html
index 094df39..dd6fe92 100644
--- a/api/perl/docs/tutorials/io.html
+++ b/api/perl/docs/tutorials/io.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/perl/docs/tutorials/kvstore.html b/api/perl/docs/tutorials/kvstore.html
index e5c875e..e8be65e 100644
--- a/api/perl/docs/tutorials/kvstore.html
+++ b/api/perl/docs/tutorials/kvstore.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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                 <a href="/versions/1.6/">1.6</a>
               
             
diff --git a/api/perl/docs/tutorials/ndarray.html b/api/perl/docs/tutorials/ndarray.html
index 6a34179..1aaca14 100644
--- a/api/perl/docs/tutorials/ndarray.html
+++ b/api/perl/docs/tutorials/ndarray.html
@@ -89,6 +89,10 @@
                 
               
                 
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@@ -146,6 +150,10 @@
                 
               
                 
+                  <li class="gs-opt gs-versions">1.7</li>
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@@ -201,6 +209,10 @@
               
             
               
+                <a href="/versions/1.7/">1.7</a>
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diff --git a/api/python/docs/_modules/mxnet/callback.html b/api/python/docs/_modules/mxnet/callback.html
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+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
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     <div class="mdl-layout__header-row header-links">
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/index.html">Python Tutorials</a><ul>
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-<li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/index.html">Getting started with NP on MXNet</a><ul>
-<li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/1-ndarray.html">Step 1: Manipulate data with NP on MXNet</a></li>
-<li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/2-nn.html">Step 2: Create a neural network</a></li>
-<li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/3-autograd.html">Step 3: Automatic differentiation with autograd</a></li>
-<li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/4-train.html">Step 4: Train the neural network</a></li>
-<li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/5-predict.html">Step 5: Predict with a pretrained model</a></li>
-<li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/6-use_gpus.html">Step 6: Use GPUs to increase efficiency</a></li>
-</ul>
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-<li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/to-mxnet/index.html">Moving to MXNet from Other Frameworks</a><ul>
-<li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/to-mxnet/pytorch.html">PyTorch vs Apache MXNet</a></li>
-</ul>
-</li>
-<li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/gluon_from_experiment_to_deployment.html">Gluon: from experiment to deployment</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/logistic_regression_explained.html">Logistic regression explained</a></li>
-<li class="toctree-l3"><a class="reference external" href="https://mxnet.apache.org/api/python/docs/tutorials/packages/gluon/image/mnist.html">MNIST</a></li>
-</ul>
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-<li class="toctree-l2"><a class="reference internal" href="../../../tutorials/packages/index.html">Packages</a><ul>
-<li class="toctree-l3"><a class="reference internal" href="../../../tutorials/packages/autograd/index.html">Automatic Differentiation</a></li>
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-<li class="toctree-l4"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/index.html">Blocks</a><ul>
-<li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/custom-layer.html">Custom Layers</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/custom_layer_beginners.html">Customer Layers (Beginners)</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/hybridize.html">Hybridize</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/init.html">Initialization</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/naming.html">Parameter and Block Naming</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/gluon/blocks/nn.html">Layers and Blocks</a></li>
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-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.empty.html">mxnet.np.empty</a></li>
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-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.dstack.html">mxnet.np.dstack</a></li>
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-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.split.html">mxnet.np.split</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.hsplit.html">mxnet.np.hsplit</a></li>
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-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.unique.html">mxnet.np.unique</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.reshape.html">mxnet.np.reshape</a></li>
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-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.rot90.html">mxnet.np.rot90</a></li>
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-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.io.html">Input and output</a><ul>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.genfromtxt.html">mxnet.np.genfromtxt</a></li>
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-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.linalg.html">Linear algebra (<code class="xref py py-mod docutils literal notranslate"><span class="pre">numpy.linalg</span></code>)</a><ul>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.dot.html">mxnet.np.dot</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.vdot.html">mxnet.np.vdot</a></li>
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-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.sqrt.html">mxnet.np.sqrt</a></li>
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-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/random/index.html">np.random</a></li>
-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.sort.html">Sorting, searching, and counting</a><ul>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.argmax.html">mxnet.np.argmax</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.argmin.html">mxnet.np.argmin</a></li>
-</ul>
-</li>
-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.statistics.html">Statistics</a><ul>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.min.html">mxnet.np.min</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.max.html">mxnet.np.max</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.mean.html">mxnet.np.mean</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.std.html">mxnet.np.std</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.var.html">mxnet.np.var</a></li>
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-</ul>
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-</ul>
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-<li class="toctree-l2"><a class="reference internal" href="../../../api/npx/index.html">NPX: NumPy Neural Network Extension</a><ul>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.set_np.html">mxnet.npx.set_np</a></li>
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-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.cpu_pinned.html">mxnet.npx.cpu_pinned</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.gpu.html">mxnet.npx.gpu</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.gpu_memory_info.html">mxnet.npx.gpu_memory_info</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.current_context.html">mxnet.npx.current_context</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.num_gpus.html">mxnet.npx.num_gpus</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.activation.html">mxnet.npx.activation</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.batch_norm.html">mxnet.npx.batch_norm</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.convolution.html">mxnet.npx.convolution</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.dropout.html">mxnet.npx.dropout</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.embedding.html">mxnet.npx.embedding</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.fully_connected.html">mxnet.npx.fully_connected</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.layer_norm.html">mxnet.npx.layer_norm</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.pooling.html">mxnet.npx.pooling</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.rnn.html">mxnet.npx.rnn</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.leaky_relu.html">mxnet.npx.leaky_relu</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.multibox_detection.html">mxnet.npx.multibox_detection</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.multibox_prior.html">mxnet.npx.multibox_prior</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.multibox_target.html">mxnet.npx.multibox_target</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.roi_pooling.html">mxnet.npx.roi_pooling</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.sigmoid.html">mxnet.npx.sigmoid</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.smooth_l1.html">mxnet.npx.smooth_l1</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.softmax.html">mxnet.npx.softmax</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.topk.html">mxnet.npx.topk</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.waitall.html">mxnet.npx.waitall</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.load.html">mxnet.npx.load</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.save.html">mxnet.npx.save</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.one_hot.html">mxnet.npx.one_hot</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.pick.html">mxnet.npx.pick</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.reshape_like.html">mxnet.npx.reshape_like</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.batch_flatten.html">mxnet.npx.batch_flatten</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.batch_dot.html">mxnet.npx.batch_dot</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.gamma.html">mxnet.npx.gamma</a></li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/npx/generated/mxnet.npx.sequence_mask.html">mxnet.npx.sequence_mask</a></li>
-</ul>
-</li>
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-<li class="toctree-l3"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/index.html">Getting started with NP on MXNet</a><ul>
-<li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/1-ndarray.html">Step 1: Manipulate data with NP on MXNet</a></li>
-<li class="toctree-l4"><a class="reference internal" href="../../../tutorials/getting-started/crash-course/2-nn.html">Step 2: Create a neural network</a></li>
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-<li class="toctree-l5"><a class="reference internal" href="../../../tutorials/packages/legacy/ndarray/01-ndarray-intro.html">An Intro: Manipulate Data the MXNet Way with NDArray</a></li>
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-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/arrays.ndarray.html">The N-dimensional array (<code class="xref py py-class docutils literal notranslate"><span class="pre">ndarray</span></code>)</a><ul>
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-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.argmax.html">mxnet.np.ndarray.argmax</a></li>
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-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.mean.html">mxnet.np.ndarray.mean</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.prod.html">mxnet.np.ndarray.prod</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.cumsum.html">mxnet.np.ndarray.cumsum</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.var.html">mxnet.np.ndarray.var</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.std.html">mxnet.np.ndarray.std</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__lt__.html">mxnet.np.ndarray.__lt__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__le__.html">mxnet.np.ndarray.__le__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__gt__.html">mxnet.np.ndarray.__gt__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__ge__.html">mxnet.np.ndarray.__ge__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__eq__.html">mxnet.np.ndarray.__eq__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__ne__.html">mxnet.np.ndarray.__ne__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__bool__.html">mxnet.np.ndarray.__bool__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__neg__.html">mxnet.np.ndarray.__neg__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__add__.html">mxnet.np.ndarray.__add__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__sub__.html">mxnet.np.ndarray.__sub__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__mul__.html">mxnet.np.ndarray.__mul__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__truediv__.html">mxnet.np.ndarray.__truediv__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__mod__.html">mxnet.np.ndarray.__mod__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__pow__.html">mxnet.np.ndarray.__pow__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__iadd__.html">mxnet.np.ndarray.__iadd__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__isub__.html">mxnet.np.ndarray.__isub__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__imul__.html">mxnet.np.ndarray.__imul__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__itruediv__.html">mxnet.np.ndarray.__itruediv__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__imod__.html">mxnet.np.ndarray.__imod__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__reduce__.html">mxnet.np.ndarray.__reduce__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__setstate__.html">mxnet.np.ndarray.__setstate__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__len__.html">mxnet.np.ndarray.__len__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__getitem__.html">mxnet.np.ndarray.__getitem__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__setitem__.html">mxnet.np.ndarray.__setitem__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__int__.html">mxnet.np.ndarray.__int__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__float__.html">mxnet.np.ndarray.__float__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__str__.html">mxnet.np.ndarray.__str__</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.__repr__.html">mxnet.np.ndarray.__repr__</a></li>
-</ul>
-</li>
-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/arrays.indexing.html">Indexing</a></li>
-</ul>
-</li>
-<li class="toctree-l3"><a class="reference internal" href="../../../api/np/routines.html">Routines</a><ul>
-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.array-creation.html">Array creation routines</a><ul>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.eye.html">mxnet.np.eye</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.empty.html">mxnet.np.empty</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.full.html">mxnet.np.full</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.identity.html">mxnet.np.identity</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ones.html">mxnet.np.ones</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ones_like.html">mxnet.np.ones_like</a></li>
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-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.zeros_like.html">mxnet.np.zeros_like</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.array.html">mxnet.np.array</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.copy.html">mxnet.np.copy</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arange.html">mxnet.np.arange</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linspace.html">mxnet.np.linspace</a></li>
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-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.meshgrid.html">mxnet.np.meshgrid</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tril.html">mxnet.np.tril</a></li>
-</ul>
-</li>
