text: from .util import grid_search
  from tabulate import tabulate
  
  from ...dataset import load_annotated_corpus
  from ...config import config_context
  from .parameter_space import bm25_parameter_space, tfidf_parameter_space, lexrank_parameter_space, \
      textrank_parameter_space
  from ..bm25 import BM25Summarizer
  from ..tf_idf import TFIDFSummarizer
  from ..baseline import BandSummarizer, RandomSummarizer, PositionSummarizer, LengthSummarizer
  from ..rouge import Rouge1Summarizer
  from ..rank import TextRank, LexRankSummarizer
  
  import click
  
  summarizer_list = [(BM25Summarizer, bm25_parameter_space, 50),
                     (TFIDFSummarizer, tfidf_parameter_space, 50),
                     (BandSummarizer, lambda x: [dict(k=i) for i in range(2, 6)], 5),
                     (RandomSummarizer, lambda x: [{"normalize": True}], 1),
                     (PositionSummarizer, lambda x: [dict(mode="first"), dict(mode="last")], 2),
                     (
                         Rouge1Summarizer, lambda x: [dict(metric="precision"), dict(metric="recall"), dict(metric="f1")],
                         3),
                     (LengthSummarizer, lambda x: [dict(mode="token"), dict(mode="char")], 2),
                     (LexRankSummarizer, lambda x: [{"normalize": True}], 5),
                     (LexRankPureSummarizer, lexrank_parameter_space, 10),
                     (TextRank, textrank_parameter_space, 10)]
  
  
  @click.group(help="SadedeGel summarizer commandline")
  def cli():
      pass
  
  
  @cli.command()
  @click.option("-f", "--table-format", default="github")
  @click.option("-t", "--tag", default=["extractive"], multiple=True)
  @click.option("-d", "--debug", default=False)
  def evaluate(table_format, tag, debug):
      """Evaluate various extractive summarizer using random hyper parameter sampling"""
  
      anno = load_annotated_corpus(False)
      relevance = [[doc['relevance']] for doc in anno]
  
      with config_context(tokenizer="bert") as DocBuilder:
          docs = [DocBuilder.from_sentences(doc['sentences']) for doc in anno]
  
      table = []
  
      for Summarizer, parameter_space, n_trial in filter(lambda x: any((t in x[0].tags) for t in tag), summarizer_list):
          scores = grid_search(relevance, docs, Summarizer, parameter_space(n_trial))
  
          table += [[method[0], method[1], scores[0], scores[1], scores[2]] for
                    method, scores in scores.items()]
  
      print(
          tabulate(sorted(table, key=lambda x: x[2], reverse=True)[:5]
                   , headers=['Method', "Parameter", 'ndcg(k=0.1)', 'ndcg(k=0.5)', 'ndcg(k=0.8)'],
                   tablefmt="github",
                   floatfmt=".4f"))
  
      print(
          tabulate(sorted(table, key=lambda x: x[3], reverse=True)[:5]
                   , headers=['Method', "Parameter", 'ndcg(k=0.1)', 'ndcg(k=0.5)', 'ndcg(k=0.8)'],
                   tablefmt="github",
                   floatfmt=".4f"))
  
      print(
          tabulate(sorted(table, key=lambda x: x[4], reverse=True)[:5]
                   , headers=['Method', "Parameter", 'ndcg(k=0.1)', 'ndcg(k=0.5)', 'ndcg(k=0.8)'],
                   tablefmt="github",
                   floatfmt=".4f"))
  
  
  if __name__ == '__main__':
      cli()
  