class_docstr: Summarization Metrics
  
  This class computes the following standard summarization metrics
  
  1. Rouge (1,2,L)
  2. Extractiveness (coverage, density, novel n-grams)
  3. Compression
  4. Faithfulness (SummaC)
code: def _compute_faithfulness_scores(
      self, inp: str, pred: str
  ) -> Dict[str, float]:
      return {"summac": self.summac.score_one(inp, pred)["score"]}
  
imports: import json
  import pandas
  import numpy
  import os
  import pickle
  import spacy
  from typing import List, Dict, Optional
  from collections import defaultdict
  from helm.benchmark.adaptation.scenario_state import ScenarioState
  from helm.benchmark.adaptation.request_state import RequestState
  from helm.benchmark.adaptation.adapter_spec import AdapterSpec
  from helm.common.hierarchical_logger import hlog
  from helm.common.general import ensure_file_downloaded
  from .metric import Metric, MetricResult
  from .metric_name import MetricName
  from .metric_service import MetricService
  from .basic_metrics import get_rouge_function
  from .statistic import Stat
  from .summac.model_summac import SummaCZS
  from bert_score import BERTScorer
label_desc: Use image node_id 7 for calling the SummarizationMetric obj's underlying member method code with example usage: obj._compute_faithfulness_scores(inp, pred) and returns: dict