-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.array-manipulation.html">Array manipulation routines</a><ul>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.reshape.html">mxnet.np.reshape</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ravel.html">mxnet.np.ravel</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.flatten.html">mxnet.np.ndarray.flatten</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.swapaxes.html">mxnet.np.swapaxes</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.ndarray.T.html">mxnet.np.ndarray.T</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.transpose.html">mxnet.np.transpose</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.moveaxis.html">mxnet.np.moveaxis</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.expand_dims.html">mxnet.np.expand_dims</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.squeeze.html">mxnet.np.squeeze</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.broadcast_to.html">mxnet.np.broadcast_to</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.broadcast_arrays.html">mxnet.np.broadcast_arrays</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.concatenate.html">mxnet.np.concatenate</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.stack.html">mxnet.np.stack</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.dstack.html">mxnet.np.dstack</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.vstack.html">mxnet.np.vstack</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.split.html">mxnet.np.split</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.hsplit.html">mxnet.np.hsplit</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.vsplit.html">mxnet.np.vsplit</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tile.html">mxnet.np.tile</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.repeat.html">mxnet.np.repeat</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.unique.html">mxnet.np.unique</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.reshape.html">mxnet.np.reshape</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.flip.html">mxnet.np.flip</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.roll.html">mxnet.np.roll</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.rot90.html">mxnet.np.rot90</a></li>
-</ul>
-</li>
-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.io.html">Input and output</a><ul>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.genfromtxt.html">mxnet.np.genfromtxt</a></li>
-</ul>
-</li>
-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.linalg.html">Linear algebra (<code class="xref py py-mod docutils literal notranslate"><span class="pre">numpy.linalg</span></code>)</a><ul>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.dot.html">mxnet.np.dot</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.vdot.html">mxnet.np.vdot</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.inner.html">mxnet.np.inner</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.outer.html">mxnet.np.outer</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tensordot.html">mxnet.np.tensordot</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.einsum.html">mxnet.np.einsum</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.svd.html">mxnet.np.linalg.svd</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.linalg.norm.html">mxnet.np.linalg.norm</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.trace.html">mxnet.np.trace</a></li>
-</ul>
-</li>
-<li class="toctree-l4"><a class="reference internal" href="../../../api/np/routines.math.html">Mathematical functions</a><ul>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.sin.html">mxnet.np.sin</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.cos.html">mxnet.np.cos</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tan.html">mxnet.np.tan</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arcsin.html">mxnet.np.arcsin</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arccos.html">mxnet.np.arccos</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arctan.html">mxnet.np.arctan</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.degrees.html">mxnet.np.degrees</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.radians.html">mxnet.np.radians</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.hypot.html">mxnet.np.hypot</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.arctan2.html">mxnet.np.arctan2</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.deg2rad.html">mxnet.np.deg2rad</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.rad2deg.html">mxnet.np.rad2deg</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.sinh.html">mxnet.np.sinh</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.cosh.html">mxnet.np.cosh</a></li>
-<li class="toctree-l5"><a class="reference internal" href="../../../api/np/generated/mxnet.np.tanh.html">mxnet.np.tanh</a></li>
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-  <h1>Source code for mxnet.contrib.autograd</h1><div class="highlight"><pre>
-<span></span><span class="c1"># Licensed to the Apache Software Foundation (ASF) under one</span>
-<span class="c1"># or more contributor license agreements.  See the NOTICE file</span>
-<span class="c1"># distributed with this work for additional information</span>
-<span class="c1"># regarding copyright ownership.  The ASF licenses this file</span>
-<span class="c1"># to you under the Apache License, Version 2.0 (the</span>
-<span class="c1"># &quot;License&quot;); you may not use this file except in compliance</span>
-<span class="c1"># with the License.  You may obtain a copy of the License at</span>
-<span class="c1">#</span>
-<span class="c1">#   http://www.apache.org/licenses/LICENSE-2.0</span>
-<span class="c1">#</span>
-<span class="c1"># Unless required by applicable law or agreed to in writing,</span>
-<span class="c1"># software distributed under the License is distributed on an</span>
-<span class="c1"># &quot;AS IS&quot; BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span>
-<span class="c1"># KIND, either express or implied.  See the License for the</span>
-<span class="c1"># specific language governing permissions and limitations</span>
-<span class="c1"># under the License.</span>
-
-<span class="c1"># coding: utf-8</span>
-<span class="sd">&quot;&quot;&quot;Autograd for NDArray.&quot;&quot;&quot;</span>
-
-<span class="kn">from</span> <span class="nn">array</span> <span class="kn">import</span> <span class="n">array</span>
-<span class="kn">import</span> <span class="nn">ctypes</span>
-<span class="kn">import</span> <span class="nn">functools</span>
-<span class="kn">from</span> <span class="nn">..base</span> <span class="kn">import</span> <span class="n">_LIB</span><span class="p">,</span> <span class="n">check_call</span><span class="p">,</span> <span class="n">string_types</span>
-<span class="kn">from</span> <span class="nn">..base</span> <span class="kn">import</span> <span class="n">mx_uint</span><span class="p">,</span> <span class="n">NDArrayHandle</span><span class="p">,</span> <span class="n">c_array</span><span class="p">,</span> <span class="n">c_array_buf</span><span class="p">,</span> <span class="n">c_handle_array</span>
-<span class="c1"># pylint: disable= unused-import</span>
-<span class="kn">from</span> <span class="nn">..ndarray</span> <span class="kn">import</span> <span class="n">NDArray</span><span class="p">,</span> <span class="n">zeros_like</span><span class="p">,</span> <span class="n">_GRAD_REQ_MAP</span>
-
-
-<div class="viewcode-block" id="set_is_training"><a class="viewcode-back" href="../../../api/contrib/autograd/index.html#mxnet.contrib.autograd.set_is_training">[docs]</a><span class="k">def</span> <span class="nf">set_is_training</span><span class="p">(</span><span class="n">is_train</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Set status to training/not training. When training, graph will be constructed</span>
-<span class="sd">    for gradient computation. Operators will also run with ctx.is_train=True. For example,</span>
-<span class="sd">    Dropout will drop inputs randomly when is_train=True while simply passing through</span>
-<span class="sd">    if is_train=False.</span>
-
-<span class="sd">    Parameters</span>
-<span class="sd">    ----------</span>
-<span class="sd">    is_train: bool</span>
-
-<span class="sd">    Returns</span>
-<span class="sd">    -------</span>
-<span class="sd">    previous state before this set.</span>
-<span class="sd">    &quot;&quot;&quot;</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">MXAutogradSetIsTraining</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">is_train</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="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXAutogradSetIsRecording</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">is_train</span><span class="p">),</span> <span class="n">ctypes</span><span class="o">.</span><span class="n">byref</span><span class="p">(</span><span class="n">prev</span><span class="p">)))</span>
-    <span class="k">return</span> <span class="nb">bool</span><span class="p">(</span><span class="n">prev</span><span class="o">.</span><span class="n">value</span><span class="p">)</span></div>
-
-
-<div class="viewcode-block" id="TrainingStateScope"><a class="viewcode-back" href="../../../api/contrib/autograd/index.html#mxnet.contrib.autograd.TrainingStateScope">[docs]</a><span class="k">class</span> <span class="nc">TrainingStateScope</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Scope for managing training state.</span>
-
-<span class="sd">    Example::</span>
-<span class="sd">        with TrainingStateScope(True):</span>
-<span class="sd">            y = model(x)</span>
-<span class="sd">            compute_gradient([y])</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">enter_state</span><span class="p">):</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_enter_state</span> <span class="o">=</span> <span class="n">enter_state</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_prev</span> <span class="o">=</span> <span class="kc">None</span>
-
-    <span class="k">def</span> <span class="fm">__enter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_prev</span> <span class="o">=</span> <span class="n">set_is_training</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_enter_state</span><span class="p">)</span>
-
-    <span class="k">def</span> <span class="fm">__exit__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ptype</span><span class="p">,</span> <span class="n">value</span><span class="p">,</span> <span class="n">trace</span><span class="p">):</span>
-        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prev</span> <span class="o">!=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_enter_state</span><span class="p">:</span>
-            <span class="n">set_is_training</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_prev</span><span class="p">)</span></div>
-
-
-<div class="viewcode-block" id="train_section"><a class="viewcode-back" href="../../../api/contrib/autograd/index.html#mxnet.contrib.autograd.train_section">[docs]</a><span class="k">def</span> <span class="nf">train_section</span><span class="p">():</span>
-    <span class="sd">&quot;&quot;&quot;Returns a training scope context to be used in &#39;with&#39; statement</span>
-<span class="sd">    and captures training code.</span>
-
-<span class="sd">    Example::</span>
-<span class="sd">        with autograd.train_section():</span>
-<span class="sd">            y = model(x)</span>
-<span class="sd">            compute_gradient([y])</span>
-<span class="sd">        metric.update(...)</span>
-<span class="sd">        optim.step(...)</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">return</span> <span class="n">TrainingStateScope</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span></div>
-
-
-<div class="viewcode-block" id="test_section"><a class="viewcode-back" href="../../../api/contrib/autograd/index.html#mxnet.contrib.autograd.test_section">[docs]</a><span class="k">def</span> <span class="nf">test_section</span><span class="p">():</span>
-    <span class="sd">&quot;&quot;&quot;Returns a testing scope context to be used in &#39;with&#39; statement</span>
-<span class="sd">    and captures testing code.</span>
-
-<span class="sd">    Example::</span>
-<span class="sd">        with autograd.train_section():</span>
-<span class="sd">            y = model(x)</span>
-<span class="sd">            compute_gradient([y])</span>
-<span class="sd">            with autograd.test_section():</span>
-<span class="sd">                # testing, IO, gradient updates...</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">return</span> <span class="n">TrainingStateScope</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span></div>
-
-
-<div class="viewcode-block" id="mark_variables"><a class="viewcode-back" href="../../../api/contrib/autograd/index.html#mxnet.contrib.autograd.mark_variables">[docs]</a><span class="k">def</span> <span class="nf">mark_variables</span><span class="p">(</span><span class="n">variables</span><span class="p">,</span> <span class="n">gradients</span><span class="p">,</span> <span class="n">grad_reqs</span><span class="o">=</span><span class="s1">&#39;write&#39;</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Mark NDArrays as variables to compute gradient for autograd.</span>
-
-<span class="sd">    Parameters</span>
-<span class="sd">    ----------</span>
-<span class="sd">    variables: list of NDArray</span>
-<span class="sd">    gradients: list of NDArray</span>
-<span class="sd">    grad_reqs: list of string</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">grad_reqs</span><span class="p">,</span> <span class="n">string_types</span><span class="p">):</span>
-        <span class="n">grad_reqs</span> <span class="o">=</span> <span class="p">[</span><span class="n">_GRAD_REQ_MAP</span><span class="p">[</span><span class="n">grad_reqs</span><span class="p">]]</span><span class="o">*</span><span class="nb">len</span><span class="p">(</span><span class="n">variables</span><span class="p">)</span>
-    <span class="k">else</span><span class="p">:</span>
-        <span class="n">grad_reqs</span> <span class="o">=</span> <span class="p">[</span><span class="n">_GRAD_REQ_MAP</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">grad_reqs</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">MXAutogradMarkVariables</span><span class="p">(</span>
-        <span class="nb">len</span><span class="p">(</span><span class="n">variables</span><span class="p">),</span>
-        <span class="n">c_handle_array</span><span class="p">(</span><span class="n">variables</span><span class="p">),</span>
-        <span class="n">c_array_buf</span><span class="p">(</span><span class="n">mx_uint</span><span class="p">,</span> <span class="n">array</span><span class="p">(</span><span class="s1">&#39;I&#39;</span><span class="p">,</span> <span class="n">grad_reqs</span><span class="p">)),</span>
-        <span class="n">c_handle_array</span><span class="p">(</span><span class="n">gradients</span><span class="p">)))</span></div>
-
-
-<div class="viewcode-block" id="backward"><a class="viewcode-back" href="../../../api/contrib/autograd/index.html#mxnet.contrib.autograd.backward">[docs]</a><span class="k">def</span> <span class="nf">backward</span><span class="p">(</span><span class="n">outputs</span><span class="p">,</span> <span class="n">out_grads</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">retain_graph</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Compute the gradients of outputs w.r.t variables.</span>
-
-<span class="sd">    Parameters</span>
-<span class="sd">    ----------</span>
-<span class="sd">    outputs: list of NDArray</span>
-<span class="sd">    out_grads: list of NDArray or None</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">outputs</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">)),</span> \
-        <span class="s2">&quot;outputs must be a list or tuple of NDArrays&quot;</span>
-
-    <span class="k">if</span> <span class="n">out_grads</span> <span class="ow">is</span> <span class="kc">None</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">MXAutogradBackward</span><span class="p">(</span>
-            <span class="nb">len</span><span class="p">(</span><span class="n">outputs</span><span class="p">),</span>
-            <span class="n">c_handle_array</span><span class="p">(</span><span class="n">outputs</span><span class="p">),</span>
-            <span class="n">ctypes</span><span class="o">.</span><span class="n">c_void_p</span><span class="p">(</span><span class="mi">0</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">retain_graph</span><span class="p">)))</span>
