



"""simple docstring"""






import numpy as np






def 	snake_case_  (				A_ :		Optional[int],    A_ :		Optional[int],    A_ :		Optional[int],    A_ :		Optional[Any],    A_ :		int						):


       '''simple docstring'''





       _lowerCamelCase						:    int         =			int(np.ceil((x_end - xa) / h						)						)
       _lowerCamelCase						:    Tuple         =			np.zeros((n + 1,)						)
       _lowerCamelCase						:    Union[str, Any]         =			ya
       _lowerCamelCase						:    Union[str, Any]         =			xa

       for k in range(A_						):
              _lowerCamelCase						:    Tuple         =			f(A_,    y[k]						)
              _lowerCamelCase						:    List[str]         =			f(x + 0.5 * h,    y[k] + 0.5 * h * ka						)
              _lowerCamelCase						:    str         =			f(x + 0.5 * h,    y[k] + 0.5 * h * ka						)
              _lowerCamelCase						:    Dict         =			f(x + h,    y[k] + h * ka						)
              _lowerCamelCase						:    int         =			y[k] + (1 / 6) * h * (ka + 2 * ka + 2 * ka + ka)
              x += h

       return y


if __name__ == "__main__":
   import doctest

   doctest.testmod()







"""simple docstring"""






import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin






class 	__snake_case	(     _lowercase  ,					unittest.TestCase):
  snake_case__    :       Optional[int]        =						BlenderbotSmallTokenizer
  snake_case__    :       List[str]        =						False




  def 						SCREAMING_SNAKE_CASE    (			self					:						Dict		):






         """simple docstring"""






         super().setUp()

         _lowerCamelCase						:    str         =			['''__start__''', '''adapt''', '''act''', '''ap@@''', '''te''', '''__end__''', '''__unk__''']
         _lowerCamelCase						:    Any         =			dict(zip(__lowerCAmelCase						, range(len(__lowerCAmelCase		)		)		)		)

         _lowerCamelCase						:    Any         =			['''#version: 0.2''', '''a p''', '''t e</w>''', '''ap t</w>''', '''a d''', '''ad apt</w>''', '''a c''', '''ac t</w>''', '''''']
         _lowerCamelCase						:    List[str]         =			{'''unk_token''': '''__unk__''', '''bos_token''': '''__start__''', '''eos_token''': '''__end__'''}

         _lowerCamelCase						:    Dict         =			os.path.join(self.tmpdirname						, VOCAB_FILES_NAMES['''vocab_file''']		)
         _lowerCamelCase						:    List[str]         =			os.path.join(self.tmpdirname						, VOCAB_FILES_NAMES['''merges_file''']		)
         with open(self.vocab_file						, '''w'''						, encoding='''utf-8'''		) as fp:
                fp.write(json.dumps(__lowerCAmelCase		) + '''\n'''		)
         with open(self.merges_file						, '''w'''						, encoding='''utf-8'''		) as fp:
                fp.write('''\n'''.join(__lowerCAmelCase		)		)




  def 						SCREAMING_SNAKE_CASE    (			self					:						Tuple						, **__lowerCAmelCase					:						List[str]		):






         """simple docstring"""






         kwargs.update(self.special_tokens_map		)
         return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname						, **__lowerCAmelCase		)




  def 						SCREAMING_SNAKE_CASE    (			self					:						List[Any]						, __lowerCAmelCase					:						List[str]		):






         """simple docstring"""






         _lowerCamelCase						:    int         =			'''adapt act apte'''
         _lowerCamelCase						:    Tuple         =			'''adapt act apte'''
         return input_text, output_text




  def 						SCREAMING_SNAKE_CASE    (			self					:						int		):






         """simple docstring"""






         _lowerCamelCase						:    Tuple         =			BlenderbotSmallTokenizer(self.vocab_file						, self.merges_file						, **self.special_tokens_map		)
         _lowerCamelCase						:    int         =			'''adapt act apte'''
         _lowerCamelCase						:    Optional[Any]         =			['''adapt''', '''act''', '''ap@@''', '''te''']
         _lowerCamelCase						:    Optional[Any]         =			tokenizer.tokenize(__lowerCAmelCase		)
         self.assertListEqual(__lowerCAmelCase						, __lowerCAmelCase		)

         _lowerCamelCase						:    List[Any]         =			[tokenizer.bos_token] + tokens + [tokenizer.eos_token]

         _lowerCamelCase						:    Dict         =			[0, 1, 2, 3, 4, 5]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCAmelCase		)						, __lowerCAmelCase		)




  def 						SCREAMING_SNAKE_CASE    (			self					:						List[str]		):






         """simple docstring"""






         _lowerCamelCase						:    str         =			BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''		)
         assert tok('''sam'''		).input_ids == [1_3_8_4]
         _lowerCamelCase						:    List[str]         =			'''I am a small frog.'''
         _lowerCamelCase						:    str         =			tok([src_text]						, padding=__lowerCAmelCase						, truncation=__lowerCAmelCase		)['''input_ids''']
         _lowerCamelCase						:    Any         =			tok.batch_decode(__lowerCAmelCase						, skip_special_tokens=__lowerCAmelCase						, clean_up_tokenization_spaces=__lowerCAmelCase		)[0]
         assert src_text != decoded  # I wish it did!
         assert decoded == "i am a small frog ."




  def 						SCREAMING_SNAKE_CASE    (			self					:						Any		):






         """simple docstring"""






         _lowerCamelCase						:    Union[str, Any]         =			BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''		)
         _lowerCamelCase						:    Optional[Any]         =			'''I am a small frog .'''
         _lowerCamelCase						:    str         =			'''.'''
         _lowerCamelCase						:    str         =			tok(__lowerCAmelCase		)['''input_ids''']
         _lowerCamelCase						:    Dict         =			tok(__lowerCAmelCase		)['''input_ids''']

         assert encoded[-1] == encoded_dot[0]


