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1. Add param op
2. Add logSoftmax
3. modify NLLLoss

Fix a bug of bias.

We have made huge improvements over its early version N3LDG:

1. Convenient model building (e.g., Node *y = dropout(x, 0.1) vs N3LDG's vector<DropoutNode> ys; ys.resize(n); for (Node *y : ys) y.init(blabla); y.forward(blabla);).
2. Transformer support, including the decoder for inference time.
3. More operators with more thoughtful dynamic batching.
4. Preliminary documentation
5. Careful Memory Management(tensor's ref_count, the object pool, the better memory pool, etc.).