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From "zhangzhaoqi (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SINGA-476) Autograd operators for ONNX
Date Wed, 31 Jul 2019 07:28:00 GMT

     [ https://issues.apache.org/jira/browse/SINGA-476?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

zhangzhaoqi updated SINGA-476:
------------------------------
    Attachment: arcface(based resnet100).png

> Autograd operators for ONNX
> ---------------------------
>
>                 Key: SINGA-476
>                 URL: https://issues.apache.org/jira/browse/SINGA-476
>             Project: Singa
>          Issue Type: New Feature
>            Reporter: zhangzhaoqi
>            Priority: Critical
>         Attachments: arcface(based resnet100).png, tiny_yolov2.png
>
>
> For the demo purpose, we need to implement these three models, and these are their components:
> h2. [Tiny yolov2|https://arxiv.org/pdf/1612.08242.pdf]
> MaxPooling2D
>  Conv2D
>  BatchNormalization
>  LeakyReLU
>  Reshape
> h2. [Arcface|https://arxiv.org/pdf/1801.07698.pdf]
> Conv2D
>  BatchNormalization
>  relu
>  MaxPooling2D
>  Dropout
>  Flatten
>  Dense
>  Softmax
>  l2_normalize
>  acos
>  cos
> h2. [BIDAF|https://arxiv.org/pdf/1611.01603.pdf]
> K.stack
>  Softmax
>  K.expand_dims
>  K.sum
>  Constant
>  Dense
>  Lambda(lambda x: 1.0 - x, output_shape=(dim,))
>  Multiply
>  Add
>  K.concatenate
>  K.shape
>  K.max
>  K.tile
>  K.squeeze
>  linear
>  TimeDistributed
>  Bidirectional(LSTM
>  
>  
> In summary, we already implemented 12 ops, and there still are 16 ops needed to be implemented:
> h2. Already implemented:
> -LSTM-
>  -Multiply-
>  -Add-
>  -linear-
>  -relu-
>  -acos-
>  -cos-
>  -LeakyReLU-
>  -Softmax-
>  -MaxPooling2D-
>  -Conv2D-
>  -BatchNormalization-
> h2. To be implemented:
> Reshape
>  Flatten
>  Dropout
>  max
>  shape
>  concatenate
>  Constant
>  L2Normalization
>  Expand
>  tile
>  squeeze
>  Dense*
>  TimeDistributed*
>  Bidirectional*
>  Stack*
>  Lambda*
> *means this op doesn't have a corresponding one at ONNX op sets, therefore, it needs
a converter function by using basic op sets.
>  



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