修改yolov8发现缺少loss文件

下面是tal_loss.py文件的显示， YOLOATSSAssigner，from models.loss.gfocal_loss import VarifocalLoss, BboxLoss这三个文件请问在哪里呢？我找了一圈没找到在哪？

`#!/usr/bin/env python3
# -*- coding:utf-8 -*-

import torch
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
from models.module.nanodet_utils import generate_anchors
from models.module.nanodet_utils import dist2bbox, xywh2xyxy
# from loss.yolox_loss import IOUloss
from models.assigner.yolo_atss_assigner import YOLOATSSAssigner
from models.assigner.tal_assigner import TaskAlignedAssigner
from utils.torch_utils import is_parallel
from models.loss.gfocal_loss import VarifocalLoss, BboxLoss

class ComputeTalLoss:
'''Loss computation func.'''
def __init__(self,
model,
cfg):
# fpn_strides=[8, 16, 32]
# grid_cell_size=5.0
# grid_cell_offset=0.5
# num_classes=80,
# ori_img_size=640
# use_dfl=True
# reg_max=16
# iou_type='siou'
# num_classes = cfg.Dataset.nc
# loss_weight={ 'class': 1.0, 'iou': 2.5, 'dfl': 0.5}
# device = next(model.parameters()).device # get model device
self.epoch = 0
self.det = model.module.head if is_parallel(model) else model.head# Detect() module
self.fpn_strides = cfg.Model.Head.strides
self.grid_cell_size = cfg.Loss.grid_cell_size
self.grid_cell_offset = cfg.Loss.grid_cell_offset
self.num_classes = cfg.Dataset.nc
self.ori_img_size = cfg.Dataset.img_size

# warmup_epoch=4
self.warmup_epoch = cfg.hyp.warmup_epochs
self.warmup_assigner = YOLOATSSAssigner(9, num_classes=self.num_classes)
self.formal_assigner = TaskAlignedAssigner(top_k=13, num_classes=self.num_classes, alpha=1.0, beta=6.0)

self.use_dfl = cfg.Loss.use_dfl
self.use_gfl = cfg.Loss.use_gfl
self.reg_max = cfg.Loss.reg_max
self.iou_type = cfg.Loss.iou_type
self.proj = nn.Parameter(torch.linspace(0, self.reg_max, self.reg_max + 1), requires_grad=False)
self.varifocal_loss = VarifocalLoss().cuda()
self.bce = nn.BCELoss(reduction='none')
self.bbox_loss = BboxLoss(self.num_classes, self.reg_max, self.use_dfl, self.iou_type).cuda()
self.loss_weight = {'class': cfg.Loss.qfl_loss_weight, 'iou': cfg.Loss.box_loss_weight, 'dfl':cfg.Loss.dfl_loss_weight} `