[DONE]New AUX_Decoder/Backbone Network : LYNXNet #200
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yxlllc
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* Faster NSF inference (#202) * faster nsf * faster nsf * Slightly optimize * Pad negative length --------- Co-authored-by: yqzhishen <yangqian_1015@icloud.com> * [DONE]New AUX_Decoder/Backbone Network : LYNXNet (#200) * Update __init__.py * Update LYNXNet * add dropout * Lynxnet outnorm (#206) * post-norm * fix * add norm+mlp * Update LYNXNet.py * Update LYNXNetDecoder.py * do not need mlp * do not need mlp * Add out norm for LYNXNET * Add out norm for LYNXNETDecoder * delete lynxnet aux_decoder (#212) * refactor configuration options --------- Co-authored-by: yqzhishen <yangqian_1015@icloud.com> Co-authored-by: KakaruHayate <97896816+KakaruHayate@users.noreply.github.com>
yqzhishen
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Nov 15, 2024
* [DONE]New AUX_Decoder/Backbone Network : LYNXNet (#200) * Update __init__.py * Update LYNXNet * add dropout * Lynxnet outnorm (#206) * post-norm * fix * add norm+mlp * Update LYNXNet.py * Update LYNXNetDecoder.py * do not need mlp * do not need mlp * Add out norm for LYNXNET * Add out norm for LYNXNETDecoder * delete lynxnet aux_decoder (#212) * refactor configuration options * fix onnx exporter for lynxnet * Add Pytorch version check when export onnx (#216) * recommended lynxnet hyperparameters for variance models * remove invalid items * Refactor code * Finish configuration schemas --------- Co-authored-by: KakaruHayate <97896816+KakaruHayate@users.noreply.github.com> Co-authored-by: yxlllc <llc1995@sina.com>
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LYNXNet(Linear Gated Depthwise Separable Convolution Network)
refer to：
https://github.com/CNChTu/Diffusion-SVC/blob/v2.0_dev/diffusion/naive_v2/model_conformer_naive.py
https://github.com/CNChTu/Diffusion-SVC/blob/v2.0_dev/diffusion/naive_v2/naive_v2_diff.py
Refactoring the code, removing unnecessary parts, and adapting to OpenVPI/DiffSinger
The following parameters are recommended for use:
Please note that when dim>512, Layernorm will be enabled by default to ensure stability during trainingTIPS:You can control the style of the generated results by modifying the 'activation'(LYNXNet.py，Line:129),