code: def read(self, image_feat_path):
      feat = load_feat(image_feat_path, convert_to_tensor=True)
      assert feat.shape[0] == 1, "batch is not 1"
      b, c, h, w = feat.shape
      if self.max_features:
          padded_feat = torch.zeros(
              (b, c, self.img_h, self.img_w), dtype=torch.float
          )
          padded_feat[:, :, :h, :w] = feat
          feat = padded_feat
      feat = feat.squeeze(0)
      return feat, None
  
imports: import math
  import os
  import pickle
  from typing import Any
  import lmdb
  import numpy
  import torch
  from mmf.utils.file_io import PathManager
label_desc: Use image node_id 2 for calling the CHWFeatureReader obj's underlying member method code with example usage: obj.read(image_feat_path) and returns: feat,  None