

import unittest

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






class 		__magic_name__ (				unittest.TestCase							):






     @cached_property
     def      UpperCAmelCase_							(							self     )->			Any:
         return BlenderbotTokenizer.from_pretrained("facebook/blenderbot-3B"     )






     @cached_property
     def      UpperCAmelCase_							(							self     )->			List[Any]:
         return BlenderbotTokenizerFast.from_pretrained("facebook/blenderbot-3B"     )






     def      UpperCAmelCase_							(							self     )->			List[str]:
         UpperCamelCase_          =		self.tokenizer_ab
         UpperCamelCase_          =		" I am a small frog."
         UpperCamelCase_          =		tok([src_text]						,		padding=_lowercase						,		truncation=_lowercase     )["input_ids"]
         UpperCamelCase_          =		tok.batch_decode(_lowercase						,		skip_special_tokens=_lowercase						,		clean_up_tokenization_spaces=_lowercase     )[0]
         assert src_text == decoded






     def      UpperCAmelCase_							(							self     )->			int:
         UpperCamelCase_          =		self.rust_tokenizer_ab
         UpperCamelCase_          =		" I am a small frog."
         UpperCamelCase_          =		tok([src_text]						,		padding=_lowercase						,		truncation=_lowercase     )["input_ids"]
         UpperCamelCase_          =		tok.batch_decode(_lowercase						,		skip_special_tokens=_lowercase						,		clean_up_tokenization_spaces=_lowercase     )[0]
         assert src_text == decoded






     def      UpperCAmelCase_							(							self     )->			List[str]:
         assert self.tokenizer_ab.add_prefix_space
         assert self.tokenizer_ab([" Sam", "Sam"]     ).input_ids == [[5_502, 2], [5_502, 2]]






     def      UpperCAmelCase_							(							self     )->			List[Any]:
         assert self.rust_tokenizer_ab.add_prefix_space
         assert self.rust_tokenizer_ab([" Sam", "Sam"]     ).input_ids == [[5_502, 2], [5_502, 2]]



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowerCamelCase_    =					logging.get_logger(__name__)

lowerCamelCase_    =					{
    '''google/rembert''': '''https://huggingface.co/google/rembert/resolve/main/config.json''',
    # See all RemBERT models at https://huggingface.co/models?filter=rembert
}







class  __lowerCamelCase				(	__snake_case	):
      lowerCamelCase_	:      Tuple          =					'rembert'







      def __init__(     self							,  lowerCamelCase=250300							,  lowerCamelCase=1152							,  lowerCamelCase=32							,  lowerCamelCase=18							,  lowerCamelCase=256							,  lowerCamelCase=1664							,  lowerCamelCase=4608							,  lowerCamelCase="gelu"							,  lowerCamelCase=0.0							,  lowerCamelCase=0.0							,  lowerCamelCase=0.1							,  lowerCamelCase=512							,  lowerCamelCase=2							,  lowerCamelCase=0.02							,  lowerCamelCase=1e-12							,  lowerCamelCase=True							,  lowerCamelCase=0							,  lowerCamelCase=312							,  lowerCamelCase=313							,  **lowerCamelCase							,  )						->       Union[str, Any]:
        super().__init__(pad_token_id=lowerCamelCase							,  bos_token_id=lowerCamelCase							,  eos_token_id=lowerCamelCase							,  **lowerCamelCase   )

        snake_case_       						=      vocab_size
        snake_case_       						=      input_embedding_size
        snake_case_       						=      output_embedding_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_       						=      classifier_dropout_prob
        snake_case_       						=      initializer_range
        snake_case_       						=      type_vocab_size
        snake_case_       						=      layer_norm_eps
        snake_case_       						=      use_cache
        snake_case_       						=      False







class  __lowerCamelCase				(	__snake_case	):







      @property
      def 	lowerCAmelCase_    (     self   )						->       Mapping[str, Mapping[int, str]]:
        if self.task == "multiple-choice":
          snake_case_       						=      {0: """batch""", 1: """choice""", 2: """sequence"""}
        else:
          snake_case_       						=      {0: """batch""", 1: """sequence"""}
        return OrderedDict(
            [
                ("""input_ids""", dynamic_axis),
                ("""attention_mask""", dynamic_axis),
                ("""token_type_ids""", dynamic_axis),
            ]   )







      @property
      def 	lowerCAmelCase_    (     self   )						->       float:
        return 1e-4