-        <span class="k">return</span>
-
-    <span class="n">ograd_handles</span> <span class="o">=</span> <span class="p">[]</span>
-    <span class="k">for</span> <span class="n">arr</span> <span class="ow">in</span> <span class="n">out_grads</span><span class="p">:</span>
-        <span class="k">if</span> <span class="n">arr</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">ograd_handles</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">arr</span><span class="o">.</span><span class="n">handle</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="n">ograd_handles</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">NDArrayHandle</span><span class="p">(</span><span class="mi">0</span><span class="p">))</span>
-    <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">ograd_handles</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">outputs</span><span class="p">),</span> \
-        <span class="s2">&quot;outputs and out_grads must have the same length&quot;</span>
-
-    <span class="n">check_call</span><span class="p">(</span><span class="n">_LIB</span><span class="o">.</span><span class="n">MXAutogradBackward</span><span class="p">(</span>
-        <span class="nb">len</span><span class="p">(</span><span class="n">outputs</span><span class="p">),</span>
-        <span class="n">c_handle_array</span><span class="p">(</span><span class="n">outputs</span><span class="p">),</span>
-        <span class="n">c_array</span><span class="p">(</span><span class="n">NDArrayHandle</span><span class="p">,</span> <span class="n">ograd_handles</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">retain_graph</span><span class="p">)))</span></div>
-
-
-<div class="viewcode-block" id="compute_gradient"><a class="viewcode-back" href="../../../api/contrib/autograd/index.html#mxnet.contrib.autograd.compute_gradient">[docs]</a><span class="k">def</span> <span class="nf">compute_gradient</span><span class="p">(</span><span class="n">outputs</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Deprecated. Please use backward&quot;&quot;&quot;</span>
-    <span class="n">backward</span><span class="p">(</span><span class="n">outputs</span><span class="p">)</span></div>
-
-
-<div class="viewcode-block" id="grad_and_loss"><a class="viewcode-back" href="../../../api/contrib/autograd/index.html#mxnet.contrib.autograd.grad_and_loss">[docs]</a><span class="k">def</span> <span class="nf">grad_and_loss</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">argnum</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Return function that computes both gradient of arguments and loss value.</span>
-
-<span class="sd">    Parameters</span>
-<span class="sd">    ----------</span>
-<span class="sd">    func: a python function</span>
-<span class="sd">        The forward (loss) function.</span>
-<span class="sd">    argnum: an int or a list of int</span>
-<span class="sd">        The index of argument to calculate gradient for.</span>
-
-<span class="sd">    Returns</span>
-<span class="sd">    -------</span>
-<span class="sd">    grad_and_loss_func: a python function</span>
-<span class="sd">        A function that would compute both the gradient of arguments and loss value.</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="nd">@functools</span><span class="o">.</span><span class="n">wraps</span><span class="p">(</span><span class="n">func</span><span class="p">)</span>
-    <span class="k">def</span> <span class="nf">wrapped</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">):</span>
-        <span class="sd">&quot;&quot;&quot;Wrapped function.&quot;&quot;&quot;</span>
-        <span class="n">variables</span> <span class="o">=</span> <span class="n">args</span>
-        <span class="k">if</span> <span class="n">argnum</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">argnum_</span> <span class="o">=</span> <span class="n">argnum</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">argnum</span><span class="p">,</span> <span class="nb">list</span><span class="p">)</span> <span class="k">else</span> <span class="p">[</span><span class="n">argnum</span><span class="p">]</span>
-            <span class="n">variables</span> <span class="o">=</span> <span class="p">[</span><span class="n">args</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">argnum_</span><span class="p">]</span>
-        <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">variables</span><span class="p">:</span>
-            <span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">NDArray</span><span class="p">),</span> <span class="s2">&quot;type of autograd input should NDArray.&quot;</span>
-        <span class="n">grads</span> <span class="o">=</span> <span class="p">[</span><span class="n">zeros_like</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">variables</span><span class="p">]</span>
-        <span class="n">mark_variables</span><span class="p">(</span><span class="n">variables</span><span class="p">,</span> <span class="n">grads</span><span class="p">)</span>
-        <span class="k">with</span> <span class="n">train_section</span><span class="p">():</span>
-            <span class="n">outputs</span> <span class="o">=</span> <span class="n">func</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">)</span>
-        <span class="n">compute_gradient</span><span class="p">([</span><span class="n">outputs</span><span class="p">]</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">outputs</span><span class="p">,</span> <span class="n">NDArray</span><span class="p">)</span> <span class="k">else</span> <span class="n">outputs</span><span class="p">)</span>
-        <span class="k">return</span> <span class="n">grads</span><span class="p">,</span> <span class="n">outputs</span>
-    <span class="k">return</span> <span class="n">wrapped</span></div>
-
-<div class="viewcode-block" id="grad"><a class="viewcode-back" href="../../../api/contrib/autograd/index.html#mxnet.contrib.autograd.grad">[docs]</a><span class="k">def</span> <span class="nf">grad</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">argnum</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Return function that computes gradient of arguments.</span>
-
-<span class="sd">    Parameters</span>
-<span class="sd">    ----------</span>
-<span class="sd">    func: a python function</span>
-<span class="sd">        The forward (loss) function.</span>
-<span class="sd">    argnum: an int or a list of int</span>
-<span class="sd">        The index of argument to calculate gradient for.</span>
-
-<span class="sd">    Returns</span>
-<span class="sd">    -------</span>
-<span class="sd">    grad_func: a python function</span>
-<span class="sd">        A function that would compute the gradient of arguments.</span>
-
-<span class="sd">    Examples</span>
-<span class="sd">    --------</span>
-<span class="sd">    &gt;&gt;&gt; # autograd supports dynamic graph which is changed</span>
-<span class="sd">    &gt;&gt;&gt; # every instance</span>
-<span class="sd">    &gt;&gt;&gt; def func(x):</span>
-<span class="sd">    &gt;&gt;&gt;     r = random.randint(0, 1)</span>
-<span class="sd">    &gt;&gt;&gt;     if r % 2:</span>
-<span class="sd">    &gt;&gt;&gt;         return x**2</span>
-<span class="sd">    &gt;&gt;&gt;     else:</span>
-<span class="sd">    &gt;&gt;&gt;         return x/3</span>
-<span class="sd">    &gt;&gt;&gt; # use `grad(func)` to get the gradient function</span>
-<span class="sd">    &gt;&gt;&gt; for x in range(10):</span>
-<span class="sd">    &gt;&gt;&gt;     grad_func = grad(func)</span>
-<span class="sd">    &gt;&gt;&gt;     inputs = nd.array([[1, 2, 3], [4, 5, 6]])</span>
-<span class="sd">    &gt;&gt;&gt;     grad_vals = grad_func(inputs)</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">grad_with_loss_func</span> <span class="o">=</span> <span class="n">grad_and_loss</span><span class="p">(</span><span class="n">func</span><span class="p">,</span> <span class="n">argnum</span><span class="p">)</span>
-    <span class="nd">@functools</span><span class="o">.</span><span class="n">wraps</span><span class="p">(</span><span class="n">grad_with_loss_func</span><span class="p">)</span>
-    <span class="k">def</span> <span class="nf">wrapped</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">):</span>
-        <span class="k">return</span> <span class="n">grad_with_loss_func</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
-    <span class="k">return</span> <span class="n">wrapped</span></div>
-</pre></div>
-
-        <hr class="feedback-hr-top" />
-<div class="feedback-container">
-    <div class="feedback-question">Did this page help you?</div>
-    <div class="feedback-answer-container">
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-            <div class="side-doc-outline--content"> 
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-      <div class="clearer"></div>
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-            <footer class="site-footer h-card">
-    <div class="wrapper">
-        <div class="row">
-            <div class="col-4">
-                <h4 class="footer-category-title">Resources</h4>
-                <ul class="contact-list">
-                    <li><a
-                            href="https://lists.apache.org/list.html?dev@mxnet.apache.org">Mailing list</a> <a class="u-email" href="mailto:dev-subscribe@mxnet.apache.org">(subscribe)</a></li>
-                    <li><a href="https://discuss.mxnet.io">MXNet Discuss forum</a></li>
-                    <li><a href="https://github.com/apache/incubator-mxnet/issues">Github Issues</a></li>
-                    <li><a href="https://github.com/apache/incubator-mxnet/projects">Projects</a></li>
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-                    <li><a href="/community">Contribute To MXNet</a></li>
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-</div>
-
-            <div class="col-4 footer-text">
-                <p>A flexible and efficient library for deep learning.</p>
-            </div>
-        </div>
-    </div>
-</footer>
-
-<footer class="site-footer2">
-    <div class="wrapper">
-        <div class="row">
-            <div class="col-3">
-                <img src="../../../_static/apache_incubator_logo.png" class="footer-logo col-2">
-            </div>
-            <div class="footer-bottom-warning col-9">
-                <p>Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), <span style="font-weight:bold">sponsored by the <i>Apache Incubator</i></span>. Incubation is required
-                    of all newly accepted projects until a further review indicates that the infrastructure,
-                    communications, and decision making process have stabilized in a manner consistent with other
-                    successful ASF projects. While incubation status is not necessarily a reflection of the completeness
-                    or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
-                </p><p>"Copyright © 2017-2018, The Apache Software Foundation Apache MXNet, MXNet, Apache, the Apache
-                    feather, and the Apache MXNet project logo are either registered trademarks or trademarks of the
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-  </body>
-</html>
\ No newline at end of file
diff --git a/api/python/docs/_modules/mxnet/contrib/io.html b/api/python/docs/_modules/mxnet/contrib/io.html
index 0c3f9c2..9023a89 100644
--- a/api/python/docs/_modules/mxnet/contrib/io.html
+++ b/api/python/docs/_modules/mxnet/contrib/io.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/contrib/io" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
diff --git a/api/python/docs/_modules/mxnet/contrib/ndarray.html b/api/python/docs/_modules/mxnet/contrib/ndarray.html
index c3a9264..91b9d87 100644
--- a/api/python/docs/_modules/mxnet/contrib/ndarray.html
+++ b/api/python/docs/_modules/mxnet/contrib/ndarray.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/contrib/ndarray" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
diff --git a/api/python/docs/_modules/mxnet/contrib/onnx/mx2onnx/export_model.html b/api/python/docs/_modules/mxnet/contrib/onnx/mx2onnx/export_model.html
index a6e5453..3205879 100644
--- a/api/python/docs/_modules/mxnet/contrib/onnx/mx2onnx/export_model.html
+++ b/api/python/docs/_modules/mxnet/contrib/onnx/mx2onnx/export_model.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/contrib/onnx/mx2onnx/export_model" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
diff --git a/api/python/docs/_modules/mxnet/contrib/onnx/onnx2mx/import_model.html b/api/python/docs/_modules/mxnet/contrib/onnx/onnx2mx/import_model.html
index 97b523f..85ebf62 100644
--- a/api/python/docs/_modules/mxnet/contrib/onnx/onnx2mx/import_model.html
+++ b/api/python/docs/_modules/mxnet/contrib/onnx/onnx2mx/import_model.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/contrib/onnx/onnx2mx/import_model" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
diff --git a/api/python/docs/_modules/mxnet/contrib/onnx/onnx2mx/import_to_gluon.html b/api/python/docs/_modules/mxnet/contrib/onnx/onnx2mx/import_to_gluon.html
index a9a0621..5ab6832 100644
--- a/api/python/docs/_modules/mxnet/contrib/onnx/onnx2mx/import_to_gluon.html
+++ b/api/python/docs/_modules/mxnet/contrib/onnx/onnx2mx/import_to_gluon.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/contrib/onnx/onnx2mx/import_to_gluon" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
diff --git a/api/python/docs/_modules/mxnet/contrib/symbol.html b/api/python/docs/_modules/mxnet/contrib/symbol.html
index 779a9b3..a017670 100644
--- a/api/python/docs/_modules/mxnet/contrib/symbol.html
+++ b/api/python/docs/_modules/mxnet/contrib/symbol.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/contrib/symbol" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
diff --git a/api/python/docs/_modules/mxnet/contrib/tensorboard.html b/api/python/docs/_modules/mxnet/contrib/tensorboard.html
index 5da758f..7310661 100644
--- a/api/python/docs/_modules/mxnet/contrib/tensorboard.html
+++ b/api/python/docs/_modules/mxnet/contrib/tensorboard.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/contrib/tensorboard" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
diff --git a/api/python/docs/_modules/mxnet/contrib/tensorrt.html b/api/python/docs/_modules/mxnet/contrib/tensorrt.html
index ce7ac8e..6be81b5 100644
--- a/api/python/docs/_modules/mxnet/contrib/tensorrt.html
+++ b/api/python/docs/_modules/mxnet/contrib/tensorrt.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/contrib/tensorrt" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
diff --git a/api/python/docs/_modules/mxnet/dlpack.html b/api/python/docs/_modules/mxnet/dlpack.html
index 6932074..720ce20 100644
--- a/api/python/docs/_modules/mxnet/dlpack.html
+++ b/api/python/docs/_modules/mxnet/dlpack.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/dlpack" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
diff --git a/api/python/docs/_modules/mxnet/engine.html b/api/python/docs/_modules/mxnet/engine.html
index ebf9bc7..7df659c 100644
--- a/api/python/docs/_modules/mxnet/engine.html
+++ b/api/python/docs/_modules/mxnet/engine.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/engine" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
diff --git a/api/python/docs/_modules/mxnet/executor.html b/api/python/docs/_modules/mxnet/executor.html
index cf8b17c..d148d26 100644
--- a/api/python/docs/_modules/mxnet/executor.html
+++ b/api/python/docs/_modules/mxnet/executor.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/executor" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
diff --git a/api/python/docs/_modules/mxnet/gluon/block.html b/api/python/docs/_modules/mxnet/gluon/block.html
index 0e37676..84e2704 100644
--- a/api/python/docs/_modules/mxnet/gluon/block.html
+++ b/api/python/docs/_modules/mxnet/gluon/block.html
@@ -108,6 +108,7 @@
           </span>
           <div class="dropdown-content">
             <a class="dropdown-option-active" href="/">master</a><br>
+            <a class="dropdown-option" href="/versions/1.7/">1.7</a><br>
             <a class="dropdown-option" href="/versions/1.6/">1.6</a><br>
             <a class="dropdown-option" href="/versions/1.5.0/">1.5.0</a><br>
             <a class="dropdown-option" href="/versions/1.4.1/">1.4.1</a><br>
@@ -149,6 +150,13 @@
       </div>
 </form>
         
