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
云烟成雨TD20 小时前
LangFlow 1.x 系列【7】工作流创建与部署指南
人工智能·python·agent
月疯20 小时前
np.where()[0]的用法
开发语言·python·numpy
KaMeidebaby20 小时前
卡梅德生物技术快报|纳米抗体技术全套实操流程:AFB1 全合成文库淘选 + 分子对接定点突变参数手册
人工智能·python·tcp/ip·算法·机器学习
hnxaoli21 小时前
统信小程序(十六)xls转xlsx
开发语言·python·小程序
梦想三三21 小时前
Flask + PyTorch模型部署实战:从训练权重到API接口完整工程解析(附完整代码)
人工智能·pytorch·python·flask·模型推理·ai 工程化
用户2986985301421 小时前
Python 实现 Excel 与 TXT 文本的高效转换与导出
后端·python·excel
杨超越luckly21 小时前
Agent 应用指南:基于 OurAirports 的中国机场设施数据可视化
python·html·github·可视化·机场设施
卷无止境21 小时前
pytest 从零到实战:要想代码好,测试少不了
后端·python
吃糖的小孩21 小时前
# RootGraph v1.5 收工:我给 QQ 机器人补上了聊天运行时的“黑匣子”
python
Tbisnic21 小时前
22.AI大模型开发:深度学习中神经网络的神经元、激活函数与参数初始化
人工智能·深度学习·神经网络·激活函数·梯度下降·反向传播