



'''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     UpperCAmelCase_       (       _a		,		unittest.TestCase	):
    """simple docstring"""







    lowercase					=		BlenderbotSmallTokenizer
    lowercase					=		False




    def lowerCamelCase       (    self					:     Union[str, Any]						):
          super().setUp()

          snake_case__  :    Optional[Any]    						=      ["""__start__""", """adapt""", """act""", """ap@@""", """te""", """__end__""", """__unk__"""]
          snake_case__  :    List[Any]    						=      dict(zip(snake_case_ ,     range(len(snake_case_						)						)						)						)

          snake_case__  :    int    						=      ["""#version: 0.2""", """a p""", """t e</w>""", """ap t</w>""", """a d""", """ad apt</w>""", """a c""", """ac t</w>""", """"""]
          snake_case__  :    Dict    						=      {"""unk_token""": """__unk__""", """bos_token""": """__start__""", """eos_token""": """__end__"""}

          snake_case__  :    Any    						=      os.path.join(self.tmpdirname ,     VOCAB_FILES_NAMES["""vocab_file"""]						)
          snake_case__  :    Union[str, Any]    						=      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(snake_case_						) + """\n"""						)
          with open(self.merges_file ,     """w""" ,     encoding="""utf-8"""						) as fp:
                fp.write("""\n""".join(snake_case_						)						)




    def lowerCamelCase       (    self					:     List[Any] ,     **snake_case_					:     Optional[int]						):
          kwargs.update(self.special_tokens_map						)
          return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname ,     **snake_case_						)




    def lowerCamelCase       (    self					:     Tuple ,     snake_case_					:     Dict						):
          snake_case__  :    List[str]    						=      """adapt act apte"""
          snake_case__  :    Optional[int]    						=      """adapt act apte"""
          return input_text, output_text




    def lowerCamelCase       (    self					:     Any						):
          snake_case__  :    Dict    						=      BlenderbotSmallTokenizer(self.vocab_file ,     self.merges_file ,     **self.special_tokens_map						)
          snake_case__  :    str    						=      """adapt act apte"""
          snake_case__  :    Optional[int]    						=      ["""adapt""", """act""", """ap@@""", """te"""]
          snake_case__  :    List[str]    						=      tokenizer.tokenize(snake_case_						)
          self.assertListEqual(snake_case_ ,     snake_case_						)

          snake_case__  :    Optional[int]    						=      [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

          snake_case__  :    Any    						=      [0, 1, 2, 3, 4, 5]
          self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case_						) ,     snake_case_						)




    def lowerCamelCase       (    self					:     Optional[Any]						):
          snake_case__  :    Optional[int]    						=      BlenderbotSmallTokenizer.from_pretrained("""facebook/blenderbot-90M"""						)
          assert tok("""sam"""						).input_ids == [1_384]
          snake_case__  :    Optional[int]    						=      """I am a small frog."""
          snake_case__  :    List[str]    						=      tok([src_text] ,     padding=snake_case_ ,     truncation=snake_case_						)["""input_ids"""]
          snake_case__  :    Tuple    						=      tok.batch_decode(snake_case_ ,     skip_special_tokens=snake_case_ ,     clean_up_tokenization_spaces=snake_case_						)[0]
          assert src_text != decoded  # I wish it did!
          assert decoded == "i am a small frog ."




    def lowerCamelCase       (    self					:     Any						):
          snake_case__  :    Tuple    						=      BlenderbotSmallTokenizer.from_pretrained("""facebook/blenderbot-90M"""						)
          snake_case__  :    Any    						=      """I am a small frog ."""
          snake_case__  :    List[str]    						=      """."""
          snake_case__  :    Any    						=      tok(snake_case_						)["""input_ids"""]
          snake_case__  :    str    						=      tok(snake_case_						)["""input_ids"""]

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





'''simple docstring'''





from PIL import Image





def 						__snake_case(				_lowerCAmelCase     ,   _lowerCAmelCase		)		-> Image:

      def brightness(_lowerCAmelCase		) -> float:
            return 128 + level + (c - 128)

      if not -255.0 <= level <= 255.0:
            raise ValueError("""level must be between -255.0 (black) and 255.0 (white)"""		)
      return img.point(_lowerCAmelCase		)


if __name__ == "__main__":
       # Load image
       with Image.open("image_data/lena.jpg") as img:
              # Change brightness to 100
              __a          =		change_brightness(img, 100)
              brigt_img.save("image_data/lena_brightness.png", format="png")
