class_docstr: Evaluation output (always contains labels), to be used to compute metrics.
  
  Parameters:
      predictions (`np.ndarray`): Predictions of the model.
      label_ids (`np.ndarray`): Targets to be matched.
      inputs (`np.ndarray`, *optional*)
class_docstr_tok: ["Evaluation","output","(","always","contains","labels",")",",","to","be","used","to","compute","metrics",".","Parameters",":","predictions","(","`","np.ndarray","`",")",":","Predictions","of","the","model",".","label_ids","(","`","np.ndarray","`",")",":","Targets","to","be","matched",".","inputs","(","`","np.ndarray","`",",","*","optional","*",")"]
code: def __getitem__(self, idx):
      if idx < 0 or idx > 2:
          raise IndexError("tuple index out of range")
      if idx == 2 and self.inputs is None:
          raise IndexError("tuple index out of range")
      if idx == 0:
          return self.predictions
      elif idx == 1:
          return self.label_ids
      elif idx == 2:
          return self.inputs
  
imports: import copy
  import functools
  import gc
  import inspect
  import os
  import random
  import re
  import threading
  import time
  from typing import Any, Dict, List, NamedTuple, Optional, Tuple, Union
  import numpy
  from .utils import ExplicitEnum, is_psutil_available, is_tf_available, is_torch_available, is_torch_cuda_available, is_torch_tpu_available, requires_backends
label_desc: Use image node_id 3 for calling the EvalPrediction obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: self, self, self