

from collections import defaultdict
from pathlib import Path

import pandas as pd
from rouge_cli import calculate_rouge_path

from utils import calculate_rouge


lowerCAmelCase     :   Optional[int]						     =  [
    '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.',
]

lowerCAmelCase     :   List[str]						     =  [
    '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    A_      (							):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     calculate_rouge(a					,   a					,   bootstrap_aggregation=a					,   rouge_keys=['rouge2', 'rougeL']  )
      assert isinstance(a					,   a  )
      SCREAMING_SNAKE_CASE_				:  Any           =     calculate_rouge(a					,   a					,   bootstrap_aggregation=a					,   rouge_keys=['rouge2']  )
      assert (
          pd.DataFrame(no_aggregation['rouge2']  ).fmeasure.mean()
          == pd.DataFrame(no_aggregation_just_ra['rouge2']  ).fmeasure.mean()
      )

def    A_      (							):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  Dict           =     'rougeLsum'
      SCREAMING_SNAKE_CASE_				:  int           =     calculate_rouge(a					,   a					,   newline_sep=a					,   rouge_keys=[k]  )[k]
      SCREAMING_SNAKE_CASE_				:  Any           =     calculate_rouge(a					,   a					,   newline_sep=a					,   rouge_keys=[k]  )[k]
      assert score > score_no_sep

def    A_      (							):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  str           =     ['rouge1', 'rouge2', 'rougeL']
      SCREAMING_SNAKE_CASE_				:  Dict           =     calculate_rouge(a					,   a					,   newline_sep=a					,   rouge_keys=a  )
      SCREAMING_SNAKE_CASE_				:  List[Any]           =     calculate_rouge(a					,   a					,   newline_sep=a					,   rouge_keys=a  )
      assert score_sep == score_no_sep

def    A_      (							):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  str           =     [
          '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 .',
      ]
      SCREAMING_SNAKE_CASE_				:  List[Any]           =     [
          '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(a					,   a					,   newline_sep=a  ) == calculate_rouge(a					,   a					,   newline_sep=a  )

def    A_      (							):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  Optional[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" '
      ]
      SCREAMING_SNAKE_CASE_				:  List[str]           =     [
          ' 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 .'
      ]

      SCREAMING_SNAKE_CASE_				:  List[Any]           =     calculate_rouge(a					,   a					,   rouge_keys=['rougeLsum']					,   newline_sep=a  )['rougeLsum']
      SCREAMING_SNAKE_CASE_				:  Dict           =     calculate_rouge(a					,   a					,   rouge_keys=['rougeLsum']  )['rougeLsum']
      assert new_score > prev_score



def    A_      (							):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  int           =     Path('examples/seq2seq/test_data/wmt_en_ro'  )
      SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     calculate_rouge_path(data_dir.joinpath('test.source'  )					,   data_dir.joinpath('test.target'  )  )
      assert isinstance(a					,   a  )
      SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     calculate_rouge_path(
          data_dir.joinpath('test.source'  )					,   data_dir.joinpath('test.target'  )					,   bootstrap_aggregation=a  )
      assert isinstance(a					,   a  )









import json
import os
import unittest

from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
    VOCAB_FILES_NAMES,
    GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class  _A		(  __magic_name__   ,     unittest.TestCase):
  SCREAMING_SNAKE_CASE    :      Dict       =  GPTSanJapaneseTokenizer
  SCREAMING_SNAKE_CASE    :      List[Any]       =  False
  SCREAMING_SNAKE_CASE    :      Union[str, Any]       =  {'''do_clean_text''': False, '''add_prefix_space''': False}

  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        super().setUp()

        # fmt: off
        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     ['こん', 'こんに', 'にちは', 'ばんは', '世界,㔺界', '、', '。', '<BR>', '<SP>', '<TAB>', '<URL>', '<EMAIL>', '<TEL>', '<DATE>', '<PRICE>', '<BLOCK>', '<KIGOU>', '<U2000U2BFF>', '<|emoji1|>', '<unk>', '<|bagoftoken|>', '<|endoftext|>']
        # fmt: on
        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     {'emoji': {'\ud83d\ude00': '<|emoji1|>'}, 'emoji_inv': {'<|emoji1|>': '\ud83d\ude00'}}  # 😀
        SCREAMING_SNAKE_CASE_				:  int           =     {'unk_token': '<unk>'}