+<a id="button-show-github"
+    href="https://github.com/apache/mxnet/edit/master/docs/python_docs/python/_modules/mxnet/gluon/block" class="mdl-button mdl-js-button mdl-button--icon">
+<i class="material-icons">edit</i>
+</a>
+<div class="mdl-tooltip" data-mdl-for="button-show-github">
+Edit on Github
+</div>
         </nav>
     </div>
     <div class="mdl-layout__header-row header-links">
@@ -1207,6 +1215,7 @@
 <span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;Block&#39;</span><span class="p">,</span> <span class="s1">&#39;HybridBlock&#39;</span><span class="p">,</span> <span class="s1">&#39;SymbolBlock&#39;</span><span class="p">]</span>
 
 <span class="kn">import</span> <span class="nn">copy</span>
+<span class="kn">import</span> <span class="nn">inspect</span>
 <span class="kn">import</span> <span class="nn">warnings</span>
 <span class="kn">import</span> <span class="nn">weakref</span>
 <span class="kn">from</span> <span class="nn">collections</span> <span class="kn">import</span> <span class="n">OrderedDict</span><span class="p">,</span> <span class="n">defaultdict</span>
@@ -2133,8 +2142,8 @@
                     <span class="n">flatten_inputs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
             <span class="n">grouped_inputs</span> <span class="o">=</span> <span class="n">_regroup</span><span class="p">(</span><span class="n">flatten_inputs</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_in_format</span><span class="p">)</span>
 
-            <span class="n">params</span> <span class="o">=</span> <span class="p">{</span><span class="n">i</span><span class="p">:</span> <span class="n">j</span><span class="o">.</span><span class="n">var</span><span class="p">()</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">j</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_reg_params</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
             <span class="k">with</span> <span class="n">_block_scope</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+                <span class="n">params</span> <span class="o">=</span> <span class="p">{</span><span class="n">i</span><span class="p">:</span> <span class="n">j</span><span class="o">.</span><span class="n">var</span><span class="p">()</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">j</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_reg_params</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
                 <span class="n">out</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="p">(</span><span class="n">symbol</span><span class="p">,</span> <span class="o">*</span><span class="n">grouped_inputs</span><span class="p">,</span> <span class="o">**</span><span class="n">params</span><span class="p">)</span>  <span class="c1"># pylint: disable=no-value-for-parameter</span>
             <span class="n">out</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_out_format</span> <span class="o">=</span> <span class="n">_flatten</span><span class="p">(</span><span class="n">out</span><span class="p">,</span> <span class="s2">&quot;output&quot;</span><span class="p">)</span>
 
@@ -2170,7 +2179,7 @@
 
     <span class="k">def</span> <span class="nf">_get_graph</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
         <span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">_cached_graph</span><span class="p">:</span>
-            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="o">.</span><span class="vm">__func__</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">HybridBlock</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="p">:</span>  <span class="c1"># Gluon 1</span>
+            <span class="k">if</span> <span class="n">inspect</span><span class="o">.</span><span class="n">unwrap</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="o">.</span><span class="vm">__func__</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">HybridBlock</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="p">:</span>
                 <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_graph_v1</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">)</span>
             <span class="k">else</span><span class="p">:</span>  <span class="c1"># Gluon 2 based on deferred compute mode</span>
                 <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_graph_v2</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">)</span>
@@ -2463,7 +2472,7 @@
 
 <div class="viewcode-block" id="HybridBlock.infer_shape"><a class="viewcode-back" href="../../../api/gluon/nn/index.html#mxnet.gluon.nn.HybridBlock.infer_shape">[docs]</a>    <span class="k">def</span> <span class="nf">infer_shape</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
         <span class="sd">&quot;&quot;&quot;Infers shape of Parameters from inputs.&quot;&quot;&quot;</span>
-        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="o">.</span><span class="vm">__func__</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">HybridBlock</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">inspect</span><span class="o">.</span><span class="n">unwrap</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="o">.</span><span class="vm">__func__</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">HybridBlock</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="p">:</span>
             <span class="c1"># Gluon 1 based on F:  hybrid_forward is defined by user</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">_infer_attrs</span><span class="p">(</span><span class="s1">&#39;infer_shape&#39;</span><span class="p">,</span> <span class="s1">&#39;shape&#39;</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">)</span>
         <span class="k">else</span><span class="p">:</span>
@@ -2574,7 +2583,7 @@
             <span class="n">cld</span><span class="p">()</span><span class="o">.</span><span class="n">_monitor_all</span> <span class="o">=</span> <span class="n">monitor_all</span></div>
 
     <span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
-        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="o">.</span><span class="vm">__func__</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">HybridBlock</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="p">:</span>
+        <span class="k">if</span> <span class="n">inspect</span><span class="o">.</span><span class="n">unwrap</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="o">.</span><span class="vm">__func__</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="n">HybridBlock</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="p">:</span>
             <span class="c1"># Gluon 1 based on F:  hybrid_forward is defined by user</span>
             <span class="k">return</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__call__</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">)</span>
         <span class="k">else</span><span class="p">:</span>  <span class="c1"># Gluon 2 based on deferred compute mode</span>
@@ -2597,7 +2606,8 @@
                 <span class="c1"># HybridBlock is a child block of a HybridBlock that has been hybridized.</span>
                 <span class="k">return</span> <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__call__</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">)</span>
 
-            <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_call_cached_op</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">)</span>
+            <span class="k">with</span> <span class="n">x</span><span class="o">.</span><span class="n">ctx</span><span class="p">:</span>
+                <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_call_cached_op</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">)</span>
 
 <div class="viewcode-block" id="HybridBlock.forward"><a class="viewcode-back" href="../../../api/gluon/nn/index.html#mxnet.gluon.nn.HybridBlock.forward">[docs]</a>    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
         <span class="sd">&quot;&quot;&quot;Defines the forward computation. Arguments can be either</span>
@@ -2633,8 +2643,8 @@
 
                 <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="p">(</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">params</span><span class="p">)</span>
 
-        <span class="n">params</span> <span class="o">=</span> <span class="p">{</span><span class="n">i</span><span class="p">:</span> <span class="n">j</span><span class="o">.</span><span class="n">var</span><span class="p">()</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">j</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_reg_params</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
         <span class="k">with</span> <span class="n">_block_scope</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+            <span class="n">params</span> <span class="o">=</span> <span class="p">{</span><span class="n">i</span><span class="p">:</span> <span class="n">j</span><span class="o">.</span><span class="n">var</span><span class="p">()</span> <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">j</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_reg_params</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
             <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">hybrid_forward</span><span class="p">(</span><span class="n">symbol</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">params</span><span class="p">)</span></div>
 
 <div class="viewcode-block" id="HybridBlock.hybrid_forward"><a class="viewcode-back" href="../../../api/gluon/nn/index.html#mxnet.gluon.nn.HybridBlock.hybrid_forward">[docs]</a>    <span class="k">def</span> <span class="nf">hybrid_forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">F</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
@@ -2700,7 +2710,8 @@
 <span class="sd">    &gt;&gt;&gt; print(feat_model(x))</span>
 <span class="sd">    &quot;&quot;&quot;</span>
 <div class="viewcode-block" id="SymbolBlock.imports"><a class="viewcode-back" href="../../../api/gluon/nn/index.html#mxnet.gluon.nn.SymbolBlock.imports">[docs]</a>    <span class="nd">@staticmethod</span>
-    <span class="k">def</span> <span class="nf">imports</span><span class="p">(</span><span class="n">symbol_file</span><span class="p">,</span> <span class="n">input_names</span><span class="p">,</span> <span class="n">param_file</span><span class="o">=</span><span class="kc">None</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="k">def</span> <span class="nf">imports</span><span class="p">(</span><span class="n">symbol_file</span><span class="p">,</span> <span class="n">input_names</span><span class="p">,</span> <span class="n">param_file</span><span class="o">=</span><span class="kc">None</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">allow_missing</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
+                <span class="n">ignore_extra</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
         <span class="sd">&quot;&quot;&quot;Import model previously saved by `gluon.HybridBlock.export`</span>
 <span class="sd">        as a `gluon.SymbolBlock` for use in Gluon.</span>
 
@@ -2714,6 +2725,11 @@
 <span class="sd">            Path to parameter file.</span>
 <span class="sd">        ctx : Context, default None</span>
 <span class="sd">            The context to initialize `gluon.SymbolBlock` on.</span>
+<span class="sd">        allow_missing : bool, default False</span>
+<span class="sd">            Whether to silently skip loading parameters not represents in the file.</span>
+<span class="sd">        ignore_extra : bool, default False</span>
+<span class="sd">            Whether to silently ignore parameters from the file that are not</span>
+<span class="sd">            present in this Block.</span>
 
