




from collections import defaultdict
from pathlib import Path

import pandas as pd
from rouge_cli import calculate_rouge_path

from utils import calculate_rouge


_snake_case										=       [
    "Prosecutor: \"No videos were used in the crash investigation\" German papers say they saw a cell phone video of the"
    " final seconds on board Flight 9525. The Germanwings co-pilot says he had a \"previous episode of severe"
    " depression\" German airline confirms it knew of Andreas Lubitz's depression years before he took control.",
    "The Palestinian Authority officially becomes the 123rd member of the International Criminal Court. The formal"
    " accession was marked with a ceremony at The Hague, in the Netherlands. The Palestinians signed the ICC's"
    " founding Rome Statute in January. Israel and the United States opposed the Palestinians' efforts to join the"
    " body.",
    "Amnesty International releases its annual report on the death penalty. The report catalogs the use of"
    " state-sanctioned killing as a punitive measure across the globe. At least 607 people were executed around the"
    " world in 2014, compared to 778 in 2013. The U.S. remains one of the worst offenders for imposing capital"
    " punishment.",
]

_snake_case										=       [
    "Marseille prosecutor says \"so far no videos were used in the crash investigation\" despite media reports ."
    " Journalists at Bild and Paris Match are \"very confident\" the video clip is real, an editor says . Andreas Lubitz"
    " had informed his Lufthansa training school of an episode of severe depression, airline says .",
    "Membership gives the ICC jurisdiction over alleged crimes committed in Palestinian territories since last June ."
    " Israel and the United States opposed the move, which could open the door to war crimes investigations against"
    " Israelis .",
    "Amnesty's annual death penalty report catalogs encouraging signs, but setbacks in numbers of those sentenced to"
    " death . Organization claims that governments around the world are using the threat of terrorism to advance"
    " executions . The number of executions worldwide has gone down by almost 22% compared with 2013, but death"
    " sentences up by 28% .",
]







def 				lowerCAmelCase_	(     ):
      _A							:     int			=						calculate_rouge(snake_case_,snake_case_,bootstrap_aggregation=snake_case_,rouge_keys=["""rouge2""", """rougeL"""]     )
      assert isinstance(snake_case_,snake_case_     )
      _A							:     List[str]			=						calculate_rouge(snake_case_,snake_case_,bootstrap_aggregation=snake_case_,rouge_keys=["""rouge2"""]     )
      assert (
          pd.DataFrame(no_aggregation["""rouge2"""]     ).fmeasure.mean()
          == pd.DataFrame(no_aggregation_just_ra["""rouge2"""]     ).fmeasure.mean()
      )







def 				lowerCAmelCase_	(     ):
      _A							:     Any			=						"""rougeLsum"""
      _A							:     List[str]			=						calculate_rouge(snake_case_,snake_case_,newline_sep=snake_case_,rouge_keys=[k]     )[k]
      _A							:     List[Any]			=						calculate_rouge(snake_case_,snake_case_,newline_sep=snake_case_,rouge_keys=[k]     )[k]
      assert score > score_no_sep







def 				lowerCAmelCase_	(     ):
      _A							:     Dict			=						["""rouge1""", """rouge2""", """rougeL"""]
      _A							:     Dict			=						calculate_rouge(snake_case_,snake_case_,newline_sep=snake_case_,rouge_keys=snake_case_     )
      _A							:     List[Any]			=						calculate_rouge(snake_case_,snake_case_,newline_sep=snake_case_,rouge_keys=snake_case_     )
      assert score_sep == score_no_sep







def 				lowerCAmelCase_	(     ):
      _A							:     Union[str, Any]			=						[
          """Her older sister, Margot Frank, died in 1945, a month earlier than previously thought.""",
          """Marseille prosecutor says \"so far no videos were used in the crash investigation\" despite media reports .""",
      ]
      _A							:     int			=						[
          """Margot Frank, died in 1945, a month earlier than previously thought.""",
          """Prosecutor: \"No videos were used in the crash investigation\" German papers say they saw a cell phone video of"""
          """ the final seconds on board Flight 9525.""",
      ]
      assert calculate_rouge(snake_case_,snake_case_,newline_sep=snake_case_     ) == calculate_rouge(snake_case_,snake_case_,newline_sep=snake_case_     )







def 				lowerCAmelCase_	(     ):
      _A							:     int			=						[
          """\" \"a person who has such a video needs to immediately give it to the investigators,\" prosecutor says .<n> \"it is a very disturbing scene,\" editor-in-chief of bild online tells \"erin burnett: outfront\" """
      ]
      _A							:     Any			=						[
          """ Marseille prosecutor says \"so far no videos were used in the crash investigation\" despite media reports . Journalists at Bild and Paris Match are \"very confident\" the video clip is real, an editor says . Andreas Lubitz had informed his Lufthansa training school of an episode of severe depression, airline says ."""
      ]

