Have you tried something like
import torch
import torch.nn as nn
from torchvision import models

class MyNewModel(nn.Module):
  def __init__(self):
     super(MyNewModel, self).__init__()
     self.resnet = models.resnet18(pretrained=True)
     self.out = nn.Sequential([nn.Conv2d(...) , nn.Sigmoid()])
  def forward(self,x):
     x = self.resnet(x)
     x = self.out(x)
     return  x


def train():
    model = MyNewModel()
  #model training

In this case using a pretrained resnet18