


import json
import os
import unittest

from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin
class 	UpperCAmelCase_					(					_lowerCamelCase		, unittest.TestCase    ):

   '''simple docstring'''




   __A :      Dict     		=		DebertaTokenizer
   __A :      Optional[int]     		=		True
   __A :      Any     		=		DebertaTokenizerFast






   def _snake_case    (		self ):






     """simple docstring"""





     super().setUp()

     # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
     lowerCamelCase :					int    =				[
         """l""",
         """o""",
         """w""",
         """e""",
         """r""",
         """s""",
         """t""",
         """i""",
         """d""",
         """n""",
         """\u0120""",
         """\u0120l""",
         """\u0120n""",
         """\u0120lo""",
         """\u0120low""",
         """er""",
         """\u0120lowest""",
         """\u0120newer""",
         """\u0120wider""",
         """[UNK]""",
     ]
     lowerCamelCase :					Optional[int]    =				dict(zip(a_						,				range(len(a_ ) ) ) )
     lowerCamelCase :					Tuple    =				["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
     lowerCamelCase :					Any    =				{"""unk_token""": """[UNK]"""}

     lowerCamelCase :					Dict    =				os.path.join(self.tmpdirname						,				VOCAB_FILES_NAMES["vocab_file"] )
     lowerCamelCase :					List[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(a_ ) + "\n" )
     with open(self.merges_file						,				"w"						,				encoding="utf-8" ) as fp:
       fp.write("\n".join(a_ ) )






   def _snake_case    (		self						,				**__A ):






     """simple docstring"""





     kwargs.update(self.special_tokens_map )
     return self.tokenizer_class.from_pretrained(self.tmpdirname						,				**a_ )






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     lowerCamelCase :					Tuple    =				"""lower newer"""
     lowerCamelCase :					Tuple    =				"""lower newer"""
     return input_text, output_text






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Optional[Any]    =				self.get_tokenizer()
     lowerCamelCase :					Dict    =				"""lower newer"""
     lowerCamelCase :					Optional[int]    =				["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
     lowerCamelCase :					Optional[int]    =				tokenizer.tokenize(a_ )
     self.assertListEqual(a_						,				a_ )

     lowerCamelCase :					int    =				tokens + [tokenizer.unk_token]
     lowerCamelCase :					Optional[Any]    =				[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(a_ )						,				a_ )






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Union[str, Any]    =				self.get_tokenizer()
     lowerCamelCase :					Union[str, Any]    =				tokenizer("Hello"						,				"World" )
     lowerCamelCase :					Dict    =				[0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1]
     self.assertListEqual(tokd["token_type_ids"]						,				a_ )






   @slow
   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					List[str]    =				self.tokenizer_class.from_pretrained("microsoft/deberta-base" )

     lowerCamelCase :					List[Any]    =				tokenizer.encode("sequence builders"						,				add_special_tokens=a_ )
     lowerCamelCase :					List[Any]    =				tokenizer.encode("multi-sequence build"						,				add_special_tokens=a_ )

     lowerCamelCase :					Tuple    =				tokenizer.encode(
         "sequence builders"						,				add_special_tokens=a_						,				add_prefix_space=a_ )
     lowerCamelCase :					str    =				tokenizer.encode(
         "sequence builders"						,				"multi-sequence build"						,				add_special_tokens=a_						,				add_prefix_space=a_ )

     lowerCamelCase :					Optional[int]    =				tokenizer.build_inputs_with_special_tokens(a_ )
     lowerCamelCase :					List[str]    =				tokenizer.build_inputs_with_special_tokens(a_						,				a_ )

     assert encoded_sentence == encoded_text_from_decode
     assert encoded_pair == encoded_pair_from_decode






   @slow
   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					Union[str, Any]    =				[self.tokenizer_class]
     if self.test_rust_tokenizer:
       tokenizer_classes.append(self.rust_tokenizer_class )

     for tokenizer_class in tokenizer_classes:
       lowerCamelCase :					Union[str, Any]    =				tokenizer_class.from_pretrained("microsoft/deberta-base" )

       lowerCamelCase :					List[str]    =				[
           """ALBERT: A Lite BERT for Self-supervised Learning of Language Representations""",
           """ALBERT incorporates two parameter reduction techniques""",
           """The first one is a factorized embedding parameterization. By decomposing the large vocabulary"""
           """ embedding matrix into two small matrices, we separate the size of the hidden layers from the size of"""
           """ vocabulary embedding.""",
       ]

       lowerCamelCase :					List[str]    =				tokenizer(a_						,				padding=a_ )
       lowerCamelCase :					Optional[int]    =				[tokenizer.decode(a_						,				skip_special_tokens=a_ ) for seq in encoding["""input_ids"""]]

