【程序】yolo v3 : train.py

import os
import numpy as np
import time
import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
import torch.backends.cudnn as cudnn
from torch.utils.data import DataLoader
from utils.dataloader import yolo_dataset_collate, YoloDataset
from nets.yolo_training import YOLOLoss,Generator
from nets.yolo3 import YoloBody
from tqdm import tqdm



Config = 
{
    "yolo": {
        "anchors": [[[116, 90], [156, 198], [373, 326]],
                    [[30, 61], [62, 45], [59, 119]],
                    [[10, 13], [16, 30], [33, 23]]],
        "classes": 80,
    },
    "img_h": 416,
    "img_w": 416,
}


def get_lr(optimizer):
    for param_group in optimizer.param_groups:
        return param_group['lr']
        
def fit_ont_epoch(net,yolo_losses,epoch,epoch_size,epoch_size_val,gen,genval,Epoch,cuda):
    total_loss = 0
    va