"""simple docstring"""




import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class __snake_case    (						__lowercase       ,		unittest.TestCase		):
   lowerCAmelCase_														=							CLIPTokenizer
   lowerCAmelCase_														=							CLIPTokenizerFast
   lowerCAmelCase_														=							True
   lowerCAmelCase_														=							{}
   lowerCAmelCase_														=							False




   def      __a						(   self      :    int				):



     """simple docstring"""






     super().setUp()

     # fmt: off
     SCREAMING_SNAKE_CASE__      							=				["""l""", """o""", """w""", """e""", """r""", """s""", """t""", """i""", """d""", """n""", """lo""", """l</w>""", """w</w>""", """r</w>""", """t</w>""", """low</w>""", """er</w>""", """lowest</w>""", """newer</w>""", """wider""", """<unk>""", """<|startoftext|>""", """<|endoftext|>"""]
     # fmt: on
     SCREAMING_SNAKE_CASE__      							=				dict(zip(UpperCAmelCase__	,     range(len(UpperCAmelCase__				)				)				)				)
     SCREAMING_SNAKE_CASE__      							=				["""#version: 0.2""", """l o""", """lo w</w>""", """e r</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:
       fp.write(json.dumps(UpperCAmelCase__				) + """\n"""				)
     with open(self.merges_file	,     """w"""	,     encoding="""utf-8"""				) as fp:
       fp.write("""\n""".join(UpperCAmelCase__				)				)




   def      __a						(   self      :    Union[str, Any]	,     **_lowercase      :    List[Any]				):



     """simple docstring"""






     kwargs.update(self.special_tokens_map				)
     return CLIPTokenizer.from_pretrained(self.tmpdirname	,     **UpperCAmelCase__				)




   def      __a						(   self      :    Any	,     **_lowercase      :    Optional[int]				):



     """simple docstring"""






     kwargs.update(self.special_tokens_map				)
     return CLIPTokenizerFast.from_pretrained(self.tmpdirname	,     **UpperCAmelCase__				)




   def      __a						(   self      :    Optional[Any]	,     _lowercase      :    Optional[Any]				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				"""lower newer"""
     SCREAMING_SNAKE_CASE__      							=				"""lower newer"""
     return input_text, output_text




   def      __a						(   self      :    Dict				):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				CLIPTokenizer(self.vocab_file	,     self.merges_file	,     **self.special_tokens_map				)
     SCREAMING_SNAKE_CASE__      							=				"""lower newer"""
     SCREAMING_SNAKE_CASE__      							=				["""lo""", """w""", """er</w>""", """n""", """e""", """w""", """er</w>"""]
     SCREAMING_SNAKE_CASE__      							=				tokenizer.tokenize(UpperCAmelCase__				)
     self.assertListEqual(UpperCAmelCase__	,     UpperCAmelCase__				)

     SCREAMING_SNAKE_CASE__      							=				tokens + [tokenizer.unk_token]
     SCREAMING_SNAKE_CASE__      							=				[10, 2, 16, 9, 3, 2, 16, 20]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase__				)	,     UpperCAmelCase__				)




   @require_ftfy
   def      __a						(   self      :    List[Any]				):



     """simple docstring"""






     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
         SCREAMING_SNAKE_CASE__      							=				self.tokenizer_class.from_pretrained(UpperCAmelCase__	,     **UpperCAmelCase__				)
         SCREAMING_SNAKE_CASE__      							=				self.rust_tokenizer_class.from_pretrained(UpperCAmelCase__	,     **UpperCAmelCase__				)

         SCREAMING_SNAKE_CASE__      							=				"""A\n\'ll 11p223RF☆ho!!to?\'d\'d\'\'d of a cat to-$\'\'d."""
         SCREAMING_SNAKE_CASE__      							=				tokenizer_s.tokenize(UpperCAmelCase__				)
         SCREAMING_SNAKE_CASE__      							=				tokenizer_r.tokenize(UpperCAmelCase__				)

         self.assertListEqual(UpperCAmelCase__	,     UpperCAmelCase__				)

         # Test that the tokenization is identical on an example containing a character (Latin Small Letter A
         # with Tilde) encoded in 2 different ways
         SCREAMING_SNAKE_CASE__      							=				"""xa\u0303y""" + """ """ + """x\xe3y"""
         SCREAMING_SNAKE_CASE__      							=				tokenizer_s.tokenize(UpperCAmelCase__				)
         SCREAMING_SNAKE_CASE__      							=				tokenizer_r.tokenize(UpperCAmelCase__				)

         self.assertListEqual(UpperCAmelCase__	,     UpperCAmelCase__				)