 <span class="sd">        Returns</span>
 <span class="sd">        -------</span>
@@ -2746,7 +2762,7 @@
             <span class="n">inputs</span> <span class="o">=</span> <span class="p">[</span><span class="n">symbol</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="n">i</span><span class="p">)</span><span class="o">.</span><span class="n">as_np_ndarray</span><span class="p">()</span> <span class="k">if</span> <span class="n">is_np_array</span><span class="p">()</span> <span class="k">else</span> <span class="n">symbol</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">input_names</span><span class="p">]</span>
         <span class="n">ret</span> <span class="o">=</span> <span class="n">SymbolBlock</span><span class="p">(</span><span class="n">sym</span><span class="p">,</span> <span class="n">inputs</span><span class="p">)</span>
         <span class="k">if</span> <span class="n">param_file</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">ret</span><span class="o">.</span><span class="n">load_parameters</span><span class="p">(</span><span class="n">param_file</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">cast_dtype</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">dtype_source</span><span class="o">=</span><span class="s1">&#39;saved&#39;</span><span class="p">)</span>
+            <span class="n">ret</span><span class="o">.</span><span class="n">load_parameters</span><span class="p">(</span><span class="n">param_file</span><span class="p">,</span> <span class="n">ctx</span><span class="p">,</span> <span class="n">allow_missing</span><span class="p">,</span> <span class="n">ignore_extra</span><span class="p">,</span> <span class="kc">True</span><span class="p">,</span> <span class="s1">&#39;saved&#39;</span><span class="p">)</span>
         <span class="k">return</span> <span class="n">ret</span></div>
 
