class_docstr: COINZSPredictor for COIN zero-shot prediction.
class_docstr_tok: ["COINZSPredictor","for","COIN","zero-shot","prediction","."]
code: def flat_subsample(self, tensor):
      if len(tensor.size()) > 1 and tensor.size(0) == 1:
          tensor = tensor.squeeze(0)
      return tensor
  
imports: import os
  import random
  import json
  import numpy
  import torch
  import pickle
  import math
  from tqdm import tqdm
label_desc: Use image node_id 4 for calling the COINZSPredictor obj's underlying member method code with example usage: obj.flat_subsample(tensor) and returns: tensor