[GitHub] eric-haibin-lin closed pull request #51: Fixed scala namespace links

Thu, 01 Feb 2018 11:44:54 -0800 

eric-haibin-lin closed pull request #51: Fixed scala namespace links
URL: https://github.com/apache/incubator-mxnet-site/pull/51
 
 
   

This is a PR merged from a forked repository.
As GitHub hides the original diff on merge, it is displayed below for
the sake of provenance:

As this is a foreign pull request (from a fork), the diff is supplied
below (as it won't show otherwise due to GitHub magic):

diff --git a/api/scala/index.html b/api/scala/index.html
index 8e53b9ea..97b66a51 100644
--- a/api/scala/index.html
+++ b/api/scala/index.html
@@ -206,8 +206,8 @@ <h1 id="logo-wrap">
 <li class="toctree-l2"><a class="reference internal" 
href="#resources">Resources</a><ul>
 <li class="toctree-l3"><a class="reference external" 
href="https://mxnet.incubator.apache.org/api/scala/docs/index.html";>MXNet Scala 
API Documentation</a></li>
 <li class="toctree-l3"><a class="reference external" 
href="https://mxnet.incubator.apache.org/tutorials/scala/mnist.html";>Handwritten
 Digit Classification in Scala</a></li>
-<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
-<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples";>More
 Scala Examples</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples";>More
 Scala Examples</a></li>
 </ul>
 </li>
 </ul>
@@ -264,8 +264,8 @@ <h1 id="logo-wrap">
 <ul>
 <li class="toctree-l1"><a class="reference external" 
href="https://mxnet.incubator.apache.org/api/scala/docs/index.html";>MXNet Scala 
API Documentation</a></li>
 <li class="toctree-l1"><a class="reference external" 
href="https://mxnet.incubator.apache.org/tutorials/scala/mnist.html";>Handwritten
 Digit Classification in Scala</a></li>
-<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
-<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples";>More
 Scala Examples</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples";>More
 Scala Examples</a></li>
 </ul>
 </div>
 </div>
diff --git a/versions/0.11.0/api/scala/index.html 
b/versions/0.11.0/api/scala/index.html
index e66d2878..6f45666b 100644
--- a/versions/0.11.0/api/scala/index.html
+++ b/versions/0.11.0/api/scala/index.html
@@ -162,8 +162,8 @@ <h1 id="logo-wrap">
 <li class="toctree-l2"><a class="reference internal" 
href="#resources">Resources</a><ul>
 <li class="toctree-l3"><a class="reference external" 
href="https://mxnet.incubator.apache.org/api/scala/docs/index.html";>MXNet Scala 
API Documentation</a></li>
 <li class="toctree-l3"><a class="reference external" 
href="https://mxnet.incubator.apache.org/tutorials/scala/mnist.html";>Handwritten
 Digit Classification in Scala</a></li>
-<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
-<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples";>More
 Scala Examples</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples";>More
 Scala Examples</a></li>
 </ul>
 </li>
 </ul>
@@ -216,8 +216,8 @@ <h1 id="logo-wrap">
 <ul>
 <li class="toctree-l1"><a class="reference external" 
href="https://mxnet.incubator.apache.org/api/scala/docs/index.html";>MXNet Scala 
API Documentation</a></li>
 <li class="toctree-l1"><a class="reference external" 
href="https://mxnet.incubator.apache.org/tutorials/scala/mnist.html";>Handwritten
 Digit Classification in Scala</a></li>
-<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
-<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples";>More
 Scala Examples</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples";>More
 Scala Examples</a></li>
 </ul>
 </div>
 </div>
diff --git a/versions/0.12.0/api/scala/index.html 
b/versions/0.12.0/api/scala/index.html
index d117a92a..88d05831 100644
--- a/versions/0.12.0/api/scala/index.html
+++ b/versions/0.12.0/api/scala/index.html
@@ -206,8 +206,8 @@ <h1 id="logo-wrap">
 <li class="toctree-l2"><a class="reference internal" 
href="#resources">Resources</a><ul>
 <li class="toctree-l3"><a class="reference external" 
href="https://mxnet.incubator.apache.org/api/scala/docs/index.html";>MXNet Scala 
API Documentation</a></li>
 <li class="toctree-l3"><a class="reference external" 
href="https://mxnet.incubator.apache.org/tutorials/scala/mnist.html";>Handwritten
 Digit Classification in Scala</a></li>
-<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
-<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples";>More
 Scala Examples</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples";>More
 Scala Examples</a></li>
 </ul>
 </li>
 </ul>
@@ -264,8 +264,8 @@ <h1 id="logo-wrap">
 <ul>
 <li class="toctree-l1"><a class="reference external" 
href="https://mxnet.incubator.apache.org/api/scala/docs/index.html";>MXNet Scala 
API Documentation</a></li>
 <li class="toctree-l1"><a class="reference external" 
href="https://mxnet.incubator.apache.org/tutorials/scala/mnist.html";>Handwritten
 Digit Classification in Scala</a></li>
-<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
-<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples";>More
 Scala Examples</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples";>More
 Scala Examples</a></li>
 </ul>
 </div>
 </div>
diff --git a/versions/0.12.1/api/scala/index.html 
b/versions/0.12.1/api/scala/index.html
index c69350ee..7d901051 100644
--- a/versions/0.12.1/api/scala/index.html
+++ b/versions/0.12.1/api/scala/index.html
@@ -206,8 +206,8 @@ <h1 id="logo-wrap">
 <li class="toctree-l2"><a class="reference internal" 
href="#resources">Resources</a><ul>
 <li class="toctree-l3"><a class="reference external" 
href="https://mxnet.incubator.apache.org/api/scala/docs/index.html";>MXNet Scala 
API Documentation</a></li>
 <li class="toctree-l3"><a class="reference external" 
href="https://mxnet.incubator.apache.org/tutorials/scala/mnist.html";>Handwritten
 Digit Classification in Scala</a></li>
-<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
-<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples";>More
 Scala Examples</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples";>More
 Scala Examples</a></li>
 </ul>
 </li>
 </ul>
@@ -264,8 +264,8 @@ <h1 id="logo-wrap">
 <ul>
 <li class="toctree-l1"><a class="reference external" 
href="https://mxnet.incubator.apache.org/api/scala/docs/index.html";>MXNet Scala 
API Documentation</a></li>
 <li class="toctree-l1"><a class="reference external" 
href="https://mxnet.incubator.apache.org/tutorials/scala/mnist.html";>Handwritten
 Digit Classification in Scala</a></li>
-<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
-<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples";>More
 Scala Examples</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples";>More
 Scala Examples</a></li>
 </ul>
 </div>
 </div>
diff --git a/versions/0.12.1/tutorials/scala/char_lstm.html 
b/versions/0.12.1/tutorials/scala/char_lstm.html
index 55c79aa9..00761a92 100644
--- a/versions/0.12.1/tutorials/scala/char_lstm.html
+++ b/versions/0.12.1/tutorials/scala/char_lstm.html
@@ -218,7 +218,7 @@ <h1 id="logo-wrap">
 <ol class="simple">
 <li>Run it by copying the provided code snippets and pasting them into the 
Scala command line, making the appropriate changes to the input file path.</li>
 <li>Reuse the code by making changes to relevant parameters and running it 
from command line.</li>
-<li><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnet/examples/rnn";>Run
 the source code directly</a> by running the <a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/scripts/rnn";>provided
 scripts</a>.</li>
+<li><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/rnn";>Run
 the source code directly</a> by running the <a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/scripts/rnn";>provided
 scripts</a>.</li>
 </ol>
 <p>To run the scripts:</p>
 <ul class="simple">
@@ -375,7 +375,7 @@ <h1 id="logo-wrap">
 <code class="docutils literal"><span class="pre">Lstm.scala</span></code> 
contains the definition of the LSTM cell. <code class="docutils literal"><span 
class="pre">BucketIo.scala</span></code> creates a sentence iterator. <code 
class="docutils literal"><span class="pre">RnnModel.scala</span></code> is used 
for model inference. The helper files are available on the <a class="reference 
external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/rnn";>MXNet
 site</a>.
 To load them, at the Scala command prompt type:</li>
 </ol>
-<div class="highlight-scala"><div class="highlight"><pre><span></span>        
<span class="n">scala</span><span class="o">></span> <span 
class="k">:</span><span class="kt">load</span> <span 
class="kt">../../../scala-package/examples/src/main/scala/ml/dmlc/mxnet/examples/rnn/Lstm.scala</span>
+<div class="highlight-scala"><div class="highlight"><pre><span></span>        
<span class="n">scala</span><span class="o">></span> <span 
class="k">:</span><span class="kt">load</span> <span 
class="kt">../../../scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/rnn/Lstm.scala</span>
         <span class="n">scala</span><span class="o">></span> <span 
class="k">:</span><span class="kt">load</span> <span 
class="kt">../../../scala-package/examples/src/main/scala/ml/dmlc/mxnet/examples/rnn/BucketIo.scala</span>
         <span class="n">scala</span><span class="o">></span> <span 
class="k">:</span><span class="kt">load</span> <span 
class="kt">../../../scala-package/examples/src/main/scala/ml/dmlc/mxnet/examples/rnn/RnnModel.scala</span>
 </pre></div>
diff --git a/versions/master/_sources/faq/model_parallel_lstm.txt 
b/versions/master/_sources/faq/model_parallel_lstm.txt
index 1e367eb5..c4de7799 100644
--- a/versions/master/_sources/faq/model_parallel_lstm.txt
+++ b/versions/master/_sources/faq/model_parallel_lstm.txt
@@ -12,7 +12,7 @@ powerful heterogeneous hardware environments to achieve 
significant speedups.
 
