code: def forward_db(self, batch_data):
      imgs = torch.Tensor(batch_data).cuda()
      imgs.div_(255).sub_(0.5).div_(0.5)
      feat = self.model(imgs)
      feat = feat.reshape([self.batch_size, 2 * feat.shape[1]])
      return feat.cpu().numpy()
  
imports: import os
  import pickle
  import matplotlib
  import pandas
  import matplotlib.pyplot
  import timeit
  import sklearn
  import argparse
  import cv2
  import numpy
  import torch
  from skimage import transform
  from backbones import get_model
  from sklearn.metrics import roc_curve, auc
  from menpo.visualize.viewmatplotlib import sample_colours_from_colourmap
  from prettytable import PrettyTable
  from pathlib import Path
  import sys
  import warnings
label_desc: Use image node_id 3 for calling the Embedding obj's underlying member method code with example usage: obj.forward_db(batch_data) and returns: feat