      _A							:     Dict			=						calculate_rouge(snake_case_,snake_case_,rouge_keys=["""rougeLsum"""],newline_sep=snake_case_     )["""rougeLsum"""]
      _A							:     List[str]			=						calculate_rouge(snake_case_,snake_case_,rouge_keys=["""rougeLsum"""]     )["""rougeLsum"""]
      assert new_score > prev_score







def 				lowerCAmelCase_	(     ):
      _A							:     int			=						Path("""examples/seq2seq/test_data/wmt_en_ro"""     )
      _A							:     Optional[Any]			=						calculate_rouge_path(data_dir.joinpath("""test.source"""     ),data_dir.joinpath("""test.target"""     )     )
      assert isinstance(snake_case_,snake_case_     )
      _A							:     Dict			=						calculate_rouge_path(
          data_dir.joinpath("""test.source"""     ),data_dir.joinpath("""test.target"""     ),bootstrap_aggregation=snake_case_     )
      assert isinstance(snake_case_,snake_case_     )



"""simple docstring"""





import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
    from .tokenization_fnet import FNetTokenizer
else:
    _a		       =							None

_a		       =							logging.get_logger(__name__)
_a		       =							{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

_a		       =							{
    'vocab_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/spiece.model',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json',
    },
}

_a		       =							{
    'google/fnet-base': 512,
    'google/fnet-large': 512,
}

_a		       =							'▁'


class A_	(lowercase__      ):




  '''simple docstring'''
  SCREAMING_SNAKE_CASE__			:						List[str]       =		VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__			:						Tuple       =		PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__			:						Any       =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__			:						Union[str, Any]       =		["""input_ids""", """token_type_ids"""]
  SCREAMING_SNAKE_CASE__			:						Tuple       =		FNetTokenizer







  def __init__(		self				,   lowercase_=None				,   lowercase_=None				,   lowercase_=False				,   lowercase_=True				,   lowercase_=True				,   lowercase_="<unk>"				,   lowercase_="[SEP]"				,   lowercase_="<pad>"				,   lowercase_="[CLS]"				,   lowercase_="[MASK]"				,   **lowercase_				,   ):

     """simple docstring"""
     # Mask token behave like a normal word, i.e. include the space before it and
     # is included in the raw text, there should be a match in a non-normalized sentence.
     UpperCAmelCase_					:					int			     =    (
         AddedToken(lowercase_				,   lstrip=lowercase_				,   rstrip=lowercase_				,   normalized=lowercase_  )
         if isinstance(lowercase_				,   lowercase_  )
         else mask_token
     )

     super().__init__(
         lowercase_				,   tokenizer_file=lowercase_				,   do_lower_case=lowercase_				,   remove_space=lowercase_				,   keep_accents=lowercase_				,   unk_token=lowercase_				,   sep_token=lowercase_				,   pad_token=lowercase_				,   cls_token=lowercase_				,   mask_token=lowercase_				,   **lowercase_				,   )

     UpperCAmelCase_					:					Any			     =    do_lower_case
     UpperCAmelCase_					:					Tuple			     =    remove_space
     UpperCAmelCase_					:					str			     =    keep_accents
     UpperCAmelCase_					:					Any			     =    vocab_file
     UpperCAmelCase_					:					List[Any]			     =    False if not self.vocab_file else True







  def        UpperCamelCase__					(		self				,   lowercase_				,   lowercase_ = None  ):

     """simple docstring"""
     UpperCAmelCase_					:					Tuple			     =    [self.sep_token_id]
     UpperCAmelCase_					:					Any			     =    [self.cls_token_id]
     if token_ids_a is None:
        return cls + token_ids_a + sep
     return cls + token_ids_a + sep + token_ids_a + sep







  def        UpperCamelCase__					(		self				,   lowercase_				,   lowercase_ = None  ):

     """simple docstring"""
     UpperCAmelCase_					:					Any			     =    [self.sep_token_id]
     UpperCAmelCase_					:					Any			     =    [self.cls_token_id]

     if token_ids_a is None:
        return len(cls + token_ids_a + sep  ) * [0]
     return len(cls + token_ids_a + sep  ) * [0] + len(token_ids_a + sep  ) * [1]







  def        UpperCamelCase__					(		self				,   lowercase_				,   lowercase_ = None  ):

     """simple docstring"""
     if not os.path.isdir(lowercase_  ):
        logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""  )
        return
     UpperCAmelCase_					:					List[str]			     =    os.path.join(
         lowercase_				,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]  )

     if os.path.abspath(self.vocab_file  ) != os.path.abspath(lowercase_  ):
        copyfile(self.vocab_file				,   lowercase_  )

     return (out_vocab_file,)


