[GitHub] [incubator-mxnet] PistonY opened a new issue #14955: [Feature request]Calculate network calculations tools for Gluon.

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PistonY opened a new issue #14955: [Feature request]Calculate network calculations tools for Gluon.
URL: https://github.com/apache/incubator-mxnet/issues/14955
 
 
   Now gluon has a `summary` function for calculate total params for a network but don't have a tool for calculate network FLOPs(G).
   
   Why needed this?
    - Model FLOPs could straightly measure a network inference speed.
    - Research needed.
    - Some of ops are widely used in many networks like conv, pooling, fc, bn
   , relu, softmax.
    - Some of ops are looping many times and have different shape of feature_maps outpus, it's hard to calculate them manually.
   
   But it's hard for calculating all of ops and actually not necessary(Some discussions [here](https://discuss.gluon.ai/t/topic/10228/8)). So I partition them on demand.
    1. Widely used in many networks and most commonly used.[urgent]
       - Conv2d/3d
       - Maxpool2d/3d
       - Avgpool 2d/3d
       - GlobalAvgPool2d/3d
       - FC
       - Relu, LeakyReLU, PReLU, Tanh, Sigmoid
       - BN
       - Softmax
       - RNN(basic rnn is just matrix multiplication, more complicated I don't know, this may need add if anything misses.)
    2. Used somewhere but may not common.[not urgent]
       - Dropout
       - Conv1d, Maxpool1d, Avgpool1d
       - GlobalAvgPool1d
       - ConvTranspose1d/2d/3d (GAN may use this, but for now GAN don't care about FLOPs)
       - UpSampling bilinear/nearest
       - InstanceNorm, LayerNorm
       - L2Normalization
   3. May only use once or little times in a model, their FLOPs may based on implement. Not hard to calculate manually.(May not to implement.)
        - ROIPooling
        - Atomic level operation(I didn't see anyone calculate them.)
    4. Need not to implement
       - Loss functions.
   
   Welcome to add if anything missing.
   Welcome to suggest if anything wrong.

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