         # Test that the tokenization is identical on unicode of space type
         SCREAMING_SNAKE_CASE__      							=				[
             """\u0009""",  # (horizontal tab, '\t')
             """\u000B""",  # (vertical tab)
             """\u000C""",  # (form feed)
             """\u0020""",  # (space, ' ')
             """\u200E""",  # (left-to-right mark):w
             """\u200F""",  # (right-to-left mark)
         ]
         for unicode_seq in spaces_unicodes:
           SCREAMING_SNAKE_CASE__      							=				tokenizer_s.tokenize(UpperCAmelCase__				)
           SCREAMING_SNAKE_CASE__      							=				tokenizer_r.tokenize(UpperCAmelCase__				)

           self.assertListEqual(UpperCAmelCase__	,     UpperCAmelCase__				)

         # Test that the tokenization is identical on unicode of line break type
         SCREAMING_SNAKE_CASE__      							=				[
             """\u000A""",  # (line feed, '\n')
             """\r\n""",  # (carriage return and line feed, '\r\n')
             """\u000D""",  # (carriage return, '\r')
             """\r""",  # (carriage return, '\r')
             """\u000D""",  # (carriage return, '\r')
             """\u2028""",  # (line separator)
             """\u2029""",  # (paragraph separator)
             # "\u0085", # (next line)
         ]

         # The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
         # it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
         # space (and thus into an empty list).

         for unicode_seq in line_break_unicodes:
           SCREAMING_SNAKE_CASE__      							=				tokenizer_s.tokenize(UpperCAmelCase__				)
           SCREAMING_SNAKE_CASE__      							=				tokenizer_r.tokenize(UpperCAmelCase__				)

           self.assertListEqual(UpperCAmelCase__	,     UpperCAmelCase__				)




   def      __a						(   self      :    Dict				):



     """simple docstring"""






     for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
       with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""				):
         SCREAMING_SNAKE_CASE__      							=				"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
         SCREAMING_SNAKE_CASE__      							=				f"""{text_of_1_token} {text_of_1_token}"""

         SCREAMING_SNAKE_CASE__      							=				self.rust_tokenizer_class.from_pretrained(
             UpperCAmelCase__	,     use_fast=UpperCAmelCase__	,     )
         SCREAMING_SNAKE_CASE__      							=				tokenizer_r(UpperCAmelCase__	,     return_offsets_mapping=UpperCAmelCase__	,     add_special_tokens=UpperCAmelCase__				)
         self.assertEqual(encoding.offset_mapping[0]	,     (0, len(UpperCAmelCase__				))				)
         self.assertEqual(
             encoding.offset_mapping[1]	,     (len(UpperCAmelCase__				) + 1, len(UpperCAmelCase__				) + 1 + len(UpperCAmelCase__				))	,     )

         SCREAMING_SNAKE_CASE__      							=				f""" {text}"""

         SCREAMING_SNAKE_CASE__      							=				self.rust_tokenizer_class.from_pretrained(
             UpperCAmelCase__	,     use_fast=UpperCAmelCase__	,     )
         SCREAMING_SNAKE_CASE__      							=				tokenizer_r(UpperCAmelCase__	,     return_offsets_mapping=UpperCAmelCase__	,     add_special_tokens=UpperCAmelCase__				)
         self.assertEqual(encoding.offset_mapping[0]	,     (1, 1 + len(UpperCAmelCase__				))				)
         self.assertEqual(
             encoding.offset_mapping[1]	,     (1 + len(UpperCAmelCase__				) + 1, 1 + len(UpperCAmelCase__				) + 1 + len(UpperCAmelCase__				))	,     )




   def      __a						(   self      :    Any				):



     """simple docstring"""






     with self.assertRaises(UpperCAmelCase__				) as context:
       self.rust_tokenizer_class.from_pretrained("""robot-test/old-clip-tokenizer"""				)

     self.assertTrue(
         context.exception.args[0].startswith(
             """The `backend_tokenizer` provided does not match the expected format."""				)				)




   @require_ftfy
   def      __a						(   self      :    Union[str, Any]				):



     """simple docstring"""






     super().test_tokenization_python_rust_equals()




   def      __a						(   self      :    List[Any]				):



     """simple docstring"""






     pass

def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	List[Any]     )							-> Any:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				[0] * len(__UpperCamelCase     )
  SCREAMING_SNAKE_CASE__      							=				[]
  SCREAMING_SNAKE_CASE__      							=				[1] * len(__UpperCamelCase     )

  for values in graph.values():
    for i in values:
      indegree[i] += 1

  for i in range(len(__UpperCamelCase     )     ):
    if indegree[i] == 0:
      queue.append(__UpperCamelCase     )

  while queue:
    SCREAMING_SNAKE_CASE__      							=				queue.pop(0     )
    for x in graph[vertex]:
      indegree[x] -= 1

      if long_dist[vertex] + 1 > long_dist[x]:
        SCREAMING_SNAKE_CASE__      							=				long_dist[vertex] + 1

      if indegree[x] == 0:
        queue.append(__UpperCamelCase     )

  print(max(__UpperCamelCase     )     )


# Adjacency list of Graph
__lowerCamelCase      :			int							       =		{0: [2, 3, 4], 1: [2, 7], 2: [5], 3: [5, 7], 4: [7], 5: [6], 6: [7], 7: []}






longest_distance(graph)
