class_docstr: Implements SQuAD metrics, maximizing over answers per question.
class_docstr_tok: ["Implements","SQuAD","metrics",",","maximizing","over","answers","per","question","."]
code: def empty(cls) -> "ShardedSquad":
      return cls(f1=0.0, em=0.0, count=0)
  
imports: import collections
  import itertools
  import re
  import string
  from typing import Any, Dict, Mapping, Optional, Sequence, Tuple, Union
  from absl import logging
  import editdistance
  import flax
  import jax.numpy
  import numpy
  import sacrebleu
  import scipy.stats
  import seqio
  import sklearn.metrics
  from t5.evaluation import qa_utils
  import tensorflow.compat.v2
  from rouge_score import rouge_scorer
  from rouge_score import scoring
label_desc: Use image node_id 1 for calling the ShardedSquad obj's underlying member method code with example usage: obj.empty(cls) and returns: cls