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https://github.com/pmixer/zan.initializer

Sample to show how input dim(input_dim for FC layer, for CNN, it's prod(tensor.shape[1:])) reciprocal could be used for initialize NN weights rather than sqrt(input_dim_reciprocal) hinted by Xavier:dragon:
https://github.com/pmixer/zan.initializer

cnn initial-nn-weights tensor xavier

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Sample to show how input dim(input_dim for FC layer, for CNN, it's prod(tensor.shape[1:])) reciprocal could be used for initialize NN weights rather than sqrt(input_dim_reciprocal) hinted by Xavier:dragon:

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# zan.initializer

Sample to show how input dim(input_dim for FC layer, for CNN, it's prod(tensor.shape[1:])) reciprocal could be used for initial NN weights:dragon:

Sometimes more effective than xavier initializer in my experiments if without BatchNorm layers inside the network.

```
@misc{zan2017initializer,
title={Input Dimension Reciprocal for Effective Weight Initialization},
author={Huang, Zan},
year={2017},
publisher={GitHub},
howpublished={\url{https://github.com/pmixer/zan.initializer}},
}
```