


from typing import List

from .keymap import KEYMAP, get_character






def 		lowercase_(  SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  def decorator(SCREAMING_SNAKE_CASE_	):
    lowerCamelCase :					List[Any]    =				getattr(SCREAMING_SNAKE_CASE_      ,						"handle_key"      ,						[]	)
    handle += [key]
    setattr(SCREAMING_SNAKE_CASE_      ,						"handle_key"      ,						SCREAMING_SNAKE_CASE_	)
    return func

  return decorator






def 		lowercase_(  *SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  def decorator(SCREAMING_SNAKE_CASE_	):
    lowerCamelCase :					Any    =				getattr(SCREAMING_SNAKE_CASE_      ,						"handle_key"      ,						[]	)
    handle += keys
    setattr(SCREAMING_SNAKE_CASE_      ,						"handle_key"      ,						SCREAMING_SNAKE_CASE_	)
    return func

  return decorator
class 	UpperCAmelCase_					(					UpperCamelCase    ):

   '''simple docstring'''




   def __new__(		cls						,				__A						,				__A						,				__A ):






     """simple docstring"""





     lowerCamelCase :					str    =				super().__new__(cls						,				__A						,				__A						,				__A )
     if not hasattr(__A						,				"key_handler" ):
       setattr(__A						,				"key_handler"						,				{} )
     setattr(__A						,				"handle_input"						,				KeyHandler.handle_input )

     for value in attrs.values():
       lowerCamelCase :					List[Any]    =				getattr(__A						,				"handle_key"						,				[] )
       for key in handled_keys:
         lowerCamelCase :					int    =				value
     return new_cls






   @staticmethod
   def _snake_case    (		cls ):






     """simple docstring"""





     lowerCamelCase :					Tuple    =				get_character()
     if char != KEYMAP["undefined"]:
       lowerCamelCase :					List[Any]    =				ord(__A )
     lowerCamelCase :					Tuple    =				cls.key_handler.get(__A )
     if handler:
       lowerCamelCase :					List[Any]    =				char
       return handler(cls )
     else:
       return None






def 		lowercase_(  cls	):


  '''simple docstring'''

  return KeyHandler(cls.__name__      ,						cls.__bases__      ,						cls.__dict__.copy()	)







import json
import os
import unittest

from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow

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

   '''simple docstring'''




   __A :      List[Any]     		=		BioGptTokenizer
   __A :      Optional[int]     		=		False






   def _snake_case    (		self ):






     """simple docstring"""





     super().setUp()

     # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
     lowerCamelCase :					Union[str, Any]    =				[
         "l",
         "o",
         "w",
         "e",
         "r",
         "s",
         "t",
         "i",
         "d",
         "n",
         "w</w>",
         "r</w>",
         "t</w>",
         "lo",
         "low",
         "er</w>",
         "low</w>",
         "lowest</w>",
         "newer</w>",
         "wider</w>",
         "<unk>",
     ]
     lowerCamelCase :					str    =				dict(zip(__A						,				range(len(__A ) ) ) )
     lowerCamelCase :					Dict    =				["l o 123", "lo w 1456", "e r</w> 1789", ""]

     lowerCamelCase :					Dict    =				os.path.join(self.tmpdirname						,				VOCAB_FILES_NAMES["vocab_file"] )
     lowerCamelCase :					int    =				os.path.join(self.tmpdirname						,				VOCAB_FILES_NAMES["merges_file"] )
     with open(self.vocab_file						,				"w" ) as fp:
       fp.write(json.dumps(__A ) )
     with open(self.merges_file						,				"w" ) as fp:
       fp.write("\n".join(__A ) )






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     lowerCamelCase :					Dict    =				"lower newer"
     lowerCamelCase :					Union[str, Any]    =				"lower newer"
     return input_text, output_text






   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					List[str]    =				BioGptTokenizer(self.vocab_file						,				self.merges_file )

     lowerCamelCase :					Optional[int]    =				"lower"
     lowerCamelCase :					Any    =				["low", "er</w>"]
     lowerCamelCase :					List[str]    =				tokenizer.tokenize(__A )
     self.assertListEqual(__A						,				__A )

     lowerCamelCase :					Union[str, Any]    =				tokens + ["<unk>"]
     lowerCamelCase :					List[str]    =				[14, 15, 20]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(__A )						,				__A )






   @slow
   def _snake_case    (		self ):






     """simple docstring"""





     lowerCamelCase :					List[str]    =				BioGptTokenizer.from_pretrained("microsoft/biogpt" )

     lowerCamelCase :					Optional[int]    =				tokenizer.encode("sequence builders"						,				add_special_tokens=__A )
     lowerCamelCase :					Tuple    =				tokenizer.encode("multi-sequence build"						,				add_special_tokens=__A )

     lowerCamelCase :					Tuple    =				tokenizer.build_inputs_with_special_tokens(__A )
     lowerCamelCase :					List[str]    =				tokenizer.build_inputs_with_special_tokens(__A						,				__A )

     self.assertTrue(encoded_sentence == [2] + text )
     self.assertTrue(encoded_pair == [2] + text + [2] + text_a )