     <span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
diff --git a/api/python/docs/_modules/mxnet/gluon/contrib/cnn/conv_layers.html b/api/python/docs/_modules/mxnet/gluon/contrib/cnn/conv_layers.html
deleted file mode 100644
index 59439a5..0000000
--- a/api/python/docs/_modules/mxnet/gluon/contrib/cnn/conv_layers.html
+++ /dev/null
@@ -1,1655 +0,0 @@
-<!DOCTYPE html>
-
-<html xmlns="http://www.w3.org/1999/xhtml">
-  <head>
-    <meta charset="utf-8" />
-    <meta charset="utf-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
-    <meta http-equiv="x-ua-compatible" content="ie=edge">
-    <style>
-    .dropdown {
-        position: relative;
-        display: inline-block;
-    }
-
-    .dropdown-content {
-        display: none;
-        position: absolute;
-        background-color: #f9f9f9;
-        min-width: 160px;
-        box-shadow: 0px 8px 16px 0px rgba(0,0,0,0.2);
-        padding: 12px 16px;
-        z-index: 1;
-        text-align: left;
-    }
-
-    .dropdown:hover .dropdown-content {
-        display: block;
-    }
-
-    .dropdown-option:hover {
-        color: #FF4500;
-    }
-
-    .dropdown-option-active {
-        color: #FF4500;
-        font-weight: lighter;
-    }
-
-    .dropdown-option {
-        color: #000000;
-        font-weight: lighter;
-    }
-
-    .dropdown-header {
-        color: #FFFFFF;
-        display: inline-flex;
-    }
-
-    .dropdown-caret {
-        width: 18px;
-        height: 54px;
-    }
-
-    .dropdown-caret-path {
-        fill: #FFFFFF;
-    }
-    </style>
-    
-    <title>mxnet.gluon.contrib.cnn.conv_layers &#8212; Apache MXNet  documentation</title>
-
-    <link rel="stylesheet" href="../../../../../_static/basic.css" type="text/css" />
-    <link rel="stylesheet" href="../../../../../_static/pygments.css" type="text/css" />
-    <link rel="stylesheet" type="text/css" href="../../../../../_static/mxnet.css" />
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-    <script async="async" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/latest.js?config=TeX-AMS-MML_HTMLorMML"></script>
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-<li class="toctree-l4"><a class="reference internal" href="../../../../../tutorials/getting-started/crash-course/1-ndarray.html">Step 1: Manipulate data with NP on MXNet</a></li>
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-  <h1>Source code for mxnet.gluon.contrib.cnn.conv_layers</h1><div class="highlight"><pre>
-<span></span><span class="c1"># Licensed to the Apache Software Foundation (ASF) under one</span>
-<span class="c1"># or more contributor license agreements.  See the NOTICE file</span>
-<span class="c1"># distributed with this work for additional information</span>
-<span class="c1"># regarding copyright ownership.  The ASF licenses this file</span>
-<span class="c1"># to you under the Apache License, Version 2.0 (the</span>
-<span class="c1"># &quot;License&quot;); you may not use this file except in compliance</span>
-<span class="c1"># with the License.  You may obtain a copy of the License at</span>
-<span class="c1">#</span>
-<span class="c1">#   http://www.apache.org/licenses/LICENSE-2.0</span>
-<span class="c1">#</span>
-<span class="c1"># Unless required by applicable law or agreed to in writing,</span>
-<span class="c1"># software distributed under the License is distributed on an</span>
-<span class="c1"># &quot;AS IS&quot; BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span>
-<span class="c1"># KIND, either express or implied.  See the License for the</span>
-<span class="c1"># specific language governing permissions and limitations</span>
-<span class="c1"># under the License.</span>
-
-<span class="c1"># coding: utf-8</span>
-<span class="c1"># pylint: disable= arguments-differ</span>
-<span class="sd">&quot;&quot;&quot;Custom convolutional neural network layers in model_zoo.&quot;&quot;&quot;</span>
-
-<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;DeformableConvolution&#39;</span><span class="p">,</span> <span class="s1">&#39;ModulatedDeformableConvolution&#39;</span><span class="p">]</span>
-
-<span class="kn">from</span> <span class="nn">....</span> <span class="kn">import</span> <span class="n">symbol</span>
-<span class="kn">from</span> <span class="nn">...block</span> <span class="kn">import</span> <span class="n">HybridBlock</span>
-<span class="kn">from</span> <span class="nn">...parameter</span> <span class="kn">import</span> <span class="n">Parameter</span>
-<span class="kn">from</span> <span class="nn">....base</span> <span class="kn">import</span> <span class="n">numeric_types</span>
-<span class="kn">from</span> <span class="nn">...nn</span> <span class="kn">import</span> <span class="n">Activation</span>
-
-<div class="viewcode-block" id="DeformableConvolution"><a class="viewcode-back" href="../../../../../api/gluon/contrib/index.html#mxnet.gluon.contrib.cnn.DeformableConvolution">[docs]</a><span class="k">class</span> <span class="nc">DeformableConvolution</span><span class="p">(</span><span class="n">HybridBlock</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;2-D Deformable Convolution v_1 (Dai, 2017).</span>
-<span class="sd">    Normal Convolution uses sampling points in a regular grid, while the sampling</span>
-<span class="sd">    points of Deformablem Convolution can be offset. The offset is learned with a</span>
-<span class="sd">    separate convolution layer during the training. Both the convolution layer for</span>
-<span class="sd">    generating the output features and the offsets are included in this gluon layer.</span>
-
-<span class="sd">    Parameters</span>
-<span class="sd">    ----------</span>
-<span class="sd">    channels : int,</span>
-<span class="sd">        The dimensionality of the output space</span>
-<span class="sd">        i.e. the number of output channels in the convolution.</span>
-<span class="sd">    kernel_size : int or tuple/list of 2 ints, (Default value = (1,1))</span>
-<span class="sd">        Specifies the dimensions of the convolution window.</span>
-<span class="sd">    strides : int or tuple/list of 2 ints, (Default value = (1,1))</span>
-<span class="sd">        Specifies the strides of the convolution.</span>
-<span class="sd">    padding : int or tuple/list of 2 ints, (Default value = (0,0))</span>
-<span class="sd">        If padding is non-zero, then the input is implicitly zero-padded</span>
-<span class="sd">        on both sides for padding number of points.</span>
-<span class="sd">    dilation : int or tuple/list of 2 ints, (Default value = (1,1))</span>
-<span class="sd">        Specifies the dilation rate to use for dilated convolution.</span>
-<span class="sd">    groups : int, (Default value = 1)</span>
-<span class="sd">        Controls the connections between inputs and outputs.</span>
-<span class="sd">        At groups=1, all inputs are convolved to all outputs.</span>
-<span class="sd">        At groups=2, the operation becomes equivalent to having two convolution</span>
-<span class="sd">        layers side by side, each seeing half the input channels, and producing</span>
-<span class="sd">        half the output channels, and both subsequently concatenated.</span>
-<span class="sd">    num_deformable_group : int, (Default value = 1)</span>
-<span class="sd">        Number of deformable group partitions.</span>
-<span class="sd">    layout : str, (Default value = NCHW)</span>
-<span class="sd">        Dimension ordering of data and weight. Can be &#39;NCW&#39;, &#39;NWC&#39;, &#39;NCHW&#39;,</span>
-<span class="sd">        &#39;NHWC&#39;, &#39;NCDHW&#39;, &#39;NDHWC&#39;, etc. &#39;N&#39;, &#39;C&#39;, &#39;H&#39;, &#39;W&#39;, &#39;D&#39; stands for</span>
-<span class="sd">        batch, channel, height, width and depth dimensions respectively.</span>
-<span class="sd">        Convolution is performed over &#39;D&#39;, &#39;H&#39;, and &#39;W&#39; dimensions.</span>
-<span class="sd">    use_bias : bool, (Default value = True)</span>
-<span class="sd">        Whether the layer for generating the output features uses a bias vector.</span>
-<span class="sd">    in_channels : int, (Default value = 0)</span>
-<span class="sd">        The number of input channels to this layer. If not specified,</span>
-<span class="sd">        initialization will be deferred to the first time `forward` is called</span>
-<span class="sd">        and input channels will be inferred from the shape of input data.</span>
-<span class="sd">    activation : str, (Default value = None)</span>
-<span class="sd">        Activation function to use. See :func:`~mxnet.ndarray.Activation`.</span>
-<span class="sd">        If you don&#39;t specify anything, no activation is applied</span>
-<span class="sd">        (ie. &quot;linear&quot; activation: `a(x) = x`).</span>
-<span class="sd">    weight_initializer : str or `Initializer`, (Default value = None)</span>
-<span class="sd">        Initializer for the `weight` weights matrix for the convolution layer</span>
-<span class="sd">        for generating the output features.</span>
-<span class="sd">    bias_initializer : str or `Initializer`, (Default value = zeros)</span>
-<span class="sd">        Initializer for the bias vector for the convolution layer</span>
-<span class="sd">        for generating the output features.</span>
-<span class="sd">    offset_weight_initializer : str or `Initializer`, (Default value = zeros)</span>
-<span class="sd">        Initializer for the `weight` weights matrix for the convolution layer</span>
-<span class="sd">        for generating the offset.</span>
-<span class="sd">    offset_bias_initializer : str or `Initializer`, (Default value = zeros),</span>
-<span class="sd">        Initializer for the bias vector for the convolution layer</span>
-<span class="sd">        for generating the offset.</span>
-<span class="sd">    offset_use_bias: bool, (Default value = True)</span>
-<span class="sd">        Whether the layer for generating the offset uses a bias vector.</span>
-
-<span class="sd">    Inputs:</span>
-<span class="sd">        - **data**: 4D input tensor with shape</span>
-<span class="sd">          `(batch_size, in_channels, height, width)` when `layout` is `NCHW`.</span>
-<span class="sd">          For other layouts shape is permuted accordingly.</span>
-
-<span class="sd">    Outputs:</span>
-<span class="sd">        - **out**: 4D output tensor with shape</span>
-<span class="sd">          `(batch_size, channels, out_height, out_width)` when `layout` is `NCHW`.</span>
-<span class="sd">          out_height and out_width are calculated as::</span>
-
-<span class="sd">              out_height = floor((height+2*padding[0]-dilation[0]*(kernel_size[0]-1)-1)/stride[0])+1</span>
-<span class="sd">              out_width = floor((width+2*padding[1]-dilation[1]*(kernel_size[1]-1)-1)/stride[1])+1</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-
-    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">strides</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">padding</span><span class="o">=</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dilation</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">groups</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
-                 <span class="n">num_deformable_group</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">layout</span><span class="o">=</span><span class="s1">&#39;NCHW&#39;</span><span class="p">,</span> <span class="n">use_bias</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">in_channels</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">activation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
-                 <span class="n">weight_initializer</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">bias_initializer</span><span class="o">=</span><span class="s1">&#39;zeros&#39;</span><span class="p">,</span>
-                 <span class="n">offset_weight_initializer</span><span class="o">=</span><span class="s1">&#39;zeros&#39;</span><span class="p">,</span> <span class="n">offset_bias_initializer</span><span class="o">=</span><span class="s1">&#39;zeros&#39;</span><span class="p">,</span> <span class="n">offset_use_bias</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
-                 <span class="n">op_name</span><span class="o">=</span><span class="s1">&#39;DeformableConvolution&#39;</span><span class="p">,</span> <span class="n">adj</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
-        <span class="nb">super</span><span class="p">(</span><span class="n">DeformableConvolution</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_channels</span> <span class="o">=</span> <span class="n">channels</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_in_channels</span> <span class="o">=</span> <span class="n">in_channels</span>
-
-        <span class="k">assert</span> <span class="n">layout</span> <span class="ow">in</span> <span class="p">(</span><span class="s1">&#39;NCHW&#39;</span><span class="p">,</span> <span class="s1">&#39;NHWC&#39;</span><span class="p">),</span> <span class="s2">&quot;Only supports &#39;NCHW&#39; and &#39;NHWC&#39; layout for now&quot;</span>
-        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span>
-            <span class="n">kernel_size</span> <span class="o">=</span> <span class="p">(</span><span class="n">kernel_size</span><span class="p">,)</span> <span class="o">*</span> <span class="mi">2</span>
-        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">strides</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span>
-            <span class="n">strides</span> <span class="o">=</span> <span class="p">(</span><span class="n">strides</span><span class="p">,)</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">)</span>
-        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">padding</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span>
-            <span class="n">padding</span> <span class="o">=</span> <span class="p">(</span><span class="n">padding</span><span class="p">,)</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">)</span>
-        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">dilation</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span>
-            <span class="n">dilation</span> <span class="o">=</span> <span class="p">(</span><span class="n">dilation</span><span class="p">,)</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">)</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_op_name</span> <span class="o">=</span> <span class="n">op_name</span>
-
-        <span class="n">offset_channels</span> <span class="o">=</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">kernel_size</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">kernel_size</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">*</span> <span class="n">num_deformable_group</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_offset</span> <span class="o">=</span> <span class="p">{</span>
-            <span class="s1">&#39;kernel&#39;</span><span class="p">:</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="s1">&#39;stride&#39;</span><span class="p">:</span> <span class="n">strides</span><span class="p">,</span> <span class="s1">&#39;dilate&#39;</span><span class="p">:</span> <span class="n">dilation</span><span class="p">,</span>
-            <span class="s1">&#39;pad&#39;</span><span class="p">:</span> <span class="n">padding</span><span class="p">,</span> <span class="s1">&#39;num_filter&#39;</span><span class="p">:</span> <span class="n">offset_channels</span><span class="p">,</span> <span class="s1">&#39;num_group&#39;</span><span class="p">:</span> <span class="n">groups</span><span class="p">,</span>
-            <span class="s1">&#39;no_bias&#39;</span><span class="p">:</span> <span class="ow">not</span> <span class="n">offset_use_bias</span><span class="p">,</span> <span class="s1">&#39;layout&#39;</span><span class="p">:</span> <span class="n">layout</span><span class="p">}</span>
-
-        <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span> <span class="o">=</span> <span class="p">{</span>
-            <span class="s1">&#39;kernel&#39;</span><span class="p">:</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="s1">&#39;stride&#39;</span><span class="p">:</span> <span class="n">strides</span><span class="p">,</span> <span class="s1">&#39;dilate&#39;</span><span class="p">:</span> <span class="n">dilation</span><span class="p">,</span>
-            <span class="s1">&#39;pad&#39;</span><span class="p">:</span> <span class="n">padding</span><span class="p">,</span> <span class="s1">&#39;num_filter&#39;</span><span class="p">:</span> <span class="n">channels</span><span class="p">,</span> <span class="s1">&#39;num_group&#39;</span><span class="p">:</span> <span class="n">groups</span><span class="p">,</span>
-            <span class="s1">&#39;num_deformable_group&#39;</span><span class="p">:</span> <span class="n">num_deformable_group</span><span class="p">,</span>
-            <span class="s1">&#39;no_bias&#39;</span><span class="p">:</span> <span class="ow">not</span> <span class="n">use_bias</span><span class="p">,</span> <span class="s1">&#39;layout&#39;</span><span class="p">:</span> <span class="n">layout</span><span class="p">}</span>
-
-        <span class="k">if</span> <span class="n">adj</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_offset</span><span class="p">[</span><span class="s1">&#39;adj&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">adj</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span><span class="p">[</span><span class="s1">&#39;adj&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">adj</span>
-
-        <span class="n">dshape</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">)</span> <span class="o">+</span> <span class="mi">2</span><span class="p">)</span>
-        <span class="n">dshape</span><span class="p">[</span><span class="n">layout</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">)]</span> <span class="o">=</span> <span class="mi">1</span>
-        <span class="n">dshape</span><span class="p">[</span><span class="n">layout</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;C&#39;</span><span class="p">)]</span> <span class="o">=</span> <span class="n">in_channels</span>
-
-        <span class="n">op</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">symbol</span><span class="p">,</span> <span class="s1">&#39;Convolution&#39;</span><span class="p">)</span>
-        <span class="n">offset</span> <span class="o">=</span> <span class="n">op</span><span class="p">(</span><span class="n">symbol</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="s1">&#39;data&#39;</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="n">dshape</span><span class="p">),</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_offset</span><span class="p">)</span>
-
-        <span class="n">offsetshapes</span> <span class="o">=</span> <span class="n">offset</span><span class="o">.</span><span class="n">infer_shape_partial</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
-
-        <span class="bp">self</span><span class="o">.</span><span class="n">offset_weight</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="s1">&#39;offset_weight&#39;</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="n">offsetshapes</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span>