       # fmt: off
       lowerCamelCase :					Any    =				{
           """input_ids""": [
               [1, 2118, 1_1126, 565, 35, 83, 2_5191, 163, 1_8854, 13, 1_2156, 12, 1_6101, 2_5376, 1_3807, 9, 2_2205, 2_7893, 1635, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
               [1, 2118, 1_1126, 565, 2_4536, 80, 4_3797, 4878, 7373, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
               [1, 133, 78, 65, 16, 10, 3724, 1538, 3_3183, 1_1303, 4_3797, 1938, 4, 870, 2_4165, 2_9105, 5, 739, 3_2644, 3_3183, 1_1303, 3_6173, 88, 80, 650, 7821, 4_5940, 6, 52, 2559, 5, 1836, 9, 5, 7397, 1_3171, 31, 5, 1836, 9, 3_2644, 3_3183, 1_1303, 4, 2]
           ],
           """token_type_ids""": [
               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
               [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
           ],
           """attention_mask""": [
               [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
               [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
               [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
           ]
       }
       # fmt: on

       lowerCamelCase :					Optional[Any]    =				[
           """ALBERT: A Lite BERT for Self-supervised Learning of Language Representations""",
           """ALBERT incorporates two parameter reduction techniques""",
           """The first one is a factorized embedding parameterization. By decomposing the large vocabulary"""
           """ embedding matrix into two small matrices, we separate the size of the hidden layers from the size of"""
           """ vocabulary embedding.""",
       ]

       self.assertDictEqual(encoding.data						,				a_ )

       for expected, decoded in zip(a_						,				a_ ):
         self.assertEqual(a_						,				a_ )








'''simple docstring'''






# using dfs for finding eulerian path traversal




def     snake_case_					(     lowerCAmelCase_       ,   lowerCAmelCase_       ,   lowerCAmelCase_       ,   lowerCAmelCase_=None		)->		List[str]:





       '''simple docstring'''


       _UpperCAmelCase  :						Any			     = (path or []) + [u]
       for v in graph[u]:
              if visited_edge[u][v] is False:
                     _UpperCAmelCase     ,_UpperCAmelCase  :						Tuple			     = True, True
                     _UpperCAmelCase  :						List[Any]			     = dfs(lowerCAmelCase_       ,   lowerCAmelCase_       ,   lowerCAmelCase_       ,   lowerCAmelCase_		)
       return path




def     snake_case_					(     lowerCAmelCase_       ,   lowerCAmelCase_		)->		Optional[int]:





       '''simple docstring'''


       _UpperCAmelCase  :						Optional[Any]			     = 0
       _UpperCAmelCase  :						Optional[int]			     = -1
       for i in range(lowerCAmelCase_		):
              if i not in graph.keys():
                     continue
              if len(graph[i]		) % 2 == 1:
                     odd_degree_nodes += 1
                     _UpperCAmelCase  :						Optional[int]			     = i
       if odd_degree_nodes == 0:
              return 1, odd_node
       if odd_degree_nodes == 2:
              return 2, odd_node
       return 3, odd_node




def     snake_case_					(     lowerCAmelCase_       ,   lowerCAmelCase_		)->		List[Any]:





       '''simple docstring'''


       _UpperCAmelCase  :						str			     = [[False for _ in range(max_node + 1		)] for _ in range(max_node + 1		)]
       _UpperCAmelCase     ,_UpperCAmelCase  :						int			     = check_circuit_or_path(lowerCAmelCase_       ,   lowerCAmelCase_		)
       if check == 3:
              print("""graph is not Eulerian"""		)
              print("""no path"""		)
              return
       _UpperCAmelCase  :						Dict			     = 1
       if check == 2:
              _UpperCAmelCase  :						Dict			     = odd_node
              print("""graph has a Euler path"""		)
       if check == 1:
              print("""graph has a Euler cycle"""		)
       _UpperCAmelCase  :						Dict			     = dfs(lowerCAmelCase_       ,   lowerCAmelCase_       ,   lowerCAmelCase_		)
       print(lowerCAmelCase_		)




def     snake_case_					(     )->		Union[str, Any]:





       '''simple docstring'''


       _UpperCAmelCase  :						Any			     = {1: [2, 3, 4], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [4]}
       _UpperCAmelCase  :						int			     = {1: [2, 3, 4, 5], 2: [1, 3], 3: [1, 2], 4: [1, 5], 5: [1, 4]}
       _UpperCAmelCase  :						Tuple			     = {1: [2, 3, 4], 2: [1, 3, 4], 3: [1, 2], 4: [1, 2, 5], 5: [4]}
       _UpperCAmelCase  :						List[Any]			     = {1: [2, 3], 2: [1, 3], 3: [1, 2]}
       _UpperCAmelCase  :						List[str]			     = {
           1: [],
           2: []
           # all degree is zero
       }
       _UpperCAmelCase  :						Union[str, Any]			     = 10
       check_euler(lowerCAmelCase_       ,   lowerCAmelCase_		)
       check_euler(lowerCAmelCase_       ,   lowerCAmelCase_		)
       check_euler(lowerCAmelCase_       ,   lowerCAmelCase_		)
       check_euler(lowerCAmelCase_       ,   lowerCAmelCase_		)
       check_euler(lowerCAmelCase_       ,   lowerCAmelCase_		)


if __name__ == "__main__":
   main()