 There are two primary ways that we can spread a workload across multiple 
devices.
 In a previous document, [we addressed data parallelism](./multi_devices.md),
-an approach in which samples within a batch are divided among the available 
devices.
+an approach in which examples within a batch are divvied among the available 
devices.
 With data parallelism, each device stores a complete copy of the model.
 Here, we explore _model parallelism_, a different approach.
 Instead of splitting the batch among the devices, we partition the model 
itself.
@@ -25,7 +25,7 @@ for [natural language 
translation](https://arxiv.org/pdf/1409.0473.pdf), [speech
 and working with [time series data](https://arxiv.org/abs/1511.03677).
 For a general high-level introduction to LSTMs,
 see the excellent 
[tutorial](http://colah.github.io/posts/2015-08-Understanding-LSTMs/) by 
Christopher Olah. For a working example of LSTM training with model parallelism,
-see 
[example/model-parallelism-lstm/](https://github.com/dmlc/mxnet/blob/master/example/model-parallel/lstm/lstm.py).
+see 
[example/model-parallelism-lstm/](https://github.com/dmlc/mxnet/blob/master/example/model-parallel-lstm/lstm.py).
 
 
 ## Model Parallelism: Using Multiple GPUs As a Pipeline
@@ -44,7 +44,7 @@ This differs significantly from data parallelism.
 Here, there is no contention to update the shared model at the end of each 
iteration,
 and most of the communication happens when passing intermediate results 
between GPUs.
 
-In the current implementation, the layers are defined in 
[lstm_unroll()](https://github.com/dmlc/mxnet/blob/master/example/model-parallel/lstm/lstm.py).
+In the current implementation, the layers are defined in 
[lstm_unroll()](https://github.com/dmlc/mxnet/blob/master/example/model-parallel-lstm/lstm.py).
 
 ## Workload Partitioning
 
@@ -65,15 +65,15 @@ Although the LSTM layers consume less memory than the 
decoder/encoder layers, th
 Thus, the partition on the left will be faster than the one on the right
 because the workload is more evenly distributed.
 
-Currently, the layer partition is implemented in 
[lstm.py](https://github.com/apache/incubator-mxnet/blob/master/example/model-parallel/lstm/lstm.py#L171)
 and configured in 
[lstm_ptb.py](https://github.com/apache/incubator-mxnet/blob/master/example/model-parallel/lstm/lstm_ptb.py#L97-L102)
 using the `group2ctx` option.
+Currently, the layer partition is implemented in 
[lstm.py](https://github.com/eric-haibin-lin/mxnet/blob/master/example/model-parallel-lstm/lstm.py#L187)
 and configured in 
[lstm_ptb.py](https://github.com/eric-haibin-lin/mxnet/blob/master/example/model-parallel-lstm/lstm.py#L187)
 using the `group2ctx` option.
 
 ## Apply Bucketing to Model Parallelism
 
 To achieve model parallelism while using bucketing,
 you need to unroll an LSTM model for each bucket
 to obtain an executor for each.
-For details about how the model is bound, see 
[lstm.py](https://github.com/apache/incubator-mxnet/blob/master/example/model-parallel/lstm/lstm.py#L225-L235).
+For details about how the model is bound, see 
[lstm.py](https://github.com/eric-haibin-lin/mxnet/blob/master/example/model-parallel-lstm/lstm.py#L154).
 
