class_docstr: COINZSPredictor for COIN zero-shot prediction.
class_docstr_tok: ["COINZSPredictor","for","COIN","zero-shot","prediction","."]
code: def finalize(self, Y_pred, Y_true, output_file=None):
      Y_pred = torch.cat(Y_pred, dim=0).numpy()
      Y_true = torch.cat(Y_true, dim=0).numpy()
      assert len(Y_pred) == len(Y_true)
  
      error_mask = Y_pred != Y_true
      print(
          "sample error",
          Y_pred[error_mask][:10],
          Y_true[error_mask][:10],
      )
      print(
          "sample error",
          Y_pred[error_mask][10:20],
          Y_true[error_mask][10:20],
      )
  
      if output_file is not None:
          with open(
              os.path.join(self.pred_dir, output_file + ".pkl"), "wb"
          ) as fw:
              pickle.dump(
                  {"Y_pred": Y_pred, "Y_true": Y_true},
                  fw,
                  protocol=pickle.HIGHEST_PROTOCOL,
              )
      return {"outputs": Y_pred, "targets": Y_true}
  
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 6 for calling the COINZSPredictor obj's underlying member method code with example usage: obj.finalize(Y_pred, Y_true, output_file) and returns: dict