        SCREAMING_SNAKE_CASE_				:  Any           =     os.path.join(self.tmpdirname ,					VOCAB_FILES_NAMES['vocab_file']					)
        SCREAMING_SNAKE_CASE_				:  List[str]           =     os.path.join(self.tmpdirname ,					VOCAB_FILES_NAMES['emoji_file']					)
        with open(self.vocab_file ,					'w' ,					encoding='utf-8'					) as vocab_writer:
              vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]					)					)
        with open(self.emoji_file ,					'w'					) as emoji_writer:
              emoji_writer.write(json.dumps(_SCREAMING_SNAKE_CASE					)					)

  def  UpperCAmelCase    (				self ,					**_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        kwargs.update(self.special_tokens_map					)
        return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname ,					**_SCREAMING_SNAKE_CASE					)

  def  UpperCAmelCase    (				self ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     'こんにちは、世界。 \nこんばんは、㔺界。😀'
        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     'こんにちは、世界。 \nこんばんは、世界。😀'
        return input_text, output_text

  def  UpperCAmelCase    (				self ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_       ,						SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     self.get_input_output_texts(_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     tokenizer.encode(_SCREAMING_SNAKE_CASE ,					add_special_tokens=_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  Any           =     tokenizer.decode(_SCREAMING_SNAKE_CASE ,					clean_up_tokenization_spaces=_SCREAMING_SNAKE_CASE					)
        return text, ids

  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        pass  # TODO add if relevant

  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        pass  # TODO add if relevant

  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        pass  # TODO add if relevant

  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  List[str]           =     self.get_tokenizer()

        # Testing tokenization
        SCREAMING_SNAKE_CASE_				:  List[Any]           =     'こんにちは、世界。　こんばんは、㔺界。'
        SCREAMING_SNAKE_CASE_				:  List[str]           =     ['こん', 'にちは', '、', '世界', '。', '<SP>', 'こん', 'ばんは', '、', '㔺界', '。']
        SCREAMING_SNAKE_CASE_				:  str           =     tokenizer.tokenize(_SCREAMING_SNAKE_CASE					)
        self.assertListEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)

        # Testing conversion to ids without special tokens
        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
        SCREAMING_SNAKE_CASE_				:  List[str]           =     tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE					)
        self.assertListEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)

        # Testing conversion to ids with special tokens
        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     tokens + [tokenizer.unk_token]
        SCREAMING_SNAKE_CASE_				:  str           =     [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
        SCREAMING_SNAKE_CASE_				:  str           =     tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE					)
        self.assertListEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)

  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Optional[int]           =     self.get_tokenizer()

        # Testing tokenization
        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     'こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。'
        SCREAMING_SNAKE_CASE_				:  str           =     'こんにちは、、、、世界。こんばんは、、、、世界。'
        SCREAMING_SNAKE_CASE_				:  Optional[int]           =     tokenizer.encode(_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  Optional[int]           =     tokenizer.decode(_SCREAMING_SNAKE_CASE					)
        self.assertEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)

  @slow
  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Optional[int]           =     self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'					)

        # Testing tokenization
        SCREAMING_SNAKE_CASE_				:  int           =     'こんにちは、世界。'
        SCREAMING_SNAKE_CASE_				:  List[str]           =     'こんばんは、㔺界。😀'
        SCREAMING_SNAKE_CASE_				:  List[str]           =     'こんにちは、世界。こんばんは、世界。😀'
        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     tokenizer.encode(prefix_text + input_text					)
        SCREAMING_SNAKE_CASE_				:  int           =     tokenizer.encode('' ,					prefix_text=prefix_text + input_text					)
        SCREAMING_SNAKE_CASE_				:  List[Any]           =     tokenizer.encode(_SCREAMING_SNAKE_CASE ,					prefix_text=_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  List[str]           =     tokenizer.decode(_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  str           =     tokenizer.decode(_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  Dict           =     tokenizer.decode(_SCREAMING_SNAKE_CASE					)
        self.assertEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
        self.assertEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
        self.assertEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)