 On the other hand, because model parallelism partitions the model/layers,
 the input data has to be transformed/transposed to the agreed shape.
-For more details, see 
[bucket_io](https://github.com/apache/incubator-mxnet/blob/master/example/rnn/old/bucket_io.py).
+For more details, see 
[bucket_io](https://github.com/eric-haibin-lin/mxnet/blob/master/example/model-parallel-lstm/lstm.py#L154).
diff --git a/versions/master/_sources/faq/new_op.txt 
b/versions/master/_sources/faq/new_op.txt
index 994a2a6f..55b7409c 100644
--- a/versions/master/_sources/faq/new_op.txt
+++ b/versions/master/_sources/faq/new_op.txt
@@ -339,7 +339,7 @@ NNVM_REGISTER_OP(_backward_abs)
 [](const NodeAttrs& attrs){
   return std::vector<std::pair<int, int> >{{0, 0}, {1, 0}};
 })
-.set_attr<FCompute>("FCompute<cpu>", BinaryCompute<cpu, 
backward_grad<mshadow_op::sign> >);
+.set_attr<FCompute>("FCompute<cpu>", BinaryCompute<cpu, 
unary_bwd<mshadow_op::sign> >);
 ```
 
 ### Legacy Operators
diff --git a/versions/master/api/scala/index.html 
b/versions/master/api/scala/index.html
index f7e77c80..a7e941f8 100644
--- a/versions/master/api/scala/index.html
+++ b/versions/master/api/scala/index.html
@@ -52,7 +52,7 @@
 <link href="../c++/index.html" rel="prev" title="MXNet - C++ API"/>
 <link 
href="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-icon.png";
 rel="icon" type="image/png"/>
 </link></link></link></head>
-<body 
background="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-background.png";
 role="document">
+<body 
background="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-background-compressed.jpeg";
 role="document">
 <div class="content-block"><div class="navbar navbar-fixed-top">
 <div class="container" id="navContainer">
 <div class="innder" id="header-inner">
@@ -61,7 +61,6 @@ <h1 id="logo-wrap">
 </h1>
 <nav class="nav-bar" id="main-nav">
 <a class="main-nav-link" href="../../install/index.html">Install</a>
-<a class="main-nav-link" href="../../tutorials/index.html">Tutorials</a>
 <span id="dropdown-menu-position-anchor">
 <a aria-expanded="true" aria-haspopup="true" class="main-nav-link 
dropdown-toggle" data-toggle="dropdown" href="#" role="button">Gluon <span 
class="caret"></span></a>
 <ul class="dropdown-menu navbar-menu" id="package-dropdown-menu">
@@ -83,11 +82,12 @@ <h1 id="logo-wrap">
 <span id="dropdown-menu-position-anchor-docs">
 <a aria-expanded="true" aria-haspopup="true" class="main-nav-link 
dropdown-toggle" data-toggle="dropdown" href="#" role="button">Docs <span 
class="caret"></span></a>
 <ul class="dropdown-menu navbar-menu" id="package-dropdown-menu-docs">
+<li><a class="main-nav-link" href="../../tutorials/index.html">Tutorials</a>
 <li><a class="main-nav-link" href="../../faq/index.html">FAQ</a></li>
 <li><a class="main-nav-link" 
href="../../architecture/index.html">Architecture</a></li>
 <li><a class="main-nav-link" 
href="https://github.com/apache/incubator-mxnet/tree/master/example";>Examples</a></li>
 <li><a class="main-nav-link" href="../../model_zoo/index.html">Model 
Zoo</a></li>
-</ul>
+</li></ul>
 </span>
 <a class="main-nav-link" href="https://github.com/dmlc/mxnet";>Github</a>
 <span id="dropdown-menu-position-anchor-community">
@@ -96,9 +96,9 @@ <h1 id="logo-wrap">
 <li><a class="main-nav-link" 
href="../../community/index.html">Community</a></li>
 <li><a class="main-nav-link" 
href="../../community/contribute.html">Contribute</a></li>
 <li><a class="main-nav-link" href="../../community/powered_by.html">Powered 
By</a></li>
+<li><a class="main-nav-link" href="http://discuss.mxnet.io";>Discuss</a></li>
 </ul>
 </span>
-<a class="main-nav-link" href="http://discuss.mxnet.io";>Discuss</a>
 <span id="dropdown-menu-position-anchor-version" style="position: relative"><a 
href="#" class="main-nav-link dropdown-toggle" data-toggle="dropdown" 
role="button" aria-haspopup="true" aria-expanded="true">Versions(master)<span 
class="caret"></span></a><ul id="package-dropdown-menu" 
class="dropdown-menu"><li><a class="main-nav-link" 
href=https://mxnet.incubator.apache.org/>1.0.0</a></li><li><a 
class="main-nav-link" 
href=https://mxnet.incubator.apache.org/versions/0.12.1/index.html>0.12.1</a></li><li><a
 class="main-nav-link" 
href=https://mxnet.incubator.apache.org/versions/0.12.0/index.html>0.12.0</a></li><li><a
 class="main-nav-link" 
href=https://mxnet.incubator.apache.org/versions/0.11.0/index.html>0.11.0</a></li><li><a
 class="main-nav-link" 
href=https://mxnet.incubator.apache.org/versions/master/index.html>master</a></li></ul></span></nav>
 <script> function getRootPath(){ return "../../" } </script>
 <div class="burgerIcon dropdown">
@@ -204,10 +204,10 @@ <h1 id="logo-wrap">
 </ul>
 </li>
 <li class="toctree-l2"><a class="reference internal" 
href="#resources">Resources</a><ul>
-<li class="toctree-l3"><a class="reference external" 
href="http://mxnet.incubator.apache.org/api/scala/docs/index.html";>MXNet Scala 
API Documentation</a></li>
-<li class="toctree-l3"><a class="reference external" 
href="http://mxnet.incubator.apache.org/tutorials/scala/mnist.html";>Handwritten 
Digit Classification in Scala</a></li>
-<li class="toctree-l3"><a class="reference external" 
href="https://github.com/apache/incubator-mxnet/blob/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
-<li class="toctree-l3"><a class="reference external" 
href="https://github.com/apache/incubator-mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples";>More
 Scala Examples</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://mxnet.incubator.apache.org/versions/master/api/scala/docs/index.html";>MXNet
 Scala API Documentation</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://mxnet.incubator.apache.org/versions/master/tutorials/scala/mnist.html";>Handwritten
 Digit Classification in Scala</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
+<li class="toctree-l3"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples";>More
 Scala Examples</a></li>
 </ul>
 </li>
 </ul>
@@ -224,25 +224,25 @@ <h1 id="logo-wrap">
 <div class="page-tracker"></div>
 <div class="section" id="mxnet-scala-api">
 <span id="mxnet-scala-api"></span><h1>MXNet - Scala API<a class="headerlink" 
href="#mxnet-scala-api" title="Permalink to this headline">?</a></h1>
-<p>See the <a class="reference external" 
href="http://mxnet.incubator.apache.org/api/scala/docs/index.html";>MXNet Scala 
API Documentation</a>.</p>
+<p>See the <a class="reference external" 
href="https://mxnet.incubator.apache.org/versions/master/api/scala/docs/index.html";>MXNet
 Scala API Documentation</a>.</p>
 <p>MXNet supports the Scala programming language. The MXNet Scala package 
