





'''simple docstring'''


import json
import os
import unittest

from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import (
    VOCAB_FILES_NAMES,
    GPTNeoXJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class 		UpperCamelCase__     (       a	,	unittest.TestCase							):
      '''simple docstring'''






      _snake_case           =				GPTNeoXJapaneseTokenizer
      _snake_case           =				False
      _snake_case           =				{'''do_clean_text''': False, '''add_prefix_space''': False}




      def 	snake_case  (     self )				->  List[str]:
        super().setUp()

        __lowerCAmelCase		:    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>',
            '<|startoftext|>',
            '<|endoftext|>',
        ]
        __lowerCAmelCase		:    Optional[Any]			     =  {'emoji': {'\ud83d\ude00': '<|emoji1|>'}, 'emoji_inv': {'<|emoji1|>': '\ud83d\ude00'}}  # 😀
        __lowerCAmelCase		:    Tuple			     =  {'unk_token': '<unk>'}

        __lowerCAmelCase		:    List[Any]			     =  os.path.join(self.tmpdirname     , VOCAB_FILES_NAMES['vocab_file'] )
        __lowerCAmelCase		:    Any			     =  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 	snake_case  (     self     , **SCREAMING_SNAKE_CASE )				->  Optional[int]:
        kwargs.update(self.special_tokens_map )
        return GPTNeoXJapaneseTokenizer.from_pretrained(self.tmpdirname     , **SCREAMING_SNAKE_CASE )




      def 	snake_case  (     self     , SCREAMING_SNAKE_CASE )				->  List[str]:
        __lowerCAmelCase		:    Dict			     =  'こんにちは、世界。 \nこんばんは、㔺界。😀'
        __lowerCAmelCase		:    Optional[Any]			     =  'こんにちは、世界。 \nこんばんは、世界。😀'
        return input_text, output_text




      def 	snake_case  (     self     , SCREAMING_SNAKE_CASE )				->  Dict:
        __lowerCAmelCase     ,					__lowerCAmelCase		:    List[str]			     =  self.get_input_output_texts(SCREAMING_SNAKE_CASE )
        __lowerCAmelCase		:    Tuple			     =  tokenizer.encode(SCREAMING_SNAKE_CASE     , add_special_tokens=SCREAMING_SNAKE_CASE )
        __lowerCAmelCase		:    List[str]			     =  tokenizer.decode(SCREAMING_SNAKE_CASE     , clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE )
        return text, ids




      def 	snake_case  (     self )				->  Tuple:
        pass  # TODO add if relevant




      def 	snake_case  (     self )				->  List[str]:
        pass  # TODO add if relevant




      def 	snake_case  (     self )				->  List[Any]:
        pass  # TODO add if relevant




      def 	snake_case  (     self )				->  Dict:
        __lowerCAmelCase		:    Dict			     =  self.get_tokenizer()

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

        # Testing conversion to ids without special tokens
        __lowerCAmelCase		:    str			     =  [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
        __lowerCAmelCase		:    int			     =  tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE )
        self.assertListEqual(SCREAMING_SNAKE_CASE     , SCREAMING_SNAKE_CASE )

        # Testing conversion to ids with special tokens
        __lowerCAmelCase		:    Optional[int]			     =  tokens + [tokenizer.unk_token]
        __lowerCAmelCase		:    int			     =  [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
        __lowerCAmelCase		:    Tuple			     =  tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE )
        self.assertListEqual(SCREAMING_SNAKE_CASE     , SCREAMING_SNAKE_CASE )




      @slow
      def 	snake_case  (     self )				->  List[str]:
        __lowerCAmelCase		:    Any			     =  self.tokenizer_class.from_pretrained('abeja/gpt-neox-japanese-2.7b' )

        __lowerCAmelCase		:    Optional[Any]			     =  tokenizer.encode('ありがとう。'     , add_special_tokens=SCREAMING_SNAKE_CASE )
        __lowerCAmelCase		:    int			     =  tokenizer.encode('どういたしまして。'     , add_special_tokens=SCREAMING_SNAKE_CASE )

        __lowerCAmelCase		:    Optional[Any]			     =  tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE )
        __lowerCAmelCase		:    List[Any]			     =  tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE     , SCREAMING_SNAKE_CASE )

        assert encoded_sentence == ids_a
        assert encoded_pair == ids_a + ids_a




      def 	snake_case  (     self )				->  Optional[int]:
        # Intentionally convert some words to accommodate character fluctuations unique to Japanese
        pass







      def 	snake_case  (     self )				->  int:
        # tokenizer has no padding token
        pass












'''simple docstring'''


from __future__ import annotations

from collections.abc import Callable




def       A							(      _UpperCAmelCase   :				Callable[[int | float], int | float]						,_UpperCAmelCase   :				int | float						,_UpperCAmelCase   :				int | float						,_UpperCAmelCase   :				int = 1_0_0						,)  ->				float:


  '''simple docstring'''




  __lowerCAmelCase		:    Dict			     =  x_start
  __lowerCAmelCase		:    Tuple			     =  fnc(_UpperCAmelCase					)
  __lowerCAmelCase		:    Optional[int]			     =  0.0

  for _ in range(_UpperCAmelCase					):
    # Approximates small segments of curve as linear and solve
    # for trapezoidal area
    __lowerCAmelCase		:    Optional[int]			     =  (x_end - x_start) / steps + xa
    __lowerCAmelCase		:    Optional[Any]			     =  fnc(_UpperCAmelCase					)
    area += abs(fxa + fxa					) * (xa - xa) / 2

    # Increment step
    __lowerCAmelCase		:    Optional[Any]			     =  xa
    __lowerCAmelCase		:    List[Any]			     =  fxa
  return area


if __name__ == "__main__":




    def       A							(      _UpperCAmelCase   :				List[Any]					)  ->				List[Any]:


      '''simple docstring'''




      return x**3

    print("f(x) = x^3")
    print("The area between the curve, x = -10, x = 10 and the x axis is:")
    A_				     =							10
    while i <= 10_00_00:
        A_				     =							trapezoidal_area(f, -5, 5, i)
        print(F'''with {i} steps: {area}''')
        i *= 10





