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https://issues.apache.org/jira/browse/SINGA-476?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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zhangzhaoqi updated SINGA-476:
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Attachment: bidaf.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, bidaf.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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