brings flexible and efficient GPU
 computing and state-of-art deep learning to Scala. It enables you to write 
seamless tensor/matrix computation with multiple GPUs in Scala. It also lets 
you construct and customize the state-of-art deep learning models in Scala,
 and apply them to tasks, such as image classification and data science 
challenges.</p>
 <p>You can perform tensor or matrix computation in pure Scala:</p>
-<div class="highlight-scala"><div class="highlight"><pre><span></span>   <span 
class="n">scala</span><span class="o">></span> <span class="k">import</span> 
<span class="nn">org.apache.mxnet._</span>
-   <span class="k">import</span> <span class="nn">org.apache.mxnet._</span>
+<div class="highlight-scala"><div class="highlight"><pre><span></span>   <span 
class="n">scala</span><span class="o">></span> <span class="k">import</span> 
<span class="nn">ml.dmlc.mxnet._</span>
+   <span class="k">import</span> <span class="nn">ml.dmlc.mxnet._</span>
 
    <span class="n">scala</span><span class="o">></span> <span 
class="k">val</span> <span class="n">arr</span> <span class="k">=</span> <span 
class="nc">NDArray</span><span class="o">.</span><span 
class="n">ones</span><span class="o">(</span><span class="mi">2</span><span 
class="o">,</span> <span class="mi">3</span><span class="o">)</span>
-   <span class="n">arr</span><span class="k">:</span> <span 
class="kt">org.apache.mxnet.NDArray</span> <span class="o">=</span> <span 
class="n">org</span><span class="o">.</span><span class="n">apache</span><span 
class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span 
class="nc">NDArray</span><span class="nd">@f5e74790</span>
+   <span class="n">arr</span><span class="k">:</span> <span 
class="kt">ml.dmlc.mxnet.NDArray</span> <span class="o">=</span> <span 
class="n">ml</span><span class="o">.</span><span class="n">dmlc</span><span 
class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span 
class="nc">NDArray</span><span class="nd">@f5e74790</span>
 
    <span class="n">scala</span><span class="o">></span> <span 
class="n">arr</span><span class="o">.</span><span class="n">shape</span>
-   <span class="n">res0</span><span class="k">:</span> <span 
class="kt">org.apache.mxnet.Shape</span> <span class="o">=</span> <span 
class="o">(</span><span class="mi">2</span><span class="o">,</span><span 
class="mi">3</span><span class="o">)</span>
+   <span class="n">res0</span><span class="k">:</span> <span 
class="kt">ml.dmlc.mxnet.Shape</span> <span class="o">=</span> <span 
class="o">(</span><span class="mi">2</span><span class="o">,</span><span 
class="mi">3</span><span class="o">)</span>
 
    <span class="n">scala</span><span class="o">></span> <span 
class="o">(</span><span class="n">arr</span> <span class="o">*</span> <span 
class="mi">2</span><span class="o">).</span><span class="n">toArray</span>
    <span class="n">res2</span><span class="k">:</span> <span 
class="kt">Array</span><span class="o">[</span><span 
class="kt">Float</span><span class="o">]</span> <span class="k">=</span> <span 
class="nc">Array</span><span class="o">(</span><span class="mf">2.0</span><span 
class="o">,</span> <span class="mf">2.0</span><span class="o">,</span> <span 
class="mf">2.0</span><span class="o">,</span> <span class="mf">2.0</span><span 
class="o">,</span> <span class="mf">2.0</span><span class="o">,</span> <span 
class="mf">2.0</span><span class="o">)</span>
 
    <span class="n">scala</span><span class="o">></span> <span 
class="o">(</span><span class="n">arr</span> <span class="o">*</span> <span 
class="mi">2</span><span class="o">).</span><span class="n">shape</span>
-   <span class="n">res3</span><span class="k">:</span> <span 
class="kt">org.apache.mxnet.Shape</span> <span class="o">=</span> <span 
class="o">(</span><span class="mi">2</span><span class="o">,</span><span 
class="mi">3</span><span class="o">)</span>
+   <span class="n">res3</span><span class="k">:</span> <span 
class="kt">ml.dmlc.mxnet.Shape</span> <span class="o">=</span> <span 
class="o">(</span><span class="mi">2</span><span class="o">,</span><span 
class="mi">3</span><span class="o">)</span>
 </pre></div>
 </div>
 <div class="section" id="scala-api-reference">
@@ -262,10 +262,10 @@ <h1 id="logo-wrap">
 <span id="resources"></span><h2>Resources<a class="headerlink" 
href="#resources" title="Permalink to this headline">?</a></h2>
 <div class="toctree-wrapper compound">
 <ul>
-<li class="toctree-l1"><a class="reference external" 
href="http://mxnet.incubator.apache.org/api/scala/docs/index.html";>MXNet Scala 
API Documentation</a></li>
-<li class="toctree-l1"><a class="reference external" 
href="http://mxnet.incubator.apache.org/tutorials/scala/mnist.html";>Handwritten 
Digit Classification in Scala</a></li>
-<li class="toctree-l1"><a class="reference external" 
href="https://github.com/apache/incubator-mxnet/blob/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
-<li class="toctree-l1"><a class="reference external" 
href="https://github.com/apache/incubator-mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples";>More
 Scala Examples</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://mxnet.incubator.apache.org/versions/master/api/scala/docs/index.html";>MXNet
 Scala API Documentation</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://mxnet.incubator.apache.org/versions/master/tutorials/scala/mnist.html";>Handwritten
 Digit Classification in Scala</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/neuralstyle/NeuralStyle.scala";>Neural
 Style in Scala on MXNet</a></li>
+<li class="toctree-l1"><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples";>More
 Scala Examples</a></li>
 </ul>
 </div>
 </div>
@@ -293,7 +293,7 @@ <h3><a href="../../index.html">Table Of Contents</a></h3>
             Apache MXNet is an effort undergoing incubation at The Apache 
Software Foundation (ASF), <strong>sponsored by the <i>Apache 
Incubator</i></strong>. 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, The Apache Software Foundation
+            "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 Apache 
Software Foundation."
         </p>
 </div>
diff --git a/versions/master/tutorials/scala/char_lstm.html 
b/versions/master/tutorials/scala/char_lstm.html
index 1ba82a4a..50f72091 100644
--- a/versions/master/tutorials/scala/char_lstm.html
+++ b/versions/master/tutorials/scala/char_lstm.html
@@ -50,7 +50,7 @@
 <!-- -->
 <link 
href="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-icon.png";
 rel="icon" type="image/png"/>
 </link></link></head>
-<body 
background="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-background.png";