-                                       <span class="n">init</span><span class="o">=</span><span class="n">offset_weight_initializer</span><span class="p">,</span>
-                                       <span class="n">allow_deferred_init</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-
-        <span class="k">if</span> <span class="n">offset_use_bias</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">offset_bias</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="s1">&#39;offset_bias&#39;</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="n">offsetshapes</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span>
-                                         <span class="n">init</span><span class="o">=</span><span class="n">offset_bias_initializer</span><span class="p">,</span>
-                                         <span class="n">allow_deferred_init</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">offset_bias</span> <span class="o">=</span> <span class="kc">None</span>
-
-        <span class="n">deformable_conv_weight_shape</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">)</span> <span class="o">+</span> <span class="mi">2</span><span class="p">)</span>
-        <span class="n">deformable_conv_weight_shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">channels</span>
-        <span class="n">deformable_conv_weight_shape</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">=</span> <span class="n">kernel_size</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
-        <span class="n">deformable_conv_weight_shape</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span> <span class="o">=</span> <span class="n">kernel_size</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
-
-        <span class="bp">self</span><span class="o">.</span><span class="n">deformable_conv_weight</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="s1">&#39;deformable_conv_weight&#39;</span><span class="p">,</span>
-                                                <span class="n">shape</span><span class="o">=</span><span class="n">deformable_conv_weight_shape</span><span class="p">,</span>
-                                                <span class="n">init</span><span class="o">=</span><span class="n">weight_initializer</span><span class="p">,</span>
-                                                <span class="n">allow_deferred_init</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-
-        <span class="k">if</span> <span class="n">use_bias</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">deformable_conv_bias</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="s1">&#39;deformable_conv_bias&#39;</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="n">channels</span><span class="p">,),</span>
-                                                  <span class="n">init</span><span class="o">=</span><span class="n">bias_initializer</span><span class="p">,</span>
-                                                  <span class="n">allow_deferred_init</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">deformable_conv_bias</span> <span class="o">=</span> <span class="kc">None</span>
-
-        <span class="k">if</span> <span class="n">activation</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">act</span> <span class="o">=</span> <span class="n">Activation</span><span class="p">(</span><span class="n">activation</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">act</span> <span class="o">=</span> <span class="kc">None</span>
-
-<div class="viewcode-block" id="DeformableConvolution.hybrid_forward"><a class="viewcode-back" href="../../../../../api/gluon/contrib/index.html#mxnet.gluon.contrib.cnn.DeformableConvolution.hybrid_forward">[docs]</a>    <span class="k">def</span> <span class="nf">hybrid_forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">F</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">offset_weight</span><span class="p">,</span> <span class="n">deformable_conv_weight</span><span class="p">,</span> <span class="n">offset_bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">deformable_conv_bias</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
-        <span class="k">if</span> <span class="n">offset_bias</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">offset</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">Convolution</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">offset_weight</span><span class="p">,</span> <span class="n">cudnn_off</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_offset</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="n">offset</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">Convolution</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">offset_weight</span><span class="p">,</span> <span class="n">offset_bias</span><span class="p">,</span> <span class="n">cudnn_off</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_offset</span><span class="p">)</span>
-
-        <span class="k">if</span> <span class="n">deformable_conv_bias</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">act</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">DeformableConvolution</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">x</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="n">offset</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="n">deformable_conv_weight</span><span class="p">,</span>
-                                                  <span class="n">name</span><span class="o">=</span><span class="s1">&#39;fwd&#39;</span><span class="p">,</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="n">act</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">DeformableConvolution</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">x</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="n">offset</span><span class="p">,</span> <span class="n">weight</span><span class="o">=</span><span class="n">deformable_conv_weight</span><span class="p">,</span>
-                                                  <span class="n">bias</span><span class="o">=</span><span class="n">deformable_conv_bias</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;fwd&#39;</span><span class="p">,</span>
-                                                  <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span><span class="p">)</span>
-
-        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">act</span><span class="p">:</span>
-            <span class="n">act</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">act</span><span class="p">(</span><span class="n">act</span><span class="p">)</span>
-        <span class="k">return</span> <span class="n">act</span></div>
-
-    <span class="k">def</span> <span class="nf">_alias</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="k">return</span> <span class="s1">&#39;deformable_conv&#39;</span>
-
-    <span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="n">s</span> <span class="o">=</span> <span class="s1">&#39;</span><span class="si">{name}</span><span class="s1">(</span><span class="si">{mapping}</span><span class="s1">, kernel_size=</span><span class="si">{kernel}</span><span class="s1">, stride=</span><span class="si">{stride}</span><span class="s1">&#39;</span>
-        <span class="n">len_kernel_size</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span><span class="p">[</span><span class="s1">&#39;kernel&#39;</span><span class="p">])</span>
-        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span><span class="p">[</span><span class="s1">&#39;pad&#39;</span><span class="p">]</span> <span class="o">!=</span> <span class="p">(</span><span class="mi">0</span><span class="p">,)</span> <span class="o">*</span> <span class="n">len_kernel_size</span><span class="p">:</span>
-            <span class="n">s</span> <span class="o">+=</span> <span class="s1">&#39;, padding=</span><span class="si">{pad}</span><span class="s1">&#39;</span>
-        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span><span class="p">[</span><span class="s1">&#39;dilate&#39;</span><span class="p">]</span> <span class="o">!=</span> <span class="p">(</span><span class="mi">1</span><span class="p">,)</span> <span class="o">*</span> <span class="n">len_kernel_size</span><span class="p">:</span>
-            <span class="n">s</span> <span class="o">+=</span> <span class="s1">&#39;, dilation=</span><span class="si">{dilate}</span><span class="s1">&#39;</span>
-        <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;out_pad&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">out_pad</span> <span class="o">!=</span> <span class="p">(</span><span class="mi">0</span><span class="p">,)</span> <span class="o">*</span> <span class="n">len_kernel_size</span><span class="p">:</span>
-            <span class="n">s</span> <span class="o">+=</span> <span class="s1">&#39;, output_padding=</span><span class="si">{out_pad}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">out_pad</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">out_pad</span><span class="p">)</span>
-        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span><span class="p">[</span><span class="s1">&#39;num_group&#39;</span><span class="p">]</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span>
-            <span class="n">s</span> <span class="o">+=</span> <span class="s1">&#39;, groups=</span><span class="si">{num_group}</span><span class="s1">&#39;</span>
-        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">deformable_conv_bias</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">s</span> <span class="o">+=</span> <span class="s1">&#39;, bias=False&#39;</span>
-        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">act</span><span class="p">:</span>
-            <span class="n">s</span> <span class="o">+=</span> <span class="s1">&#39;, </span><span class="si">{}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">act</span><span class="p">)</span>
-        <span class="n">s</span> <span class="o">+=</span> <span class="s1">&#39;)&#39;</span>
-        <span class="n">shape</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">deformable_conv_weight</span><span class="o">.</span><span class="n">shape</span>
-        <span class="k">return</span> <span class="n">s</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="p">,</span>
-                        <span class="n">mapping</span><span class="o">=</span><span class="s1">&#39;</span><span class="si">{0}</span><span class="s1"> -&gt; </span><span class="si">{1}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">if</span> <span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">else</span> <span class="kc">None</span><span class="p">,</span> <span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span>
-                        <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span><span class="p">)</span></div>
-
-
-<div class="viewcode-block" id="ModulatedDeformableConvolution"><a class="viewcode-back" href="../../../../../api/gluon/contrib/index.html#mxnet.gluon.contrib.cnn.ModulatedDeformableConvolution">[docs]</a><span class="k">class</span> <span class="nc">ModulatedDeformableConvolution</span><span class="p">(</span><span class="n">HybridBlock</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;2-D Deformable Convolution v2 (Dai, 2018).</span>
-
-<span class="sd">    The modulated deformable convolution operation is described in https://arxiv.org/abs/1811.11168</span>
-
-<span class="sd">    Parameters</span>
-<span class="sd">    ----------</span>
-<span class="sd">    channels : int,</span>
-<span class="sd">        The dimensionality of the output space</span>
-<span class="sd">        i.e. the number of output channels in the convolution.</span>
-<span class="sd">    kernel_size : int or tuple/list of 2 ints, (Default value = (1,1))</span>
-<span class="sd">        Specifies the dimensions of the convolution window.</span>
-<span class="sd">    strides : int or tuple/list of 2 ints, (Default value = (1,1))</span>
-<span class="sd">        Specifies the strides of the convolution.</span>
-<span class="sd">    padding : int or tuple/list of 2 ints, (Default value = (0,0))</span>
-<span class="sd">        If padding is non-zero, then the input is implicitly zero-padded</span>
-<span class="sd">        on both sides for padding number of points.</span>
-<span class="sd">    dilation : int or tuple/list of 2 ints, (Default value = (1,1))</span>
-<span class="sd">        Specifies the dilation rate to use for dilated convolution.</span>
-<span class="sd">    groups : int, (Default value = 1)</span>
-<span class="sd">        Controls the connections between inputs and outputs.</span>
-<span class="sd">        At groups=1, all inputs are convolved to all outputs.</span>
-<span class="sd">        At groups=2, the operation becomes equivalent to having two convolution</span>
-<span class="sd">        layers side by side, each seeing half the input channels, and producing</span>
-<span class="sd">        half the output channels, and both subsequently concatenated.</span>
-<span class="sd">    num_deformable_group : int, (Default value = 1)</span>
-<span class="sd">        Number of deformable group partitions.</span>
-<span class="sd">    layout : str, (Default value = NCHW)</span>
-<span class="sd">        Dimension ordering of data and weight. Can be &#39;NCW&#39;, &#39;NWC&#39;, &#39;NCHW&#39;,</span>
-<span class="sd">        &#39;NHWC&#39;, &#39;NCDHW&#39;, &#39;NDHWC&#39;, etc. &#39;N&#39;, &#39;C&#39;, &#39;H&#39;, &#39;W&#39;, &#39;D&#39; stands for</span>
-<span class="sd">        batch, channel, height, width and depth dimensions respectively.</span>
-<span class="sd">        Convolution is performed over &#39;D&#39;, &#39;H&#39;, and &#39;W&#39; dimensions.</span>
-<span class="sd">    use_bias : bool, (Default value = True)</span>
-<span class="sd">        Whether the layer for generating the output features uses a bias vector.</span>
-<span class="sd">    in_channels : int, (Default value = 0)</span>
-<span class="sd">        The number of input channels to this layer. If not specified,</span>
-<span class="sd">        initialization will be deferred to the first time `forward` is called</span>
-<span class="sd">        and input channels will be inferred from the shape of input data.</span>
-<span class="sd">    activation : str, (Default value = None)</span>
-<span class="sd">        Activation function to use. See :func:`~mxnet.ndarray.Activation`.</span>
-<span class="sd">        If you don&#39;t specify anything, no activation is applied</span>
-<span class="sd">        (ie. &quot;linear&quot; activation: `a(x) = x`).</span>
-<span class="sd">    weight_initializer : str or `Initializer`, (Default value = None)</span>
-<span class="sd">        Initializer for the `weight` weights matrix for the convolution layer</span>
-<span class="sd">        for generating the output features.</span>
-<span class="sd">    bias_initializer : str or `Initializer`, (Default value = zeros)</span>
-<span class="sd">        Initializer for the bias vector for the convolution layer</span>
-<span class="sd">        for generating the output features.</span>
-<span class="sd">    offset_weight_initializer : str or `Initializer`, (Default value = zeros)</span>
-<span class="sd">        Initializer for the `weight` weights matrix for the convolution layer</span>
-<span class="sd">        for generating the offset.</span>
-<span class="sd">    offset_bias_initializer : str or `Initializer`, (Default value = zeros),</span>
-<span class="sd">        Initializer for the bias vector for the convolution layer</span>
-<span class="sd">        for generating the offset.</span>
-<span class="sd">    offset_use_bias: bool, (Default value = True)</span>
-<span class="sd">        Whether the layer for generating the offset uses a bias vector.</span>
-
-<span class="sd">    Inputs:</span>
-<span class="sd">        - **data**: 4D input tensor with shape</span>
-<span class="sd">          `(batch_size, in_channels, height, width)` when `layout` is `NCHW`.</span>
-<span class="sd">          For other layouts shape is permuted accordingly.</span>
-
-<span class="sd">    Outputs:</span>
-<span class="sd">        - **out**: 4D output tensor with shape</span>
-<span class="sd">          `(batch_size, channels, out_height, out_width)` when `layout` is `NCHW`.</span>
-<span class="sd">          out_height and out_width are calculated as::</span>
-
-<span class="sd">              out_height = floor((height+2*padding[0]-dilation[0]*(kernel_size[0]-1)-1)/stride[0])+1</span>
-<span class="sd">              out_width = floor((width+2*padding[1]-dilation[1]*(kernel_size[1]-1)-1)/stride[1])+1</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-
-    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">strides</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">padding</span><span class="o">=</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">),</span> <span class="n">dilation</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">),</span> <span class="n">groups</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span>
-                 <span class="n">num_deformable_group</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">layout</span><span class="o">=</span><span class="s1">&#39;NCHW&#39;</span><span class="p">,</span> <span class="n">use_bias</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">in_channels</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">activation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
-                 <span class="n">weight_initializer</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">bias_initializer</span><span class="o">=</span><span class="s1">&#39;zeros&#39;</span><span class="p">,</span>
-                 <span class="n">offset_weight_initializer</span><span class="o">=</span><span class="s1">&#39;zeros&#39;</span><span class="p">,</span> <span class="n">offset_bias_initializer</span><span class="o">=</span><span class="s1">&#39;zeros&#39;</span><span class="p">,</span> <span class="n">offset_use_bias</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
-                 <span class="n">op_name</span><span class="o">=</span><span class="s1">&#39;ModulatedDeformableConvolution&#39;</span><span class="p">,</span> <span class="n">adj</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
-        <span class="nb">super</span><span class="p">(</span><span class="n">ModulatedDeformableConvolution</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_channels</span> <span class="o">=</span> <span class="n">channels</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_in_channels</span> <span class="o">=</span> <span class="n">in_channels</span>
-
-        <span class="k">assert</span> <span class="n">layout</span> <span class="ow">in</span> <span class="p">(</span><span class="s1">&#39;NCHW&#39;</span><span class="p">,</span> <span class="s1">&#39;NHWC&#39;</span><span class="p">),</span> <span class="s2">&quot;Only supports &#39;NCHW&#39; and &#39;NHWC&#39; layout for now&quot;</span>
-        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span>
-            <span class="n">kernel_size</span> <span class="o">=</span> <span class="p">(</span><span class="n">kernel_size</span><span class="p">,)</span> <span class="o">*</span> <span class="mi">2</span>
-        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">strides</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span>
