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


_SCREAMING_SNAKE_CASE:						List[str]    	=       logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE:						List[str]    	=       {
    '''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 	_SCREAMING_SNAKE_CASE							(     _lowercase							):






		"""simple docstring"""







		A_						 =      '''yoso'''



		def __init__(			self    :				Optional[Any]  ,					__SCREAMING_SNAKE_CASE    :				Optional[Any]=50_265  ,					__SCREAMING_SNAKE_CASE    :				Any=768  ,					__SCREAMING_SNAKE_CASE    :				Dict=12  ,					__SCREAMING_SNAKE_CASE    :				Optional[int]=12  ,					__SCREAMING_SNAKE_CASE    :				Optional[Any]=3_072  ,					__SCREAMING_SNAKE_CASE    :				Optional[int]="gelu"  ,					__SCREAMING_SNAKE_CASE    :				Dict=0.1  ,					__SCREAMING_SNAKE_CASE    :				List[Any]=0.1  ,					__SCREAMING_SNAKE_CASE    :				Union[str, Any]=4_096  ,					__SCREAMING_SNAKE_CASE    :				Dict=1  ,					__SCREAMING_SNAKE_CASE    :				Tuple=0.0_2  ,					__SCREAMING_SNAKE_CASE    :				int=1e-12  ,					__SCREAMING_SNAKE_CASE    :				Tuple="absolute"  ,					__SCREAMING_SNAKE_CASE    :				Tuple=True  ,					__SCREAMING_SNAKE_CASE    :				Tuple=9  ,					__SCREAMING_SNAKE_CASE    :				Dict=64  ,					__SCREAMING_SNAKE_CASE    :				Any=None  ,					__SCREAMING_SNAKE_CASE    :				str=True  ,					__SCREAMING_SNAKE_CASE    :				int=True  ,					__SCREAMING_SNAKE_CASE    :				Any=1  ,					__SCREAMING_SNAKE_CASE    :				Tuple=0  ,					__SCREAMING_SNAKE_CASE    :				str=2  ,					**__SCREAMING_SNAKE_CASE    :				Optional[int]  ,					):






					"""simple docstring"""
					super().__init__(pad_token_id=__SCREAMING_SNAKE_CASE  ,					bos_token_id=__SCREAMING_SNAKE_CASE  ,					eos_token_id=__SCREAMING_SNAKE_CASE  ,					**__SCREAMING_SNAKE_CASE   )

					_snake_case              =      vocab_size
					_snake_case              =      max_position_embeddings
					_snake_case              =      hidden_size
					_snake_case              =      num_hidden_layers
					_snake_case              =      num_attention_heads
					_snake_case              =      intermediate_size
					_snake_case              =      hidden_act
					_snake_case              =      hidden_dropout_prob
					_snake_case              =      attention_probs_dropout_prob
					_snake_case              =      initializer_range
					_snake_case              =      type_vocab_size
					_snake_case              =      layer_norm_eps
					_snake_case              =      position_embedding_type
					_snake_case              =      use_expectation
					_snake_case              =      hash_code_len
					_snake_case              =      num_hash
					_snake_case              =      conv_window
					_snake_case              =      use_fast_hash
					_snake_case              =      lsh_backward


import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property

class 	_SCREAMING_SNAKE_CASE							(     unittest.TestCase							):






		"""simple docstring"""







		@cached_property
		def 				_a				(			self    :				Tuple   ):






					"""simple docstring"""
					return BlenderbotTokenizer.from_pretrained("facebook/blenderbot-3B"   )



		@cached_property
		def 				_a				(			self    :				Tuple   ):






					"""simple docstring"""
					return BlenderbotTokenizerFast.from_pretrained("facebook/blenderbot-3B"   )



		def 				_a				(			self    :				Optional[Any]   ):






					"""simple docstring"""
					_snake_case              =      self.tokenizer_ab
					_snake_case              =      " I am a small frog."
					_snake_case              =      tok([src_text]  ,					padding=__SCREAMING_SNAKE_CASE  ,					truncation=__SCREAMING_SNAKE_CASE   )["input_ids"]
					_snake_case              =      tok.batch_decode(__SCREAMING_SNAKE_CASE  ,					skip_special_tokens=__SCREAMING_SNAKE_CASE  ,					clean_up_tokenization_spaces=__SCREAMING_SNAKE_CASE   )[0]
					assert src_text == decoded



		def 				_a				(			self    :				str   ):






					"""simple docstring"""
					_snake_case              =      self.rust_tokenizer_ab
					_snake_case              =      " I am a small frog."
					_snake_case              =      tok([src_text]  ,					padding=__SCREAMING_SNAKE_CASE  ,					truncation=__SCREAMING_SNAKE_CASE   )["input_ids"]
					_snake_case              =      tok.batch_decode(__SCREAMING_SNAKE_CASE  ,					skip_special_tokens=__SCREAMING_SNAKE_CASE  ,					clean_up_tokenization_spaces=__SCREAMING_SNAKE_CASE   )[0]
					assert src_text == decoded



		def 				_a				(			self    :				Optional[Any]   ):






					"""simple docstring"""
					assert self.tokenizer_ab.add_prefix_space
					assert self.tokenizer_ab([" Sam", "Sam"]   ).input_ids == [[5_502, 2], [5_502, 2]]







		def 				_a				(			self    :				str   ):






					"""simple docstring"""
					assert self.rust_tokenizer_ab.add_prefix_space
					assert self.rust_tokenizer_ab([" Sam", "Sam"]   ).input_ids == [[5_502, 2], [5_502, 2]]