 role="document">
+<body 
background="https://raw.githubusercontent.com/dmlc/web-data/master/mxnet/image/mxnet-background-compressed.jpeg";
 role="document">
 <div class="content-block"><div class="navbar navbar-fixed-top">
 <div class="container" id="navContainer">
 <div class="innder" id="header-inner">
@@ -59,7 +59,6 @@ <h1 id="logo-wrap">
 </h1>
 <nav class="nav-bar" id="main-nav">
 <a class="main-nav-link" href="../../install/index.html">Install</a>
-<a class="main-nav-link" href="../../tutorials/index.html">Tutorials</a>
 <span id="dropdown-menu-position-anchor">
 <a aria-expanded="true" aria-haspopup="true" class="main-nav-link 
dropdown-toggle" data-toggle="dropdown" href="#" role="button">Gluon <span 
class="caret"></span></a>
 <ul class="dropdown-menu navbar-menu" id="package-dropdown-menu">
@@ -81,11 +80,12 @@ <h1 id="logo-wrap">
 <span id="dropdown-menu-position-anchor-docs">
 <a aria-expanded="true" aria-haspopup="true" class="main-nav-link 
dropdown-toggle" data-toggle="dropdown" href="#" role="button">Docs <span 
class="caret"></span></a>
 <ul class="dropdown-menu navbar-menu" id="package-dropdown-menu-docs">
+<li><a class="main-nav-link" href="../../tutorials/index.html">Tutorials</a>
 <li><a class="main-nav-link" href="../../faq/index.html">FAQ</a></li>
 <li><a class="main-nav-link" 
href="../../architecture/index.html">Architecture</a></li>
 <li><a class="main-nav-link" 
href="https://github.com/apache/incubator-mxnet/tree/master/example";>Examples</a></li>
 <li><a class="main-nav-link" href="../../model_zoo/index.html">Model 
Zoo</a></li>
-</ul>
+</li></ul>
 </span>
 <a class="main-nav-link" href="https://github.com/dmlc/mxnet";>Github</a>
 <span id="dropdown-menu-position-anchor-community">
@@ -94,9 +94,9 @@ <h1 id="logo-wrap">
 <li><a class="main-nav-link" 
href="../../community/index.html">Community</a></li>
 <li><a class="main-nav-link" 
href="../../community/contribute.html">Contribute</a></li>
 <li><a class="main-nav-link" href="../../community/powered_by.html">Powered 
By</a></li>
+<li><a class="main-nav-link" href="http://discuss.mxnet.io";>Discuss</a></li>
 </ul>
 </span>
-<a class="main-nav-link" href="http://discuss.mxnet.io";>Discuss</a>
 <span id="dropdown-menu-position-anchor-version" style="position: relative"><a 
href="#" class="main-nav-link dropdown-toggle" data-toggle="dropdown" 
role="button" aria-haspopup="true" aria-expanded="true">Versions(master)<span 
class="caret"></span></a><ul id="package-dropdown-menu" 
class="dropdown-menu"><li><a class="main-nav-link" 
href=https://mxnet.incubator.apache.org/>1.0.0</a></li><li><a 
class="main-nav-link" 
href=https://mxnet.incubator.apache.org/versions/0.12.1/index.html>0.12.1</a></li><li><a
 class="main-nav-link" 
href=https://mxnet.incubator.apache.org/versions/0.12.0/index.html>0.12.0</a></li><li><a
 class="main-nav-link" 
href=https://mxnet.incubator.apache.org/versions/0.11.0/index.html>0.11.0</a></li><li><a
 class="main-nav-link" 
href=https://mxnet.incubator.apache.org/versions/master/index.html>master</a></li></ul></span></nav>
 <script> function getRootPath(){ return "../../" } </script>
 <div class="burgerIcon dropdown">
@@ -210,7 +210,7 @@ <h1 id="logo-wrap">
 <li>Christopher Olah?s <a class="reference external" 
href="http://colah.github.io/posts/2015-08-Understanding-LSTMs/";>Understanding 
LSTM blog post</a></li>
 <li><a class="reference external" 
href="http://dmlc.ml/mxnet/2015/11/15/char-lstm-in-julia.html";>Training a LSTM 
char-rnn in Julia to Generate Random Sentences</a></li>
 <li><a class="reference external" 
href="https://github.com/dmlc/mxnet-notebooks/blob/master/python/tutorials/char_lstm.ipynb";>Bucketing
 in MXNet in Python</a></li>
-<li><a class="reference external" 
href="https://mxnet.incubator.apache.org/versions/master/how_to/bucketing.html";>Bucketing
 in MXNet</a></li>
+<li><a class="reference external" 
href="https://mxnet.incubator.apache.org/versions/master/faq/bucketing.html";>Bucketing
 in MXNet</a></li>
 </ul>
 <div class="section" id="how-to-use-this-tutorial">
 <span id="how-to-use-this-tutorial"></span><h2>How to Use This Tutorial<a 
class="headerlink" href="#how-to-use-this-tutorial" title="Permalink to this 
headline">?</a></h2>
@@ -218,11 +218,11 @@ <h1 id="logo-wrap">
 <ol class="simple">
 <li>Run it by copying the provided code snippets and pasting them into the 
Scala command line, making the appropriate changes to the input file path.</li>
 <li>Reuse the code by making changes to relevant parameters and running it 
from command line.</li>
-<li><a class="reference external" 
href="https://github.com/apache/incubator-mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/rnn";>Run
 the source code directly</a> by running the <a class="reference external" 
href="https://github.com/apache/incubator-mxnet/tree/master/scala-package/examples/scripts/rnn";>provided
 scripts</a>.</li>
+<li><a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnet/examples/rnn";>Run
 the source code directly</a> by running the <a class="reference external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/scripts/rnn";>provided
 scripts</a>.</li>
 </ol>
 <p>To run the scripts:</p>
 <ul class="simple">
-<li>Build and train the model with the <a class="reference external" 
href="https://github.com/apache/incubator-mxnet/tree/master/scala-package/examples/scripts/rnn/run_train_charrnn.sh";>run_train_charrnn.sh
 script</a>. Edit the script as follows:</li>
+<li>Build and train the model with the <a class="reference external" 
href="https://github.com/dmlc/mxnet/blob/master/scala-package/examples/scripts/rnn/run_train_charrnn.sh";>run_train_charrnn.sh
 script</a>. Edit the script as follows:</li>
 </ul>
 <p>Edit the CLASS_PATH variable in the script to include your operating 
system-specific folder (e.g., linux-x86_64-cpu/linux-x86_64-gpu/osx-x86_64-cpu) 
in the path. Run the script with the following command:</p>
 <div class="highlight-bash"><div class="highlight"><pre><span></span>    bash 
run_train_charrnn.sh <which GPU card to use<span class="p">;</span> -1 means 
CPU> <input data path> <location to save the model>
@@ -254,7 +254,7 @@ <h1 id="logo-wrap">
 <span id="prerequisites"></span><h2>Prerequisites<a class="headerlink" 
href="#prerequisites" title="Permalink to this headline">?</a></h2>
 <p>To complete this tutorial, you need:</p>
 <ul class="simple">
-<li>MXNet. See the instructions for your operating system in <a 
class="reference external" 
href="https://mxnet.incubator.apache.org/versions/master/get_started/install.html";>Setup
 and Installation</a></li>
+<li>MXNet. See the instructions for your operating system in <a 
