code: def extract_activation_maps(img, model, img_scalings):
      activation_maps = []
  
      for scale in img_scalings:
          # Reshape image.
          inp = img.unsqueeze(0)
  
          # Scale image. If scale == 1, this is a no-op.
          inp = torch.nn.functional.interpolate(
              inp,
              scale_factor=scale,
              mode="bilinear",
              align_corners=False,
          )
  
          vc = inp.cuda()
          feats = model(vc)[0].cpu()
          activation_maps.append(feats)
  
      return activation_maps
  
imports: import logging
  import os
  import sys
  from argparse import Namespace
  from typing import Any, List
  import numpy
  import torch
  import torchvision
  from classy_vision.generic.util import copy_model_to_gpu, load_checkpoint
  from iopath.common.file_io import g_pathmgr
  from vissl.config import AttrDict
  from vissl.hooks import default_hook_generator
  from vissl.models import build_model
  from vissl.utils.checkpoint import get_checkpoint_folder, init_model_from_consolidated_weights
  from vissl.utils.distributed_launcher import launch_distributed
  from vissl.utils.env import set_env_vars, setup_path_manager
  from vissl.utils.extract_features_utils import ExtractedFeaturesLoader
  from vissl.utils.hydra_config import compose_hydra_configuration, convert_to_attrdict, print_cfg
  from vissl.utils.instance_retrieval_utils.data_util import CopyDaysDataset, GenericInstanceRetrievalDataset, get_average_gem, InstanceRetrievalDataset, InstanceRetrievalImageLoader, InstreDataset, is_copdays_dataset, is_instre_dataset, is_oxford_paris_dataset, is_revisited_dataset, is_whiten_dataset, l2n, MultigrainResize, RevisitedInstanceRetrievalDataset, WhiteningTrainingImageDataset
  from vissl.utils.instance_retrieval_utils.rmac import get_rmac_descriptors
  from vissl.utils.io import load_file, makedir, save_file
  from vissl.utils.logger import setup_logging, shutdown_logging
  from vissl.utils.pca import load_pca, train_and_save_pca
  from vissl.utils.perf_stats import PerfStats, PerfTimer
label_desc: Use image node_id 2 for calling a global function with example usage: extract_activation_maps(img, model, img_scalings) and returns: activation_maps