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The implementation of various lightweight networks by using PyTorch. such as:MobileNetV2,MobileNeXt,GhostNet,ParNet,MobileViT、AdderNet,ShuffleNetV1-V2,LCNet,ConvNeXt,etc. ⭐⭐⭐⭐⭐

Home Page: https://github.com/murufeng/awesome_lightweight_networks

License: MIT License

Python 100.00%
awesome-list deep-learning mobile-networks mobilenet

awesome_lightweight_networks's Introduction

Hi 👋Hello , 😄 I am murufeng ✨.

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awesome_lightweight_networks's Issues

想请教一下轻量模型占大显存的原因?

在工程实践的时候发现很多轻量模型的推理速度确实快,但是其所占的显存也很大,如mobileNetV3在显存中达到3到4G,这是正常的吗?因为其参数量其实很小,但是在显存中占据如此大的资源?

谢谢您的整合与工作

如何贡献?

很高兴看到轻量级网络的github工具包,我是SCNU大学的研究生,也在研究轻量级网络设计及剪枝这块,目前在写论文,论文完成后,可贡献源码到这个工具包中。

轻量的人体姿态估计

请问对轻量的人体姿态估计有没有什么好的推荐呢?或者相应的思路优化。谢谢您!

黑白单通道照片报错:维度出错

light_cnns ==0.4.2

from light_cnns import parnet_s
model = parnet_s(1, 12)
model.eval()
print(model)
input = torch.randn(1, 1, 12, 5000) # 1张高12宽5000分辨率的黑白单通道照片
y = model(input)
print(y.size())

运行报错:
RuntimeError: The size of tensor a (312) must match the size of tensor b (313) at non-singleton dimension 3
x: torch.Size([1, 384, 1, 312])
y: torch.Size([1, 384, 1, 313])

a = x + y 这里报错

对于新网络的支持

您好,我想知道这个包是否还会更新?
我最近看到了一些新的网络,比如MobileViT v2,Parc-Net,EdgeNeXt等
请问您是否有计划在包内补充这些网络?

einops.EinopsError

import torch
from light_cnns import mobilevit_s
model = mobilevit_s()
model.eval()
print(model)
input = torch.randn(1, 3, 224, 224)
y = model(input)
print(y.size())
这段代码输入报错:einops.EinopsError: Error while processing rearrange-reduction pattern "b d (h ph) (w pw) -> b (ph pw) (h w) d".
Input tensor shape: torch.Size([1, 240, 7, 7]). Additional info: {'ph': 2, 'pw': 2}.
Shape mismatch, can't divide axis of length 7 in chunks of 2

修改为(1, 3, 256, 256)才好

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