class="reference external" 
href="https://mxnet.incubator.apache.org/versions/master/install/index.html";>Setup
 and Installation</a></li>
 <li><a class="reference external" 
href="https://www.scala-lang.org/download/2.11.8.html";>Scala 2.11.8</a></li>
 <li><a class="reference external" 
href="https://maven.apache.org/install.html";>Maven 3</a></li>
 </ul>
@@ -372,12 +372,12 @@ <h1 id="logo-wrap">
 <p>To create the model:</p>
 <ol class="simple">
 <li>Load the helper files (<code class="docutils literal"><span 
class="pre">Lstm.scala</span></code>, <code class="docutils literal"><span 
class="pre">BucketIo.scala</span></code> and <code class="docutils 
literal"><span class="pre">RnnModel.scala</span></code>).
-<code class="docutils literal"><span class="pre">Lstm.scala</span></code> 
contains the definition of the LSTM cell. <code class="docutils literal"><span 
class="pre">BucketIo.scala</span></code> creates a sentence iterator. <code 
class="docutils literal"><span class="pre">RnnModel.scala</span></code> is used 
for model inference. The helper files are available on the <a class="reference 
external" 
href="https://github.com/apache/incubator-mxnet/tree/master/scala-package/examples/src/main/scala/org/apache/mxnetexamples/rnn";>MXNet
 site</a>.
+<code class="docutils literal"><span class="pre">Lstm.scala</span></code> 
contains the definition of the LSTM cell. <code class="docutils literal"><span 
class="pre">BucketIo.scala</span></code> creates a sentence iterator. <code 
class="docutils literal"><span class="pre">RnnModel.scala</span></code> is used 
for model inference. The helper files are available on the <a class="reference 
external" 
href="https://github.com/dmlc/mxnet/tree/master/scala-package/examples/src/main/scala/ml/dmlc/mxnetexamples/rnn";>MXNet
 site</a>.
 To load them, at the Scala command prompt type:</li>
 </ol>
-<div class="highlight-scala"><div class="highlight"><pre><span></span>        
<span class="n">scala</span><span class="o">></span> <span 
class="k">:</span><span class="kt">load</span> <span 
class="kt">../../../scala-package/examples/src/main/scala/org/apache/mxnet/examples/rnn/Lstm.scala</span>
-        <span class="n">scala</span><span class="o">></span> <span 
class="k">:</span><span class="kt">load</span> <span 
class="kt">../../../scala-package/examples/src/main/scala/org/apache/mxnet/examples/rnn/BucketIo.scala</span>
-        <span class="n">scala</span><span class="o">></span> <span 
class="k">:</span><span class="kt">load</span> <span 
class="kt">../../../scala-package/examples/src/main/scala/org/apache/mxnet/examples/rnn/RnnModel.scala</span>
+<div class="highlight-scala"><div class="highlight"><pre><span></span>        
<span class="n">scala</span><span class="o">></span> <span 
class="k">:</span><span class="kt">load</span> <span 
class="kt">../../../scala-package/examples/src/main/scala/ml/dmlc/mxnet/examples/rnn/Lstm.scala</span>
+        <span class="n">scala</span><span class="o">></span> <span 
class="k">:</span><span class="kt">load</span> <span 
class="kt">../../../scala-package/examples/src/main/scala/ml/dmlc/mxnet/examples/rnn/BucketIo.scala</span>
+        <span class="n">scala</span><span class="o">></span> <span 
class="k">:</span><span class="kt">load</span> <span 
class="kt">../../../scala-package/examples/src/main/scala/ml/dmlc/mxnet/examples/rnn/RnnModel.scala</span>
 </pre></div>
 </div>
 <ol class="simple">
@@ -415,11 +415,11 @@ <h1 id="logo-wrap">
                         <span class="n">numHidden</span> <span 
class="k">=</span> <span class="n">numHidden</span><span class="o">,</span> 
<span class="n">numEmbed</span> <span class="k">=</span> <span 
class="n">numEmbed</span><span class="o">,</span>
                         <span class="n">numLabel</span> <span 
class="k">=</span> <span class="n">vocab</span><span class="o">.</span><span 
class="n">size</span> <span class="o">+</span> <span class="mi">1</span><span 
class="o">,</span> <span class="n">dropout</span> <span class="k">=</span> 
<span class="mf">0.2f</span><span class="o">)</span>
           <span class="o">}</span>
-        <span class="n">symGen</span><span class="k">:</span> <span 
class="o">(</span><span class="kt">seqLen:</span> <span 
class="kt">Int</span><span class="o">)</span><span 
class="kt">org.apache.mxnet.Symbol</span>
+        <span class="n">symGen</span><span class="k">:</span> <span 
class="o">(</span><span class="kt">seqLen:</span> <span 
class="kt">Int</span><span class="o">)</span><span 
class="kt">ml.dmlc.mxnet.Symbol</span>
 
         <span class="n">scala</span><span class="o">></span> <span 
class="c1">// create the network symbol</span>
         <span class="n">scala</span><span class="o">></span> <span 
class="k">val</span> <span class="n">symbol</span> <span class="k">=</span> 
<span class="n">symGen</span><span class="o">(</span><span 
class="n">buckets</span><span class="o">(</span><span class="mi">0</span><span 
class="o">))</span>
-        <span class="n">symbol</span><span class="k">:</span> <span 
class="kt">org.apache.mxnet.Symbol</span> <span class="o">=</span> <span 
class="n">org</span><span class="o">.</span><span class="n">apache</span><span 
class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span 
class="nc">Symbol</span><span class="k">@</span><span class="mi">3</span><span 
class="n">a589eed</span>
+        <span class="n">symbol</span><span class="k">:</span> <span 
class="kt">ml.dmlc.mxnet.Symbol</span> <span class="o">=</span> <span 
class="n">ml</span><span class="o">.</span><span class="n">dmlc</span><span 
class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span 
class="nc">Symbol</span><span class="k">@</span><span class="mi">3</span><span 
class="n">a589eed</span>
 </pre></div>
 </div>
 <ol class="simple">
@@ -451,16 +451,16 @@ <h1 id="logo-wrap">
 </pre></div>
 </div>
 <ol class="simple">
-<li>You can set more than 100 epochs, but for this tutorial, specify 75 
epochs. Each epoch can take as long as 4 minutes on a GPU. In this tutorial, 
you will use the <a class="reference external" 
href="https://mxnet.incubator.apache.org/versions/master/api/scala/docs/index.html#org.apache.mxnet.optimizer.Adam";>ADAM
 optimizer</a>:</li>
+<li>You can set more than 100 epochs, but for this tutorial, specify 75 
epochs. Each epoch can take as long as 4 minutes on a GPU. In this tutorial, 
you will use the <a class="reference external" 
href="https://mxnet.incubator.apache.org/versions/master/api/scala/docs/index.html#ml.dmlc.mxnet.optimizer.Adam";>ADAM
 optimizer</a>:</li>
 </ol>
-<div class="highlight-scala"><div class="highlight"><pre><span></span>        
