resnet18下载与保存,转换为ONNX模型,导出 .wts 格式的权重文件

1.download and save to 'resnet18.pth' file:

复制代码
import torch
from torch import nn
from torch.nn import functional as F
import torchvision

def main():
    print('cuda device count: ', torch.cuda.device_count())
    net = torchvision.models.resnet18(pretrained=True)
    #net.fc = nn.Linear(512, 2)
    net = net.to('cuda:0')
    net.eval()
    print(net)
    tmp = torch.ones(2, 3, 224, 224).to('cuda:0')
    out = net(tmp)
    print('resnet18 out:', out.shape)
    torch.save(net, "resnet18.pth")

if __name__ == '__main__':
    main()

this 'resnet18.pth' file contains the model structure and weights.

2.load the .pth file and transform it to ONNX format:

复制代码
import torch

def main():
    
    model = torch.load('resnet18.pth')
    # model.eval()
    inputs = torch.randn(1,3,224,224)
    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
    inputs = inputs.to(device)
    torch.onnx.export(model,inputs, 'resnet18_trtpose.onnx',training=2)
    
if __name__ == '__main__':
    main()

3.load and read the .pth file, extract the weights of the model to a .wts file

复制代码
import torch
from torch import nn
import torchvision
import os
import struct
from torchsummary import summary

def main():
    print('cuda device count: ', torch.cuda.device_count())
    net = torch.load('resnet18.pth')
    net = net.to('cuda:0')
    net.eval()
    print('model: ', net)
    #print('state dict: ', net.state_dict().keys())
    tmp = torch.ones(1, 3, 224, 224).to('cuda:0')
    print('input: ', tmp)
    out = net(tmp)
    print('output:', out)

    summary(net, (3,224,224))
    #return
    f = open("resnet18.wts", 'w')
    f.write("{}\n".format(len(net.state_dict().keys())))
    for k,v in net.state_dict().items():
        print('key: ', k)
        print('value: ', v.shape)
        vr = v.reshape(-1).cpu().numpy()
        f.write("{} {}".format(k, len(vr)))
        for vv in vr:
            f.write(" ")
            f.write(struct.pack(">f", float(vv)).hex())
        f.write("\n")

if __name__ == '__main__':
    main()
相关推荐
云泽野3 小时前
【Java|集合类】list遍历的6种方式
java·python·list
IMPYLH5 小时前
Python 的内置函数 reversed
笔记·python
shangyingying_16 小时前
关于小波降噪、小波增强、小波去雾的原理区分
人工智能·深度学习·计算机视觉
小赖同学啊7 小时前
物联网数据安全区块链服务
开发语言·python·区块链
码荼7 小时前
学习开发之hashmap
java·python·学习·哈希算法·个人开发·小白学开发·不花钱不花时间crud
书玮嘎7 小时前
【WIP】【VLA&VLM——InternVL系列】
人工智能·深度学习
要努力啊啊啊7 小时前
YOLOv2 正负样本分配机制详解
人工智能·深度学习·yolo·计算机视觉·目标跟踪
小陈phd8 小时前
李宏毅机器学习笔记——梯度下降法
人工智能·python·机器学习
喝过期的拉菲8 小时前
如何使用 Pytorch Lightning 启用早停机制
pytorch·lightning·早停机制
kk爱闹8 小时前
【挑战14天学完python和pytorch】- day01
android·pytorch·python