  @slow
  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Any           =     self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'					)

        # Testing tokenization
        SCREAMING_SNAKE_CASE_				:  Any           =     'こんにちは、世界。'
        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     'こんばんは、㔺界。😀'

        SCREAMING_SNAKE_CASE_				:  int           =     len(tokenizer.encode(_SCREAMING_SNAKE_CASE					)					) - 2
        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     len(tokenizer.encode(_SCREAMING_SNAKE_CASE					)					) - 2

        SCREAMING_SNAKE_CASE_				:  str           =     [1] + [0] * (len_prefix + len_text + 1)
        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     [1] * (len_prefix + len_text + 1) + [0]
        SCREAMING_SNAKE_CASE_				:  Dict           =     [1] + [1] * (len_prefix) + [0] * (len_text + 1)

        SCREAMING_SNAKE_CASE_				:  Any           =     tokenizer(prefix_text + input_text					).token_type_ids
        SCREAMING_SNAKE_CASE_				:  List[Any]           =     tokenizer('' ,					prefix_text=prefix_text + input_text					).token_type_ids
        SCREAMING_SNAKE_CASE_				:  Tuple           =     tokenizer(_SCREAMING_SNAKE_CASE ,					prefix_text=_SCREAMING_SNAKE_CASE					).token_type_ids
        self.assertListEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
        self.assertListEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
        self.assertListEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)

  @slow
  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  int           =     self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'					)

        SCREAMING_SNAKE_CASE_				:  List[Any]           =     tokenizer.encode('あンいワ'					)
        SCREAMING_SNAKE_CASE_				:  Dict           =     tokenizer.encode('' ,					prefix_text='あンいワ'					)
        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     tokenizer.encode('いワ' ,					prefix_text='あン'					)

        self.assertEqual(tokenizer.decode(_SCREAMING_SNAKE_CASE					) ,					tokenizer.decode(_SCREAMING_SNAKE_CASE					)					)
        self.assertEqual(tokenizer.decode(_SCREAMING_SNAKE_CASE					) ,					tokenizer.decode(_SCREAMING_SNAKE_CASE					)					)
        self.assertNotEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
        self.assertNotEqual(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE					)
        self.assertEqual(x_token_a[1] ,					x_token_a[-1]					)  # SEG token
        self.assertEqual(x_token_a[1] ,					x_token_a[3]					)  # SEG token

  @slow
  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Optional[Any]           =     self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'					)

        SCREAMING_SNAKE_CASE_				:  Tuple           =     [['武田信玄', 'は、'], ['織田信長', 'の配下の、']]
        SCREAMING_SNAKE_CASE_				:  Tuple           =     tokenizer(_SCREAMING_SNAKE_CASE ,					padding=_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     tokenizer.batch_encode_plus(_SCREAMING_SNAKE_CASE ,					padding=_SCREAMING_SNAKE_CASE					)

        # fmt: off
        SCREAMING_SNAKE_CASE_				:  List[str]           =     [[3_5993, 8640, 2_5948, 3_5998, 3_0647, 3_5675, 3_5999, 3_5999], [3_5993, 1_0382, 9868, 3_5998, 3_0646, 9459, 3_0646, 3_5675]]
        SCREAMING_SNAKE_CASE_				:  int           =     [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
        SCREAMING_SNAKE_CASE_				:  Any           =     [[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
        # fmt: on
        self.assertListEqual(x_token.input_ids ,					_SCREAMING_SNAKE_CASE					)
        self.assertListEqual(x_token.token_type_ids ,					_SCREAMING_SNAKE_CASE					)
        self.assertListEqual(x_token.attention_mask ,					_SCREAMING_SNAKE_CASE					)
        self.assertListEqual(x_token_a.input_ids ,					_SCREAMING_SNAKE_CASE					)
        self.assertListEqual(x_token_a.token_type_ids ,					_SCREAMING_SNAKE_CASE					)
        self.assertListEqual(x_token_a.attention_mask ,					_SCREAMING_SNAKE_CASE					)

  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        pass



  def  UpperCAmelCase    (				self					):





        """simple docstring"""







        pass