<span class="n">scala</span><span class="o">></span> <span 
class="k">import</span> <span class="nn">org.apache.mxnet._</span>
-        <span class="k">import</span> <span 
class="nn">org.apache.mxnet._</span>
+<div class="highlight-scala"><div class="highlight"><pre><span></span>        
<span class="n">scala</span><span class="o">></span> <span 
class="k">import</span> <span class="nn">ml.dmlc.mxnet._</span>
+        <span class="k">import</span> <span class="nn">ml.dmlc.mxnet._</span>
 
-        <span class="n">scala</span><span class="o">></span> <span 
class="k">import</span> <span 
class="nn">org.apache.mxnet.Callback.Speedometer</span>
-        <span class="k">import</span> <span 
class="nn">org.apache.mxnet.Callback.Speedometer</span>
+        <span class="n">scala</span><span class="o">></span> <span 
class="k">import</span> <span 
class="nn">ml.dmlc.mxnet.Callback.Speedometer</span>
+        <span class="k">import</span> <span 
class="nn">ml.dmlc.mxnet.Callback.Speedometer</span>
 
-        <span class="n">scala</span><span class="o">></span> <span 
class="k">import</span> <span class="nn">org.apache.mxnet.optimizer.Adam</span>
-        <span class="k">import</span> <span 
class="nn">org.apache.mxnet.optimizer.Adam</span>
+        <span class="n">scala</span><span class="o">></span> <span 
class="k">import</span> <span class="nn">ml.dmlc.mxnet.optimizer.Adam</span>
+        <span class="k">import</span> <span 
class="nn">ml.dmlc.mxnet.optimizer.Adam</span>
 
         <span class="n">scala</span><span class="o">></span> <span 
class="c1">// and we will see result by training 75 epochs</span>
         <span class="n">scala</span><span class="o">></span> <span 
class="k">val</span> <span class="n">numEpoch</span> <span class="k">=</span> 
<span class="mi">75</span>
@@ -497,7 +497,7 @@ <h1 id="logo-wrap">
                 <span class="n">loss</span> <span class="o">/</span> <span 
class="n">size</span>
                 <span class="o">}</span>
 
-        <span class="n">perplexity</span><span class="k">:</span> <span 
class="o">(</span><span class="kt">label:</span> <span 
class="kt">org.apache.mxnet.NDArray</span><span class="o">,</span> <span 
class="kt">pred:</span> <span class="kt">org.apache.mxnet.NDArray</span><span 
class="o">)</span><span class="nc">Float</span>
+        <span class="n">perplexity</span><span class="k">:</span> <span 
class="o">(</span><span class="kt">label:</span> <span 
class="kt">ml.dmlc.mxnet.NDArray</span><span class="o">,</span> <span 
class="kt">pred:</span> <span class="kt">ml.dmlc.mxnet.NDArray</span><span 
class="o">)</span><span class="nc">Float</span>
 
         <span class="n">scala</span><span class="o">></span> <span 
class="k">def</span> <span class="n">doCheckpoint</span><span 
class="o">(</span><span class="n">prefix</span><span class="k">:</span> <span 
class="kt">String</span><span class="o">)</span><span class="k">:</span> <span 
class="kt">EpochEndCallback</span> <span class="o">=</span> <span 
class="k">new</span> <span class="nc">EpochEndCallback</span> <span 
class="o">{</span>
                     <span class="k">override</span> <span class="k">def</span> 
<span class="n">invoke</span><span class="o">(</span><span 
class="n">epoch</span><span class="k">:</span> <span class="kt">Int</span><span 
class="o">,</span> <span class="n">symbol</span><span class="k">:</span> <span 
class="kt">Symbol</span><span class="o">,</span>
@@ -507,7 +507,7 @@ <h1 id="logo-wrap">
                     <span class="o">}</span>
                 <span class="o">}</span>
 
-        <span class="n">doCheckpoint</span><span class="k">:</span> <span 
class="o">(</span><span class="kt">prefix:</span> <span 
class="kt">String</span><span class="o">)</span><span 
class="kt">org.apache.mxnet.EpochEndCallback</span>
+        <span class="n">doCheckpoint</span><span class="k">:</span> <span 
class="o">(</span><span class="kt">prefix:</span> <span 
class="kt">String</span><span class="o">)</span><span 
class="kt">ml.dmlc.mxnet.EpochEndCallback</span>
 </pre></div>
 </div>
 <ol class="simple">
@@ -515,11 +515,11 @@ <h1 id="logo-wrap">
 </ol>
 <div class="highlight-scala"><div class="highlight"><pre><span></span>        
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> 
<span class="n">initializer</span> <span class="k">=</span> <span 
class="k">new</span> <span class="nc">Xavier</span><span 
class="o">(</span><span class="n">factorType</span> <span class="k">=</span> 
<span class="s">"in"</span><span class="o">,</span> <span 
class="n">magnitude</span> <span class="k">=</span> <span 
class="mf">2.34f</span><span class="o">)</span>
 
-        <span class="n">initializer</span><span class="k">:</span> <span 
class="kt">org.apache.mxnet.Xavier</span> <span class="o">=</span> <span 
class="n">org</span><span class="o">.</span><span class="n">apache</span><span 
class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span 
class="nc">Xavier</span><span class="k">@</span><span class="mi">54</span><span 
class="n">e8f10a</span>
+        <span class="n">initializer</span><span class="k">:</span> <span 
class="kt">ml.dmlc.mxnet.Xavier</span> <span class="o">=</span> <span 
class="n">ml</span><span class="o">.</span><span class="n">dmlc</span><span 
class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span 
class="nc">Xavier</span><span class="k">@</span><span class="mi">54</span><span 
class="n">e8f10a</span>
 </pre></div>
 </div>
 <ol class="simple">
-<li>Now, you have implemented all the supporting infrastructures for the 
char-lstm model. To train the model, use the standard <a class="reference 
external" 
href="https://mxnet.incubator.apache.org/versions/master/api/scala/docs/index.html#org.apache.mxnet.FeedForward";>MXNet
 high-level API</a>. You can train the model on a single GPU or CPU from 
multiple GPUs or CPUs by changing <code class="docutils literal"><span 
class="pre">scala</span> <span 
class="pre">.setContext(Array(Context.gpu(0),Context.gpu(1),Context.gpu(2),Context.gpu(3)))</span></code>
 to <code class="docutils literal"><span class="pre">scala</span> <span 
class="pre">.setContext(Array(Context.gpu(0)))</span></code>:</li>
+<li>Now, you have implemented all the supporting infrastructures for the 
char-lstm model. To train the model, use the standard <a class="reference 
external" 
href="https://mxnet.incubator.apache.org/versions/master/api/scala/docs/index.html#ml.dmlc.mxnet.FeedForward";>MXNet
 high-level API</a>. You can train the model on a single GPU or CPU from 
multiple GPUs or CPUs by changing <code class="docutils literal"><span 
class="pre">scala</span> <span 
