TODO about cl-waffe HOT 8 OPEN

The things that I should do next:

1. Optimize broadcasting until it beats numpy/pytorch
   The current implementation of broadcasting depends on BLAS/CUDA Operation, failing to parallelize.
   I guess I need to look for other ways of implementation....

2. Support Half(FP16)
   i gonna call CFFI by myself or something

3. Save and Restore Models.
   support compatibility with npz

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The first version won't be released until the above is completed if not all.

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I'm working on inlining call-forward/call-backward.
This works really nicely.

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I've inlined call-forward/call-backward, #120

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とりあえずやること:
ドキュメントの編集 (Important)
kernel.lispの最適化 (it's done?)
npzのパーサーをかく (turned to be unnecessary)

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Anyway, the rest things should be done until the first version release are the following:

1. Prepare more documents and tutorials for those who are new to cl-waffe
2. More impls of NN: (e.g. RNN/LSTM/GRU (make them 100x faster!), CNN/AvgPooling MaxPooling/, Attentions, faster embedding, Normalizations, More various activations etc...)
3. To achieve 2., the speed of iterations is important.

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1. float16
2. !view, which works like torch's one.
3. refactoring whole codes

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build documentations on mkdocs

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