-            <span class="n">strides</span> <span class="o">=</span> <span class="p">(</span><span class="n">strides</span><span class="p">,)</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">)</span>
-        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">padding</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span>
-            <span class="n">padding</span> <span class="o">=</span> <span class="p">(</span><span class="n">padding</span><span class="p">,)</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">)</span>
-        <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">dilation</span><span class="p">,</span> <span class="n">numeric_types</span><span class="p">):</span>
-            <span class="n">dilation</span> <span class="o">=</span> <span class="p">(</span><span class="n">dilation</span><span class="p">,)</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">)</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_op_name</span> <span class="o">=</span> <span class="n">op_name</span>
-
-        <span class="n">offset_channels</span> <span class="o">=</span> <span class="n">num_deformable_group</span> <span class="o">*</span> <span class="mi">3</span> <span class="o">*</span> <span class="n">kernel_size</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">kernel_size</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">offset_split_index</span> <span class="o">=</span> <span class="n">num_deformable_group</span> <span class="o">*</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">kernel_size</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">kernel_size</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_offset</span> <span class="o">=</span> <span class="p">{</span>
-            <span class="s1">&#39;kernel&#39;</span><span class="p">:</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="s1">&#39;stride&#39;</span><span class="p">:</span> <span class="n">strides</span><span class="p">,</span> <span class="s1">&#39;dilate&#39;</span><span class="p">:</span> <span class="n">dilation</span><span class="p">,</span>
-            <span class="s1">&#39;pad&#39;</span><span class="p">:</span> <span class="n">padding</span><span class="p">,</span> <span class="s1">&#39;num_filter&#39;</span><span class="p">:</span> <span class="n">offset_channels</span><span class="p">,</span> <span class="s1">&#39;num_group&#39;</span><span class="p">:</span> <span class="n">groups</span><span class="p">,</span>
-            <span class="s1">&#39;no_bias&#39;</span><span class="p">:</span> <span class="ow">not</span> <span class="n">offset_use_bias</span><span class="p">,</span> <span class="s1">&#39;layout&#39;</span><span class="p">:</span> <span class="n">layout</span><span class="p">}</span>
-
-        <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span> <span class="o">=</span> <span class="p">{</span>
-            <span class="s1">&#39;kernel&#39;</span><span class="p">:</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="s1">&#39;stride&#39;</span><span class="p">:</span> <span class="n">strides</span><span class="p">,</span> <span class="s1">&#39;dilate&#39;</span><span class="p">:</span> <span class="n">dilation</span><span class="p">,</span>
-            <span class="s1">&#39;pad&#39;</span><span class="p">:</span> <span class="n">padding</span><span class="p">,</span> <span class="s1">&#39;num_filter&#39;</span><span class="p">:</span> <span class="n">channels</span><span class="p">,</span> <span class="s1">&#39;num_group&#39;</span><span class="p">:</span> <span class="n">groups</span><span class="p">,</span>
-            <span class="s1">&#39;num_deformable_group&#39;</span><span class="p">:</span> <span class="n">num_deformable_group</span><span class="p">,</span>
-            <span class="s1">&#39;no_bias&#39;</span><span class="p">:</span> <span class="ow">not</span> <span class="n">use_bias</span><span class="p">,</span> <span class="s1">&#39;layout&#39;</span><span class="p">:</span> <span class="n">layout</span><span class="p">}</span>
-
-        <span class="k">if</span> <span class="n">adj</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_offset</span><span class="p">[</span><span class="s1">&#39;adj&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">adj</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span><span class="p">[</span><span class="s1">&#39;adj&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">adj</span>
-
-        <span class="n">deformable_conv_weight_shape</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">)</span> <span class="o">+</span> <span class="mi">2</span><span class="p">)</span>
-        <span class="n">deformable_conv_weight_shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">channels</span>
-        <span class="n">deformable_conv_weight_shape</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">=</span> <span class="n">kernel_size</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
-        <span class="n">deformable_conv_weight_shape</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span> <span class="o">=</span> <span class="n">kernel_size</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
-
-        <span class="bp">self</span><span class="o">.</span><span class="n">deformable_conv_weight</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="s1">&#39;deformable_conv_weight&#39;</span><span class="p">,</span>
-                                                <span class="n">shape</span><span class="o">=</span><span class="n">deformable_conv_weight_shape</span><span class="p">,</span>
-                                                <span class="n">init</span><span class="o">=</span><span class="n">weight_initializer</span><span class="p">,</span>
-                                                <span class="n">allow_deferred_init</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-
-        <span class="k">if</span> <span class="n">use_bias</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">deformable_conv_bias</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="s1">&#39;deformable_conv_bias&#39;</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="p">(</span><span class="n">channels</span><span class="p">,),</span>
-                                                  <span class="n">init</span><span class="o">=</span><span class="n">bias_initializer</span><span class="p">,</span>
-                                                  <span class="n">allow_deferred_init</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">deformable_conv_bias</span> <span class="o">=</span> <span class="kc">None</span>
-
-        <span class="n">dshape</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">kernel_size</span><span class="p">)</span> <span class="o">+</span> <span class="mi">2</span><span class="p">)</span>
-        <span class="n">dshape</span><span class="p">[</span><span class="n">layout</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;N&#39;</span><span class="p">)]</span> <span class="o">=</span> <span class="mi">1</span>
-        <span class="n">dshape</span><span class="p">[</span><span class="n">layout</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;C&#39;</span><span class="p">)]</span> <span class="o">=</span> <span class="n">in_channels</span>
-
-        <span class="n">op</span> <span class="o">=</span> <span class="nb">getattr</span><span class="p">(</span><span class="n">symbol</span><span class="p">,</span> <span class="s1">&#39;Convolution&#39;</span><span class="p">)</span>
-        <span class="n">offset</span> <span class="o">=</span> <span class="n">op</span><span class="p">(</span><span class="n">symbol</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="s1">&#39;data&#39;</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="n">dshape</span><span class="p">),</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_offset</span><span class="p">)</span>
-
-        <span class="n">offsetshapes</span> <span class="o">=</span> <span class="n">offset</span><span class="o">.</span><span class="n">infer_shape_partial</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span>
-
-        <span class="bp">self</span><span class="o">.</span><span class="n">offset_weight</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="s1">&#39;offset_weight&#39;</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="n">offsetshapes</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span>
-                                       <span class="n">init</span><span class="o">=</span><span class="n">offset_weight_initializer</span><span class="p">,</span>
-                                       <span class="n">allow_deferred_init</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-
-        <span class="k">if</span> <span class="n">offset_use_bias</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">offset_bias</span> <span class="o">=</span> <span class="n">Parameter</span><span class="p">(</span><span class="s1">&#39;offset_bias&#39;</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="n">offsetshapes</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span>
-                                         <span class="n">init</span><span class="o">=</span><span class="n">offset_bias_initializer</span><span class="p">,</span>
-                                         <span class="n">allow_deferred_init</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">offset_bias</span> <span class="o">=</span> <span class="kc">None</span>
-
-        <span class="k">if</span> <span class="n">activation</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">act</span> <span class="o">=</span> <span class="n">Activation</span><span class="p">(</span><span class="n">activation</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">act</span> <span class="o">=</span> <span class="kc">None</span>
-
-<div class="viewcode-block" id="ModulatedDeformableConvolution.hybrid_forward"><a class="viewcode-back" href="../../../../../api/gluon/contrib/index.html#mxnet.gluon.contrib.cnn.ModulatedDeformableConvolution.hybrid_forward">[docs]</a>    <span class="k">def</span> <span class="nf">hybrid_forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">F</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">offset_weight</span><span class="p">,</span> <span class="n">deformable_conv_weight</span><span class="p">,</span> <span class="n">offset_bias</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">deformable_conv_bias</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
-        <span class="k">if</span> <span class="n">offset_bias</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">offset</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">Convolution</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">offset_weight</span><span class="p">,</span> <span class="n">cudnn_off</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_offset</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="n">offset</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">Convolution</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">offset_weight</span><span class="p">,</span> <span class="n">offset_bias</span><span class="p">,</span> <span class="n">cudnn_off</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_offset</span><span class="p">)</span>
-
-        <span class="n">offset_t</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">slice_axis</span><span class="p">(</span><span class="n">offset</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">begin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">offset_split_index</span><span class="p">)</span>
-        <span class="n">mask</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">slice_axis</span><span class="p">(</span><span class="n">offset</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">begin</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">offset_split_index</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span>
-        <span class="n">mask</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">sigmoid</span><span class="p">(</span><span class="n">mask</span><span class="p">)</span> <span class="o">*</span> <span class="mi">2</span>
-
-        <span class="k">if</span> <span class="n">deformable_conv_bias</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">act</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">ModulatedDeformableConvolution</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">x</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="n">offset_t</span><span class="p">,</span> <span class="n">mask</span><span class="o">=</span><span class="n">mask</span><span class="p">,</span>
-                                                           <span class="n">weight</span><span class="o">=</span><span class="n">deformable_conv_weight</span><span class="p">,</span>
-                                                           <span class="n">name</span><span class="o">=</span><span class="s1">&#39;fwd&#39;</span><span class="p">,</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span><span class="p">)</span>
-        <span class="k">else</span><span class="p">:</span>
-            <span class="n">act</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">contrib</span><span class="o">.</span><span class="n">ModulatedDeformableConvolution</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">x</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="n">offset_t</span><span class="p">,</span> <span class="n">mask</span><span class="o">=</span><span class="n">mask</span><span class="p">,</span>
-                                                           <span class="n">weight</span><span class="o">=</span><span class="n">deformable_conv_weight</span><span class="p">,</span>
-                                                           <span class="n">bias</span><span class="o">=</span><span class="n">deformable_conv_bias</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">&#39;fwd&#39;</span><span class="p">,</span>
-                                                           <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">_kwargs_deformable_conv</span><span class="p">)</span>
-
-        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">act</span><span class="p">:</span>
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-  <h1>Source code for mxnet.gluon.contrib.data.sampler</h1><div class="highlight"><pre>
-<span></span><span class="c1"># Licensed to the Apache Software Foundation (ASF) under one</span>
-<span class="c1"># or more contributor license agreements.  See the NOTICE file</span>
-<span class="c1"># distributed with this work for additional information</span>
-<span class="c1"># regarding copyright ownership.  The ASF licenses this file</span>
-<span class="c1"># to you under the Apache License, Version 2.0 (the</span>
-<span class="c1"># &quot;License&quot;); you may not use this file except in compliance</span>
-<span class="c1"># with the License.  You may obtain a copy of the License at</span>
-<span class="c1">#</span>
-<span class="c1">#   http://www.apache.org/licenses/LICENSE-2.0</span>
-<span class="c1">#</span>
-<span class="c1"># Unless required by applicable law or agreed to in writing,</span>
-<span class="c1"># software distributed under the License is distributed on an</span>
-<span class="c1"># &quot;AS IS&quot; BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY</span>
-<span class="c1"># KIND, either express or implied.  See the License for the</span>
-<span class="c1"># specific language governing permissions and limitations</span>
-<span class="c1"># under the License.</span>
-
-<span class="c1"># coding: utf-8</span>
-<span class="c1"># pylint: disable=</span>
-<span class="sd">&quot;&quot;&quot;Dataset sampler.&quot;&quot;&quot;</span>
-<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;IntervalSampler&#39;</span><span class="p">]</span>
-
-<span class="kn">from</span> <span class="nn">...data</span> <span class="kn">import</span> <span class="n">sampler</span>
-
-<div class="viewcode-block" id="IntervalSampler"><a class="viewcode-back" href="../../../../../api/gluon/contrib/index.html#mxnet.gluon.contrib.data.sampler.IntervalSampler">[docs]</a><span class="k">class</span> <span class="nc">IntervalSampler</span><span class="p">(</span><span class="n">sampler</span><span class="o">.</span><span class="n">Sampler</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;Samples elements from [0, length) at fixed intervals.</span>
-
-<span class="sd">    Parameters</span>
-<span class="sd">    ----------</span>
-<span class="sd">    length : int</span>
-<span class="sd">        Length of the sequence.</span>
-<span class="sd">    interval : int</span>
-<span class="sd">        The number of items to skip between two samples.</span>
-<span class="sd">    rollover : bool, default True</span>
-<span class="sd">        Whether to start again from the first skipped item after reaching the end.</span>
-<span class="sd">        If true, this sampler would start again from the first skipped item until all items</span>
-<span class="sd">        are visited.</span>
-<span class="sd">        Otherwise, iteration stops when end is reached and skipped items are ignored.</span>
-
-<span class="sd">    Examples</span>
-<span class="sd">    --------</span>
-<span class="sd">    &gt;&gt;&gt; sampler = contrib.data.IntervalSampler(13, interval=3)</span>
-<span class="sd">    &gt;&gt;&gt; list(sampler)</span>
-<span class="sd">    [0, 3, 6, 9, 12, 1, 4, 7, 10, 2, 5, 8, 11]</span>
-<span class="sd">    &gt;&gt;&gt; sampler = contrib.data.IntervalSampler(13, interval=3, rollover=False)</span>
-<span class="sd">    &gt;&gt;&gt; list(sampler)</span>
-<span class="sd">    [0, 3, 6, 9, 12]</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">length</span><span class="p">,</span> <span class="n">interval</span><span class="p">,</span> <span class="n">rollover</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
-        <span class="k">assert</span> <span class="n">interval</span> <span class="o">&lt;=</span> <span class="n">length</span><span class="p">,</span> \
-            <span class="s2">&quot;Interval </span><span class="si">{}</span><span class="s2"> must be smaller than or equal to length </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">interval</span><span class="p">,</span> <span class="n">length</span><span class="p">)</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_length</span> <span class="o">=</span> <span class="n">length</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_interval</span> <span class="o">=</span> <span class="n">interval</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">_rollover</span> <span class="o">=</span> <span class="n">rollover</span>
-
-    <span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_interval</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rollover</span> <span class="k">else</span> <span class="mi">1</span><span class="p">):</span>
-            <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_length</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_interval</span><span class="p">):</span>
-                <span class="k">yield</span> <span class="n">j</span>
-
-    <span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
-        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_length</span></div>
-</pre></div>
-
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