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From "zhangzhaoqi (Jira)" <j...@apache.org>
Subject [jira] [Updated] (SINGA-476) Autograd operators for ONNX
Date Thu, 12 Dec 2019 10:13:00 GMT

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

zhangzhaoqi updated SINGA-476:
------------------------------
    Description: 
For the demo purpose, we need to implement these three models and their components as following:
h2. [Tiny yolov2|https://arxiv.org/pdf/1612.08242.pdf]

-Add-
 -BatchNormalization-
 -Conv-
 -LeakyRelu-
 -MaxPool-
 -Mul-
h2. [Arcface|https://arxiv.org/pdf/1801.07698.pdf]

-Acos-
 -Add-
 -BatchNormalization-
 -Conv-
 -Cos-
 -Dropout-
 -Flatten-
 -Gemm-
 -Identity-
 InstanceNormalization
 LpNormalization
 -Mul-
 -PRelu-
 -Reshape-
 -Sub-
h2. [BIDAF|https://arxiv.org/pdf/1611.01603.pdf]

Abs
 -Add-
 ArgMax
 Cast
 Ceil
 -Clip-
 Compress
 -Concat-
 ConstantOfShape
 -Conv-
 -Dropout-
 Gather
 Hardmax
 Log
 LSTM
 -MatMul-
 ReduceMax
 ReduceSum
 Relu
 Shape
 Sigmoid
 Slice
 Squeeze
 Sub
 Sum
 Transpose
 Unsqueeze

 

In summary, we already implemented 13 ops, and there're still 27 ops needed to be implemented:
h2. Already implemented:

-Acos-
 -BatchNormalization-
 -Cos-
 -Conv-
 -LeakyRelu-
 -LSTM-
 -Abs-
 -MaxPool-
 -Flatten-
 -Add-
 -MatMul-
 -Relu-
 -Sigmoid-
h2. To be implemented:

ArgMax
 Cast
 Ceil
 -Clip-
 Compress
 -Concat-
 ConstantOfShape
 -Dropout-
 Gather
 -Gemm-
 Hardmax
 -Identity-
 InstanceNormalization
 -Log-
 LpNormalization
 -Mul-
 -PRelu-
 ReduceMax
 ReduceSum
 -Reshape-
 -Shape-
 Slice
 Squeeze
 -Sub-
 -Sum-
 -Transpose-
 Unsqueeze

Please refer to the [ONNX Operator Schemas|https://github.com/onnx/onnx/blob/master/docs/Operators.md] for
more detailed information.

  was:
For the demo purpose, we need to implement these three models and their components as following:
h2. [Tiny yolov2|https://arxiv.org/pdf/1612.08242.pdf]

-Add-
 -BatchNormalization-
 -Conv-
 -LeakyRelu-
 -MaxPool-
 -Mul-
h2. [Arcface|https://arxiv.org/pdf/1801.07698.pdf]

-Acos-
 -Add-
 -BatchNormalization-
 -Conv-
 -Cos-
 -Dropout-
 -Flatten-
 -Gemm-
 -Identity-
 InstanceNormalization
 LpNormalization
 -Mul-
 -PRelu-
 -Reshape-
 -Sub-
h2. [BIDAF|https://arxiv.org/pdf/1611.01603.pdf]

Abs
 -Add-
 ArgMax
 Cast
 Ceil
 -Clip-
 Compress
 -Concat-
 ConstantOfShape
 -Conv-
 -Dropout-
 Gather
 Hardmax
 Log
 LSTM
 -MatMul-
 ReduceMax
 ReduceSum
 Relu
 Shape
 Sigmoid
 Slice
 Squeeze
 Sub
 Sum
 Transpose
 Unsqueeze

 

In summary, we already implemented 13 ops, and there're still 27 ops needed to be implemented:
h2. Already implemented:

-Acos-
 -BatchNormalization-
 -Cos-
 -Conv-
 -LeakyRelu-
 -LSTM-
 -Abs-
 -MaxPool-
 -Flatten-
 -Add-
 -MatMul-
 -Relu-
 -Sigmoid-
h2. To be implemented:

ArgMax
 Cast
 Ceil
 Clip
 Compress
 -Concat-
 ConstantOfShape
 -Dropout-
 Gather
 -Gemm-
 Hardmax
 -Identity-
 InstanceNormalization
 -Log-
 LpNormalization
 -Mul-
 -PRelu-
 ReduceMax
 ReduceSum
 -Reshape-
 -Shape-
 Slice
 Squeeze
 -Sub-
 -Sum-
 -Transpose-
 Unsqueeze

Please refer to the [ONNX Operator Schemas|https://github.com/onnx/onnx/blob/master/docs/Operators.md] for
more detailed information.


> 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, bidaf.png, tiny_yolov2.png
>
>          Time Spent: 1h
>  Remaining Estimate: 0h
>
> For the demo purpose, we need to implement these three models and their components as
following:
> h2. [Tiny yolov2|https://arxiv.org/pdf/1612.08242.pdf]
> -Add-
>  -BatchNormalization-
>  -Conv-
>  -LeakyRelu-
>  -MaxPool-
>  -Mul-
> h2. [Arcface|https://arxiv.org/pdf/1801.07698.pdf]
> -Acos-
>  -Add-
>  -BatchNormalization-
>  -Conv-
>  -Cos-
>  -Dropout-
>  -Flatten-
>  -Gemm-
>  -Identity-
>  InstanceNormalization
>  LpNormalization
>  -Mul-
>  -PRelu-
>  -Reshape-
>  -Sub-
> h2. [BIDAF|https://arxiv.org/pdf/1611.01603.pdf]
> Abs
>  -Add-
>  ArgMax
>  Cast
>  Ceil
>  -Clip-
>  Compress
>  -Concat-
>  ConstantOfShape
>  -Conv-
>  -Dropout-
>  Gather
>  Hardmax
>  Log
>  LSTM
>  -MatMul-
>  ReduceMax
>  ReduceSum
>  Relu
>  Shape
>  Sigmoid
>  Slice
>  Squeeze
>  Sub
>  Sum
>  Transpose
>  Unsqueeze
>  
> In summary, we already implemented 13 ops, and there're still 27 ops needed to be implemented:
> h2. Already implemented:
> -Acos-
>  -BatchNormalization-
>  -Cos-
>  -Conv-
>  -LeakyRelu-
>  -LSTM-
>  -Abs-
>  -MaxPool-
>  -Flatten-
>  -Add-
>  -MatMul-
>  -Relu-
>  -Sigmoid-
> h2. To be implemented:
> ArgMax
>  Cast
>  Ceil
>  -Clip-
>  Compress
>  -Concat-
>  ConstantOfShape
>  -Dropout-
>  Gather
>  -Gemm-
>  Hardmax
>  -Identity-
>  InstanceNormalization
>  -Log-
>  LpNormalization
>  -Mul-
>  -PRelu-
>  ReduceMax
>  ReduceSum
>  -Reshape-
>  -Shape-
>  Slice
>  Squeeze
>  -Sub-
>  -Sum-
>  -Transpose-
>  Unsqueeze
> Please refer to the [ONNX Operator Schemas|https://github.com/onnx/onnx/blob/master/docs/Operators.md] for
more detailed information.



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