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28 changes: 14 additions & 14 deletions docs/api/python/gluon/model_zoo.md
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Expand Up @@ -42,20 +42,20 @@ The following table summarizes the available models.
| mobilenet0.5 | [MobileNet 0.5](https://arxiv.org/abs/1704.04861) | 1,342,536 | 0.6307 | 0.8475 | Trained with [script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py) |
| mobilenet0.75 | [MobileNet 0.75](https://arxiv.org/abs/1704.04861) | 2,601,976 | 0.6738 | 0.8782 | Trained with [script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py) |
| mobilenet1.0 | [MobileNet 1.0](https://arxiv.org/abs/1704.04861) | 4,253,864 | 0.7105 | 0.9006 | Trained with [script](https://github.com/apache/incubator-mxnet/blob/master/example/gluon/image_classification.py) |
| mobilenetv2_1.0 | [MobileNetV2 1.0](https://arxiv.org/abs/1801.04381) | 3,539,136 | 0.7192 | 0.9056 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| mobilenetv2_0.75 | [MobileNetV2 0.75](https://arxiv.org/abs/1801.04381) | 2,653,864 | 0.6961 | 0.8895 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| mobilenetv2_0.5 | [MobileNetV2 0.5](https://arxiv.org/abs/1801.04381) | 1,983,104 | 0.6449 | 0.8547 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| mobilenetv2_0.25 | [MobileNetV2 0.25](https://arxiv.org/abs/1801.04381) | 1,526,856 | 0.5074 | 0.7456 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| resnet18_v1 | [ResNet-18 V1](http://arxiv.org/abs/1512.03385) | 11,699,112 | 0.7093 | 0.8992 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| resnet34_v1 | [ResNet-34 V1](http://arxiv.org/abs/1512.03385) | 21,814,696 | 0.7437 | 0.9187 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| resnet50_v1 | [ResNet-50 V1](http://arxiv.org/abs/1512.03385) | 25,629,032 | 0.7647 | 0.9313 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| resnet101_v1 | [ResNet-101 V1](http://arxiv.org/abs/1512.03385) | 44,695,144 | 0.7834 | 0.9401 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| resnet152_v1 | [ResNet-152 V1](http://arxiv.org/abs/1512.03385) | 60,404,072 | 0.7900 | 0.9438 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| resnet18_v2 | [ResNet-18 V2](https://arxiv.org/abs/1603.05027) | 11,695,796 | 0.7100 | 0.8992 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| resnet34_v2 | [ResNet-34 V2](https://arxiv.org/abs/1603.05027) | 21,811,380 | 0.7440 | 0.9208 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| resnet50_v2 | [ResNet-50 V2](https://arxiv.org/abs/1603.05027) | 25,595,060 | 0.7711 | 0.9343 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| resnet101_v2 | [ResNet-101 V2](https://arxiv.org/abs/1603.05027) | 44,639,412 | 0.7853 | 0.9417 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| resnet152_v2 | [ResNet-152 V2](https://arxiv.org/abs/1603.05027) | 60,329,140 | 0.7921 | 0.9431 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/index.html#image-classification) |
| mobilenetv2_1.0 | [MobileNetV2 1.0](https://arxiv.org/abs/1801.04381) | 3,539,136 | 0.7192 | 0.9056 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| mobilenetv2_0.75 | [MobileNetV2 0.75](https://arxiv.org/abs/1801.04381) | 2,653,864 | 0.6961 | 0.8895 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| mobilenetv2_0.5 | [MobileNetV2 0.5](https://arxiv.org/abs/1801.04381) | 1,983,104 | 0.6449 | 0.8547 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| mobilenetv2_0.25 | [MobileNetV2 0.25](https://arxiv.org/abs/1801.04381) | 1,526,856 | 0.5074 | 0.7456 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| resnet18_v1 | [ResNet-18 V1](http://arxiv.org/abs/1512.03385) | 11,699,112 | 0.7093 | 0.8992 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| resnet34_v1 | [ResNet-34 V1](http://arxiv.org/abs/1512.03385) | 21,814,696 | 0.7437 | 0.9187 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| resnet50_v1 | [ResNet-50 V1](http://arxiv.org/abs/1512.03385) | 25,629,032 | 0.7647 | 0.9313 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| resnet101_v1 | [ResNet-101 V1](http://arxiv.org/abs/1512.03385) | 44,695,144 | 0.7834 | 0.9401 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| resnet152_v1 | [ResNet-152 V1](http://arxiv.org/abs/1512.03385) | 60,404,072 | 0.7900 | 0.9438 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| resnet18_v2 | [ResNet-18 V2](https://arxiv.org/abs/1603.05027) | 11,695,796 | 0.7100 | 0.8992 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| resnet34_v2 | [ResNet-34 V2](https://arxiv.org/abs/1603.05027) | 21,811,380 | 0.7440 | 0.9208 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| resnet50_v2 | [ResNet-50 V2](https://arxiv.org/abs/1603.05027) | 25,595,060 | 0.7711 | 0.9343 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| resnet101_v2 | [ResNet-101 V2](https://arxiv.org/abs/1603.05027) | 44,639,412 | 0.7853 | 0.9417 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| resnet152_v2 | [ResNet-152 V2](https://arxiv.org/abs/1603.05027) | 60,329,140 | 0.7921 | 0.9431 | Trained with [script](https://gluon-cv.mxnet.io/model_zoo/classification.html) |
| squeezenet1.0 | [SqueezeNet 1.0](https://arxiv.org/abs/1602.07360) | 1,248,424 | 0.5611 | 0.7909 | Converted from pytorch vision |
| squeezenet1.1 | [SqueezeNet 1.1](https://github.com/DeepScale/SqueezeNet/tree/master/SqueezeNet_v1.1) | 1,235,496 | 0.5496 | 0.7817 | Converted from pytorch vision |
| vgg11 | [VGG-11](https://arxiv.org/abs/1409.1556) | 132,863,336 | 0.6662 | 0.8734 | Converted from pytorch vision |
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6 changes: 3 additions & 3 deletions docs/api/python/optimization/optimization.md
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Expand Up @@ -133,18 +133,18 @@ straightforward.
For `initializer`, create a subclass of ``Initializer`` and define the
`_init_weight` method. We can also change the default behaviors to initialize
other parameters such as `_init_bias`. See
[`initializer.py`](https://github.com/dmlc/mxnet/blob/master/python/mxnet/initializer.py)
[`initializer.py`](https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/initializer.py)
for examples.

