






from __future__ import annotations






class 					SCREAMING_SNAKE_CASE_  :
       """simple docstring"""


       def __init__(				self	:Any,      snake_case	:str,      snake_case	:str):



          """simple docstring"""

          _lowercase       ,       _lowercase              =text, pattern
          _lowercase       ,       _lowercase              =len(snake_case), len(snake_case)





       def 				UpperCamelCase__						(				self	:Optional[int],      snake_case	:str):



          """simple docstring"""

          for i in range(self.patLen - 1,      -1,      -1):
             if char == self.pattern[i]:
                return i
          return -1





       def 				UpperCamelCase__						(				self	:List[Any],      snake_case	:int):



          """simple docstring"""

          for i in range(self.patLen - 1,      -1,      -1):
             if self.pattern[i] != self.text[current_pos + i]:
                return current_pos + i
          return -1





       def 				UpperCamelCase__						(				self	:List[Any]):



          """simple docstring"""

          _lowercase              =[]
          for i in range(self.textLen - self.patLen + 1):
             _lowercase              =self.mismatch_in_text(snake_case)
             if mismatch_index == -1:
                positions.append(snake_case)
             else:
                _lowercase              =self.match_in_pattern(self.text[mismatch_index])
                _lowercase              =(
                    mismatch_index - match_index
                )  # shifting index lgtm [py/multiple-definition]
          return positions

_SCREAMING_SNAKE_CASE   =  "ABAABA"
_SCREAMING_SNAKE_CASE   =  "AB"
_SCREAMING_SNAKE_CASE   =  BoyerMooreSearch(text, pattern)
_SCREAMING_SNAKE_CASE   =  bms.bad_character_heuristic()

if len(positions) == 0:
    print("No match found")
else:
    print("Pattern found in following positions: ")
    print(positions)










import warnings

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


_SCREAMING_SNAKE_CASE   =  logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE   =  {
    "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json",
}






class 					SCREAMING_SNAKE_CASE_  (       _a ):
       """simple docstring"""


       __lowerCAmelCase    :		List[str]					='''mvp'''
       __lowerCAmelCase    :		List[Any]					=['''past_key_values''']
       __lowerCAmelCase    :		Optional[Any]					={'''num_attention_heads''': '''encoder_attention_heads''', '''hidden_size''': '''d_model'''}





       def __init__(				self	:Any,      snake_case	:Any=5_0267,      snake_case	:List[str]=1024,      snake_case	:List[str]=12,      snake_case	:List[Any]=4096,      snake_case	:List[Any]=16,      snake_case	:Optional[int]=12,      snake_case	:Optional[int]=4096,      snake_case	:List[str]=16,      snake_case	:Optional[Any]=0.0,      snake_case	:Tuple=0.0,      snake_case	:str="gelu",      snake_case	:int=1024,      snake_case	:Any=0.1,      snake_case	:Dict=0.0,      snake_case	:Optional[Any]=0.0,      snake_case	:int=0.0_2,      snake_case	:Union[str, Any]=0.0,      snake_case	:Tuple=False,      snake_case	:Optional[int]=True,      snake_case	:Any=1,      snake_case	:Union[str, Any]=0,      snake_case	:Optional[Any]=2,      snake_case	:Union[str, Any]=True,      snake_case	:Tuple=2,      snake_case	:Any=2,      snake_case	:List[Any]=False,      snake_case	:Optional[int]=100,      snake_case	:Union[str, Any]=800,      **snake_case	:Tuple,      ):



          """simple docstring"""

          _lowercase              =vocab_size
          _lowercase              =max_position_embeddings
          _lowercase              =d_model
          _lowercase              =encoder_ffn_dim
          _lowercase              =encoder_layers
          _lowercase              =encoder_attention_heads
          _lowercase              =decoder_ffn_dim
          _lowercase              =decoder_layers
          _lowercase              =decoder_attention_heads
          _lowercase              =dropout
          _lowercase              =attention_dropout
          _lowercase              =activation_dropout
          _lowercase              =activation_function
          _lowercase              =init_std
          _lowercase              =encoder_layerdrop
          _lowercase              =decoder_layerdrop
          _lowercase              =classifier_dropout
          _lowercase              =use_cache
          _lowercase              =encoder_layers
          _lowercase              =scale_embedding  # scale factor will be sqrt(d_model) if True
          _lowercase              =use_prompt
          _lowercase              =prompt_length
          _lowercase              =prompt_mid_dim

          super().__init__(
              pad_token_id=snake_case,      bos_token_id=snake_case,      eos_token_id=snake_case,      is_encoder_decoder=snake_case,      decoder_start_token_id=snake_case,      forced_eos_token_id=snake_case,      **snake_case,      )

          if self.forced_bos_token_id is None and kwargs.get('force_bos_token_to_be_generated',      snake_case):
             _lowercase              =self.bos_token_id
             warnings.warn(
                 f'''Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. '''
                 'The config can simply be saved and uploaded again to be fixed.')


