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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2017/11/20 05:56:03 UTC
[GitHub] piiswrong closed pull request #8710: Remove experimental warning on Gluon and add Gluon tutorials
piiswrong closed pull request #8710: Remove experimental warning on Gluon and add Gluon tutorials
URL: https://github.com/apache/incubator-mxnet/pull/8710
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diff --git a/docs/api/python/autograd/autograd.md b/docs/api/python/autograd/autograd.md
index de8188446b..410d6a94e2 100644
--- a/docs/api/python/autograd/autograd.md
+++ b/docs/api/python/autograd/autograd.md
@@ -1,14 +1,9 @@
# Autograd Package
-
```eval_rst
.. currentmodule:: mxnet.autograd
```
-```eval_rst
-.. warning:: This package is currently experimental and may change in the near future.
-```
-
## Overview
The `autograd` package enables automatic
diff --git a/docs/api/python/gluon/data.md b/docs/api/python/gluon/data.md
index f72f3cd03f..0b5f959e32 100644
--- a/docs/api/python/gluon/data.md
+++ b/docs/api/python/gluon/data.md
@@ -15,10 +15,6 @@ This document lists the data APIs in Gluon:
The `Gluon Data` API, defined in the `gluon.data` package, provides useful dataset loading
and processing tools, as well as common public datasets.
-```eval_rst
-.. warning:: This package contains experimental APIs and may change in the near future.
-```
-
In the rest of this document, we list routines provided by the `gluon.data` package.
## Data
diff --git a/docs/api/python/gluon/gluon.md b/docs/api/python/gluon/gluon.md
index 0ef6dbed0e..2ae766fdcb 100644
--- a/docs/api/python/gluon/gluon.md
+++ b/docs/api/python/gluon/gluon.md
@@ -5,10 +5,6 @@
.. currentmodule:: mxnet.gluon
```
-```eval_rst
-.. warning:: This package is currently experimental and may change in the near future.
-```
-
<script type="text/javascript" src='../../_static/js/auto_module_index.js'></script>
## Overview
diff --git a/docs/api/python/gluon/model_zoo.md b/docs/api/python/gluon/model_zoo.md
index 18d9ae2cb8..a22b437640 100644
--- a/docs/api/python/gluon/model_zoo.md
+++ b/docs/api/python/gluon/model_zoo.md
@@ -18,10 +18,6 @@ This document lists the model APIs in Gluon:
The `Gluon Model Zoo` API, defined in the `gluon.model_zoo` package, provides pre-defined
and pre-trained models to help bootstrap machine learning applications.
-```eval_rst
-.. warning:: This package contains experimental APIs and may change in the near future.
-```
-
In the rest of this document, we list routines provided by the `gluon.model_zoo` package.
### Vision
diff --git a/docs/tutorials/index.md b/docs/tutorials/index.md
index aaaa40c381..6429dfb31b 100644
--- a/docs/tutorials/index.md
+++ b/docs/tutorials/index.md
@@ -2,13 +2,37 @@
These tutorials introduce a few fundamental concepts in deep learning and how to implement them in _MXNet_. The _Basics_ section contains tutorials on manipulating arrays, building networks, loading/preprocessing data, etc. The _Training and Inference_ section talks about implementing Linear Regression, training a Handwritten digit classifier using MLP and CNN, running inferences using a pre-trained model, and lastly, efficiently training a large scale image classifier.
-```eval_rst
-.. Note:: We are working on a set of tutorials for the new imperative interface called Gluon. A preview version is hosted at http://gluon.mxnet.io.
-```
-## Python
+## Gluon
+
+Gluon is the high-level interface for MXNet. It is more intuitive and easier to use than the lower level interface.
+Gluon supports dynamic (define-by-run) graphs with JIT-compilation to achieve both flexibility and efficiency.
+This is a selected subset of Gluon tutorials. For the comprehensive tutorial on Gluon,
+please see [gluon.mxnet.io](http://gluon.mxnet.io).
+
+### Basics
+
+- [Manipulate data the MXNet way with ndarray](http://gluon.mxnet.io/chapter01_crashcourse/ndarray.html)
+- [Automatic differentiation with autograd](http://gluon.mxnet.io/chapter01_crashcourse/autograd.html)
+- [Linear regression with gluon](http://gluon.mxnet.io/chapter02_supervised-learning/linear-regression-gluon.html)
+- [Serialization - saving, loading and checkpointing](http://gluon.mxnet.io/chapter03_deep-neural-networks/serialization.html)
+
+### Neural Networks
+
+- [Multilayer perceptrons in gluon](http://gluon.mxnet.io/chapter03_deep-neural-networks/mlp-gluon.html)
+- [Convolutional Neural Networks in gluon](http://gluon.mxnet.io/chapter04_convolutional-neural-networks/cnn-gluon.html)
+- [Recurrent Neural Networks with gluon](http://gluon.mxnet.io/chapter05_recurrent-neural-networks/rnns-gluon.html)
+
+### Advanced
+
+- [Plumbing: A look under the hood of gluon](http://gluon.mxnet.io/chapter03_deep-neural-networks/plumbing.html)
+- [Designing a custom layer with gluon](http://gluon.mxnet.io/chapter03_deep-neural-networks/custom-layer.html)
+- [Fast, portable neural networks with Gluon HybridBlocks](http://gluon.mxnet.io/chapter07_distributed-learning/hybridize.html)
+- [Training on multiple GPUs with gluon](http://gluon.mxnet.io/chapter07_distributed-learning/multiple-gpus-gluon.html)
+
+## MXNet
-### Basic
+### Basics
```eval_rst
.. toctree::
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