from collections import OrderedDict
from typing import Mapping

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


A   :     Optional[Any]       =				logging.get_logger(__name__)

A   :     Any       =				{
    "andreasmadsen/efficient_mlm_m0.40": (
        "https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json"
    ),
}


class      lowerCamelCase    (SCREAMING_SNAKE_CASE__    ):
  """simple docstring"""







  lowerCamelCase__   =  '''roberta-prelayernorm'''







  def __init__(							self       :				Union[str, Any]     ,   __magic_name__       :				str=50_265     ,   __magic_name__       :				str=768     ,   __magic_name__       :				List[Any]=12     ,   __magic_name__       :				Optional[Any]=12     ,   __magic_name__       :				str=3_072     ,   __magic_name__       :				List[Any]="gelu"     ,   __magic_name__       :				Dict=0.1     ,   __magic_name__       :				int=0.1     ,   __magic_name__       :				int=512     ,   __magic_name__       :				Tuple=2     ,   __magic_name__       :				str=0.02     ,   __magic_name__       :				Optional[int]=1e-12     ,   __magic_name__       :				Union[str, Any]=1     ,   __magic_name__       :				Tuple=0     ,   __magic_name__       :				List[str]=2     ,   __magic_name__       :				Any="absolute"     ,   __magic_name__       :				List[Any]=True     ,   __magic_name__       :				List[Any]=None     ,   **__magic_name__       :				Tuple     ,   )     ->		Optional[Any]:
        super().__init__(pad_token_id=__magic_name__     ,   bos_token_id=__magic_name__     ,   eos_token_id=__magic_name__     ,   **__magic_name__      )

        SCREAMING_SNAKE_CASE_      =     vocab_size
        SCREAMING_SNAKE_CASE_      =     hidden_size
        SCREAMING_SNAKE_CASE_      =     num_hidden_layers
        SCREAMING_SNAKE_CASE_      =     num_attention_heads
        SCREAMING_SNAKE_CASE_      =     hidden_act
        SCREAMING_SNAKE_CASE_      =     intermediate_size
        SCREAMING_SNAKE_CASE_      =     hidden_dropout_prob
        SCREAMING_SNAKE_CASE_      =     attention_probs_dropout_prob
        SCREAMING_SNAKE_CASE_      =     max_position_embeddings
        SCREAMING_SNAKE_CASE_      =     type_vocab_size
        SCREAMING_SNAKE_CASE_      =     initializer_range
        SCREAMING_SNAKE_CASE_      =     layer_norm_eps
        SCREAMING_SNAKE_CASE_      =     position_embedding_type
        SCREAMING_SNAKE_CASE_      =     use_cache
        SCREAMING_SNAKE_CASE_      =     classifier_dropout



class      lowerCamelCase    (SCREAMING_SNAKE_CASE__    ):
  """simple docstring"""







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



from __future__ import annotations


class      lowerCamelCase    :
  """simple docstring"""







  def __init__(							self       :				Union[str, Any]     ,   __magic_name__       :				str     ,   __magic_name__       :				str      )     ->		Dict:
        SCREAMING_SNAKE_CASE_   ,       SCREAMING_SNAKE_CASE_      =     text, pattern
        SCREAMING_SNAKE_CASE_   ,       SCREAMING_SNAKE_CASE_      =     len(__magic_name__      ), len(__magic_name__      )







  def       __A   (							self       :				List[str]     ,   __magic_name__       :				str      )     ->		int:

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







  def       __A   (							self       :				Dict     ,   __magic_name__       :				int      )     ->		int:

        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       __A   (							self       :				Tuple      )     ->		list[int]:
        # searches pattern in text and returns index positions
        SCREAMING_SNAKE_CASE_      =     []
        for i in range(self.textLen - self.patLen + 1      ):
              SCREAMING_SNAKE_CASE_      =     self.mismatch_in_text(__magic_name__      )
              if mismatch_index == -1:
                    positions.append(__magic_name__      )
              else:
                    SCREAMING_SNAKE_CASE_      =     self.match_in_pattern(self.text[mismatch_index]      )
                    SCREAMING_SNAKE_CASE_      =     (
                        mismatch_index - match_index
                    )  # shifting index lgtm [py/multiple-definition]
        return positions



A   :     Dict       =				"ABAABA"
A   :     Union[str, Any]       =				"AB"
A   :     str       =				BoyerMooreSearch(text, pattern)
A   :     Tuple       =				bms.bad_character_heuristic()

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