class="pre">.setContext(Array(Context.gpu(0),Context.gpu(1),Context.gpu(2),Context.gpu(3)))</span></code>
 to <code class="docutils literal"><span class="pre">scala</span> <span 
class="pre">.setContext(Array(Context.gpu(0)))</span></code>:</li>
 </ol>
 <div class="highlight-scala"><div class="highlight"><pre><span></span>        
<span class="n">scala</span><span class="o">></span> <span class="k">val</span> 
<span class="n">model</span> <span class="k">=</span> <span 
class="nc">FeedForward</span><span class="o">.</span><span 
class="n">newBuilder</span><span class="o">(</span><span 
class="n">symbol</span><span class="o">)</span>
                 <span class="o">.</span><span class="n">setContext</span><span 
class="o">(</span><span class="nc">Array</span><span class="o">(</span><span 
class="nc">Context</span><span class="o">.</span><span 
class="n">gpu</span><span class="o">(</span><span class="mi">0</span><span 
class="o">),</span><span class="nc">Context</span><span class="o">.</span><span 
class="n">gpu</span><span class="o">(</span><span class="mi">1</span><span 
class="o">),</span><span class="nc">Context</span><span class="o">.</span><span 
class="n">gpu</span><span class="o">(</span><span class="mi">2</span><span 
class="o">),</span><span class="nc">Context</span><span class="o">.</span><span 
class="n">gpu</span><span class="o">(</span><span class="mi">3</span><span 
class="o">)))</span>
@@ -532,7 +532,7 @@ <h1 id="logo-wrap">
                 <span class="o">.</span><span 
class="n">setEpochEndCallback</span><span class="o">(</span><span 
class="n">doCheckpoint</span><span class="o">(</span><span 
class="s">"obama"</span><span class="o">))</span>
                 <span class="o">.</span><span class="n">build</span><span 
class="o">()</span>
 
-        <span class="n">model</span><span class="k">:</span> <span 
class="kt">org.apache.mxnet.FeedForward</span> <span class="o">=</span> <span 
class="n">org</span><span class="o">.</span><span class="n">apache</span><span 
class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span 
class="nc">FeedForward</span><span class="k">@</span><span 
class="mi">4926</span><span class="n">f6c7</span>
+        <span class="n">model</span><span class="k">:</span> <span 
class="kt">ml.dmlc.mxnet.FeedForward</span> <span class="o">=</span> <span 
class="n">ml</span><span class="o">.</span><span class="n">dmlc</span><span 
class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span 
class="nc">FeedForward</span><span class="k">@</span><span 
class="mi">4926</span><span class="n">f6c7</span>
 </pre></div>
 </div>
 <p>Now, you have an LSTM model and you?ve trained it. Use this model to create 
the inference.</p>
@@ -574,7 +574,7 @@ <h1 id="logo-wrap">
               <span class="n">arr</span><span class="o">.</span><span 
class="n">set</span><span class="o">(</span><span class="n">tmp</span><span 
class="o">)</span>
             <span class="o">}</span>
 
-      <span class="n">makeInput</span><span class="k">:</span> <span 
class="o">(</span><span class="kt">char:</span> <span 
class="kt">Char</span><span class="o">,</span> <span class="kt">vocab:</span> 
<span class="kt">Map</span><span class="o">[</span><span 
class="kt">String</span>,<span class="kt">Int</span><span class="o">],</span> 
<span class="n">arr</span><span class="k">:</span> <span 
class="kt">org.apache.mxnet.NDArray</span><span class="o">)</span><span 
class="nc">Unit</span>
+      <span class="n">makeInput</span><span class="k">:</span> <span 
class="o">(</span><span class="kt">char:</span> <span 
class="kt">Char</span><span class="o">,</span> <span class="kt">vocab:</span> 
<span class="kt">Map</span><span class="o">[</span><span 
class="kt">String</span>,<span class="kt">Int</span><span class="o">],</span> 
<span class="n">arr</span><span class="k">:</span> <span 
class="kt">ml.dmlc.mxnet.NDArray</span><span class="o">)</span><span 
class="nc">Unit</span>
 
       <span class="n">scala</span><span class="o">></span> <span class="c1">// 
helper function for random sample</span>
       <span class="n">scala</span><span class="o">></span> <span 
class="k">def</span> <span class="n">cdf</span><span class="o">(</span><span 
class="n">weights</span><span class="k">:</span> <span 
class="kt">Array</span><span class="o">[</span><span 
class="kt">Float</span><span class="o">])</span><span class="k">:</span> <span 
class="kt">Array</span><span class="o">[</span><span 
class="kt">Float</span><span class="o">]</span> <span class="k">=</span> <span 
class="o">{</span>
@@ -653,7 +653,7 @@ <h1 id="logo-wrap">
         <span class="n">seqLength</span><span class="k">:</span> <span 
class="kt">Int</span> <span class="o">=</span> <span class="mi">1200</span>
 
         <span class="n">scala</span><span class="o">></span> <span 
class="k">val</span> <span class="n">inputNdarray</span> <span 
class="k">=</span> <span class="nc">NDArray</span><span class="o">.</span><span 
class="n">zeros</span><span class="o">(</span><span class="mi">1</span><span 
class="o">)</span>
-        <span class="n">inputNdarray</span><span class="k">:</span> <span 
class="kt">org.apache.mxnet.NDArray</span> <span class="o">=</span> <span 
class="n">org</span><span class="o">.</span><span class="n">apache</span><span 
class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span 
class="nc">NDArray</span><span class="k">@</span><span class="mi">9</span><span 
class="n">c231a24</span>
+        <span class="n">inputNdarray</span><span class="k">:</span> <span 
class="kt">ml.dmlc.mxnet.NDArray</span> <span class="o">=</span> <span 
class="n">ml</span><span class="o">.</span><span class="n">dmlc</span><span 
class="o">.</span><span class="n">mxnet</span><span class="o">.</span><span 
class="nc">NDArray</span><span class="k">@</span><span class="mi">9</span><span 
class="n">c231a24</span>
 
         <span class="n">scala</span><span class="o">></span> <span 
class="k">val</span> <span class="n">revertVocab</span> <span 
class="k">=</span> <span class="n">makeRevertVocab</span><span 
class="o">(</span><span class="n">vocab</span><span class="o">)</span>
 
@@ -727,7 +727,7 @@ <h3><a href="../../index.html">Table Of Contents</a></h3>
             Apache MXNet is an effort undergoing incubation at The Apache 
Software Foundation (ASF), <strong>sponsored by the <i>Apache 
Incubator</i></strong>. 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, The Apache Software Foundation
+            "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 Apache 
Software Foundation."
         </p>
 </div>


 

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