





from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase_        =			logging.get_logger(__name__)

lowerCAmelCase_        =			{
    """uw-madison/yoso-4096""": """https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json""",
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}



class 				_lowerCAmelCase			(	UpperCAmelCase_							):


  '''simple docstring'''
  a_							:				Tuple					    ="""yoso"""







  def __init__(					self					:    List[Any]					, UpperCamelCase					:    Any=5_02_65					, UpperCamelCase					:    str=7_68					, UpperCamelCase					:    Tuple=12					, UpperCamelCase					:    Optional[Any]=12					, UpperCamelCase					:    Dict=30_72					, UpperCamelCase					:    Any="gelu"					, UpperCamelCase					:    List[str]=0.1					, UpperCamelCase					:    int=0.1					, UpperCamelCase					:    Optional[int]=40_96					, UpperCamelCase					:    Tuple=1					, UpperCamelCase					:    Union[str, Any]=0.02					, UpperCamelCase					:    Optional[Any]=1e-1_2					, UpperCamelCase					:    str="absolute"					, UpperCamelCase					:    Optional[Any]=True					, UpperCamelCase					:    Union[str, Any]=9					, UpperCamelCase					:    Any=64					, UpperCamelCase					:    Tuple=None					, UpperCamelCase					:    List[Any]=True					, UpperCamelCase					:    Optional[Any]=True					, UpperCamelCase					:    List[Any]=1					, UpperCamelCase					:    Any=0					, UpperCamelCase					:    Tuple=2					, **UpperCamelCase					:    Tuple					, ):


    '''simple docstring'''





    super().__init__(pad_token_id=UpperCamelCase					, bos_token_id=UpperCamelCase					, eos_token_id=UpperCamelCase					, **UpperCamelCase							)

    _snake_case      : Any														=		vocab_size
    _snake_case      : int														=		max_position_embeddings
    _snake_case      : List[str]														=		hidden_size
    _snake_case      : Optional[Any]														=		num_hidden_layers
    _snake_case      : Optional[Any]														=		num_attention_heads
    _snake_case      : Any														=		intermediate_size
    _snake_case      : Dict														=		hidden_act
    _snake_case      : Optional[int]														=		hidden_dropout_prob
    _snake_case      : int														=		attention_probs_dropout_prob
    _snake_case      : Dict														=		initializer_range
    _snake_case      : Any														=		type_vocab_size
    _snake_case      : List[Any]														=		layer_norm_eps
    _snake_case      : List[Any]														=		position_embedding_type
    _snake_case      : List[Any]														=		use_expectation
    _snake_case      : int														=		hash_code_len
    _snake_case      : List[Any]														=		num_hash
    _snake_case      : Dict														=		conv_window
    _snake_case      : List[Any]														=		use_fast_hash
    _snake_case      : str														=		lsh_backward










import os
import unittest

from transformers import MPNetTokenizerFast
from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 			a__       (					UpperCamelCase__   ,					unittest.TestCase      ):
     a		:			Dict							=	MPNetTokenizer
     a		:			Dict							=	MPNetTokenizerFast
     a		:			Optional[int]							=	True
     a		:			Any							=	True







     def 			lowerCAmelCase_				(	self )  ->    Any:



          '''simple docstring'''



          super().setUp()

          a      =      [
              "[UNK]",
              "[CLS]",
              "[SEP]",
              "[PAD]",
              "[MASK]",
              "want",
              "##want",
              "##ed",
              "wa",
              "un",
              "runn",
              "##ing",
              ",",
              "low",
              "lowest",
          ]
          a      =      os.path.join(self.tmpdirname  ,		VOCAB_FILES_NAMES["vocab_file"] )
          with open(self.vocab_file  ,		"w"  ,		encoding="utf-8" ) as vocab_writer:
               vocab_writer.write("".join([x + "\n" for x in vocab_tokens] ) )







     def 			lowerCAmelCase_				(	self  ,		A )  ->    Any:



          '''simple docstring'''



          a      =      "UNwant\u00E9d,running"
          a      =      "unwanted, running"
          return input_text, output_text







     def 			lowerCAmelCase_				(	self )  ->    List[Any]:



          '''simple docstring'''



          a      =      self.tokenizer_class(self.vocab_file )

          a      =      tokenizer.tokenize("UNwant\u00E9d,running" )
          self.assertListEqual(A  ,		["un", "##want", "##ed", ",", "runn", "##ing"] )
          self.assertListEqual(tokenizer.convert_tokens_to_ids(A )  ,		[9, 6, 7, 12, 10, 11] )







     @slow
     def 			lowerCAmelCase_				(	self )  ->    Dict:



          '''simple docstring'''



          a      =      self.tokenizer_class.from_pretrained("microsoft/mpnet-base" )

          a      =      tokenizer.encode("sequence builders"  ,		add_special_tokens=A )
          a      =      tokenizer.encode("multi-sequence build"  ,		add_special_tokens=A )

          a      =      tokenizer.build_inputs_with_special_tokens(A )
          a      =      tokenizer.build_inputs_with_special_tokens(A  ,		A )

          assert encoded_sentence == [0] + text + [2]
          assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]