For ``optimizer``, create a subclass of ``Optimizer``
and implement two methods ``create_state`` and ``update``. Also add
``@mx.optimizer.Optimizer.register`` before this class. See
[`optimizer.py`](https://github.com/dmlc/mxnet/blob/master/python/mxnet/optimizer.py)
[`optimizer.py`](https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/optimizer/optimizer.py)
for examples.

For `lr_scheduler`, create a subclass of `LRScheduler` and then implement the
`__call__` method. See
[`lr_scheduler.py`](https://github.com/dmlc/mxnet/blob/master/python/mxnet/lr_scheduler.py)
[`lr_scheduler.py`](https://github.com/apache/incubator-mxnet/blob/master/python/mxnet/lr_scheduler.py)
for examples.

## API Reference
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4 changes: 2 additions & 2 deletions docs/community/contribute.md
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Expand Up @@ -81,9 +81,9 @@ MXNet uses Apache's JIRA to track issues and larger projects. Anyone can review

## Confluence Wiki

The [MXNet Confluence Wiki](https://cwiki.apache.org/confluence/display/MXNET/MXNet+Home) has detailed development environment setup info, design proposals, release process info, and more. This is generally where contributor information is maintained.
The [MXNet Confluence Wiki](https://cwiki.apache.org/confluence/display/MXNET/Apache+MXNet+Home) has detailed development environment setup info, design proposals, release process info, and more. This is generally where contributor information is maintained.

* [MXNet Confluence Wiki](https://cwiki.apache.org/confluence/display/MXNET/MXNet+Home) <i class="fas fa-external-link-alt"></i>
* [MXNet Confluence Wiki](https://cwiki.apache.org/confluence/display/MXNET/Apache+MXNet+Home) <i class="fas fa-external-link-alt"></i>


## Setup MXNet for Development
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