

'''simple docstring'''



import os
import unittest

from transformers.models.bertweet.tokenization_bertweet import VOCAB_FILES_NAMES, BertweetTokenizer

from ...test_tokenization_common import TokenizerTesterMixin







class 		lowerCAmelCase__     (   a				,      unittest.TestCase      ):



 """simple docstring"""



 lowerCAmelCase__						      =   BertweetTokenizer
 lowerCAmelCase__						      =   False
 def    UpperCAmelCase__	(	self      : Dict    )						->				Optional[Any]:


      """simple docstring"""




      super().setUp()

      # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
      __SCREAMING_SNAKE_CASE						     =   ["""I""", """m""", """V@@""", """R@@""", """r""", """e@@"""]
      __SCREAMING_SNAKE_CASE						     =   dict(zip(__SCREAMING_SNAKE_CASE      ,							range(len(__SCREAMING_SNAKE_CASE    )    )    )    )
      __SCREAMING_SNAKE_CASE						     =   ["""#version: 0.2""", """a m</w>"""]
      __SCREAMING_SNAKE_CASE						     =   {"""unk_token""": """<unk>"""}

      __SCREAMING_SNAKE_CASE						     =   os.path.join(self.tmpdirname      ,							VOCAB_FILES_NAMES["""vocab_file"""]    )
      __SCREAMING_SNAKE_CASE						     =   os.path.join(self.tmpdirname      ,							VOCAB_FILES_NAMES["""merges_file"""]    )
      with open(self.vocab_file      ,							"""w"""      ,							encoding="""utf-8"""    ) as fp:
           for token in vocab_tokens:
                fp.write(f'{token} {vocab_tokens[token]}\n'    )
      with open(self.merges_file      ,							"""w"""      ,							encoding="""utf-8"""    ) as fp:
           fp.write("""\n""".join(__SCREAMING_SNAKE_CASE    )    )
 def    UpperCAmelCase__	(	self      : Optional[int]      ,							**__SCREAMING_SNAKE_CASE      : Optional[Any]    )						->				Dict:


      """simple docstring"""




      kwargs.update(self.special_tokens_map    )
      return BertweetTokenizer.from_pretrained(self.tmpdirname      ,							**__SCREAMING_SNAKE_CASE    )
 def    UpperCAmelCase__	(	self      : Optional[int]      ,							__SCREAMING_SNAKE_CASE      : Union[str, Any]    )						->				Union[str, Any]:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE						     =   """I am VinAI Research"""
      __SCREAMING_SNAKE_CASE						     =   """I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"""
      return input_text, output_text


 def    UpperCAmelCase__	(	self      : Optional[int]    )						->				Any:


      """simple docstring"""




      __SCREAMING_SNAKE_CASE						     =   BertweetTokenizer(self.vocab_file      ,							self.merges_file      ,							**self.special_tokens_map    )
      __SCREAMING_SNAKE_CASE						     =   """I am VinAI Research"""
      __SCREAMING_SNAKE_CASE						     =   """I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h""".split()
      __SCREAMING_SNAKE_CASE						     =   tokenizer.tokenize(__SCREAMING_SNAKE_CASE    )
      self.assertListEqual(__SCREAMING_SNAKE_CASE      ,							__SCREAMING_SNAKE_CASE    )

      __SCREAMING_SNAKE_CASE						     =   tokens + [tokenizer.unk_token]

      __SCREAMING_SNAKE_CASE						     =   [4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__SCREAMING_SNAKE_CASE    )      ,							__SCREAMING_SNAKE_CASE    )









'''simple docstring'''



from __future__ import annotations

from collections.abc import Callable







def      a__ (						a__   ,					a__   ,					a__   ,					a__ = 1_00   ,					):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE						     =   x_start
     __SCREAMING_SNAKE_CASE						     =   fnc(a__		)
     __SCREAMING_SNAKE_CASE						     =   0.0

     for _ in range(a__		):
          # Approximates small segments of curve as linear and solve
          # for trapezoidal area
          __SCREAMING_SNAKE_CASE						     =   (x_end - x_start) / steps + xa
          __SCREAMING_SNAKE_CASE						     =   fnc(a__		)
          area += abs(fxa + fxa		) * (xa - xa) / 2

          # Increment step
          __SCREAMING_SNAKE_CASE						     =   xa
          __SCREAMING_SNAKE_CASE						     =   fxa
     return area


if __name__ == "__main__":







  def      a__ (						a__		):




       """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:')
  UpperCAmelCase				: Optional[Any]         =  1_0
  while i <= 1_0_0_0_0_0:
    UpperCAmelCase				: Union[str, Any]         =  trapezoidal_area(f, -5, 5, i)
    print(f"""with {i} steps: {area}""")
    i *= 1_0






