repvgg

最新推荐文章于 2025-05-10 13:48:35 发布

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最新推荐文章于 2025-05-10 13:48:35 发布

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分类专栏：深度学习宝典

本文链接：https://blog.youkuaiyun.com/jacke121/article/details/112970245

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这篇博客探讨了RepVGG模型在ImageNet数据集上的精度表现，深入研究了其优化技术和成果。

imagenet精度：

import torch.nn as nn
import numpy as np
import torch

def conv_bn(in_channels, out_channels, kernel_size, stride, padding, groups=1):
    result = nn.Sequential()
    result.add_module('conv', nn.Conv2d(in_channels=in_channels, out_channels=out_channels,
                                                  kernel_size=kernel_size, stride=stride, padding=padding, groups=groups, bias=False))
    result.add_module('bn', nn.BatchNorm2d(num_features=out_channels))
    return result

class RepVGGBlock(nn.Module):

    def __init__(self, in_channels, out_channels, kernel_size,
                 stride=1, padding=0,

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