

import copy
from typing import Dict

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
from ..bit import BitConfig


A__										=      logging.get_logger(__name__)

A__										=      {
    "google/vit-hybrid-base-bit-384": "https://huggingface.co/vit-hybrid-base-bit-384/resolve/main/config.json",
    # See all ViT hybrid models at https://huggingface.co/models?filter=vit
}







class  UpperCamelCase_      (	_snake_case      ):


  """simple docstring"""
  SCREAMING_SNAKE_CASE__					:			Union[str, Any]					    =   """vit-hybrid"""



  def __init__(						self     :					Any  ,	A_     :					int=None  ,	A_     :					Optional[int]=768  ,	A_     :					Dict=12  ,	A_     :					Union[str, Any]=12  ,	A_     :					Union[str, Any]=3072  ,	A_     :					int="gelu"  ,	A_     :					Tuple=0.0  ,	A_     :					int=0.0  ,	A_     :					Dict=0.02  ,	A_     :					Union[str, Any]=1E-1_2  ,	A_     :					Optional[Any]=224  ,	A_     :					Union[str, Any]=1  ,	A_     :					List[Any]=3  ,	A_     :					List[str]=[1, 1024, 24, 24]  ,	A_     :					Optional[Any]=True  ,	**A_     :					Tuple  ,	)       ->			Dict:
      super().__init__(**A_						)

      if backbone_config is None:
          logger.info("`backbone_config` is `None`. Initializing the config with a `BiT` backbone."						)
          SCREAMING_SNAKE_CASE__         =    {
              "global_padding": "same",
              "layer_type": "bottleneck",
              "depths": [3, 4, 9],
              "out_features": ["stage3"],
              "embedding_dynamic_padding": True,
          }

      if isinstance(A_  ,	A_						):
          if "model_type" in backbone_config:
              SCREAMING_SNAKE_CASE__         =    CONFIG_MAPPING[backbone_config["model_type"]]
          else:
              logger.info(
                  "`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class."						)
              SCREAMING_SNAKE_CASE__         =    BitConfig
          SCREAMING_SNAKE_CASE__         =    backbone_config_class(**A_						)

      SCREAMING_SNAKE_CASE__         =    backbone_featmap_shape
      SCREAMING_SNAKE_CASE__         =    backbone_config
      SCREAMING_SNAKE_CASE__         =    hidden_size
      SCREAMING_SNAKE_CASE__         =    num_hidden_layers
      SCREAMING_SNAKE_CASE__         =    num_attention_heads
      SCREAMING_SNAKE_CASE__         =    intermediate_size
      SCREAMING_SNAKE_CASE__         =    hidden_act
      SCREAMING_SNAKE_CASE__         =    hidden_dropout_prob
      SCREAMING_SNAKE_CASE__         =    attention_probs_dropout_prob
      SCREAMING_SNAKE_CASE__         =    initializer_range
      SCREAMING_SNAKE_CASE__         =    layer_norm_eps
      SCREAMING_SNAKE_CASE__         =    image_size
      SCREAMING_SNAKE_CASE__         =    patch_size
      SCREAMING_SNAKE_CASE__         =    num_channels
      SCREAMING_SNAKE_CASE__         =    qkv_bias







  def   _UpperCamelCase     (						self     :					Dict						)       ->			Dict[str, any]:
      SCREAMING_SNAKE_CASE__         =    copy.deepcopy(self.__dict__						)
      SCREAMING_SNAKE_CASE__         =    self.backbone_config.to_dict()
      SCREAMING_SNAKE_CASE__         =    self.__class__.model_type
      return output





def 				__a							(       __A			,							__A			,							__A			,							__A						):
    return len_board * len_board_column * row + column





def 				__a							(       __A			,							__A			,							__A			,							__A			,							__A			,							__A			,							):

    if board[row][column] != word[word_index]:
        return False

    if word_index == len(__A						) - 1:
        return True

    SCREAMING_SNAKE_CASE__         =    [(0, 1), (0, -1), (-1, 0), (1, 0)]
    SCREAMING_SNAKE_CASE__         =    len(__A						)
    SCREAMING_SNAKE_CASE__         =    len(board[0]						)
    for direction in traverts_directions:
        SCREAMING_SNAKE_CASE__         =    row + direction[0]
        SCREAMING_SNAKE_CASE__         =    column + direction[1]
        if not (0 <= next_i < len_board and 0 <= next_j < len_board_column):
            continue

        SCREAMING_SNAKE_CASE__         =    get_point_key(__A			,							__A			,							__A			,							__A						)
        if key in visited_points_set:
            continue

        visited_points_set.add(__A						)
        if exits_word(__A			,							__A			,							__A			,							__A			,							word_index + 1			,							__A						):
            return True

        visited_points_set.remove(__A						)

    return False





def 				__a							(       __A			,							__A						):
    SCREAMING_SNAKE_CASE__         =    (
        "The board should be a non empty matrix of single chars strings."
    )

    SCREAMING_SNAKE_CASE__         =    len(__A						)
    if not isinstance(__A			,							__A						) or len(__A						) == 0:
        raise ValueError(__A						)

    for row in board:
        if not isinstance(__A			,							__A						) or len(__A						) == 0:
            raise ValueError(__A						)

        for item in row:
            if not isinstance(__A			,							__A						) or len(__A						) != 1:
                raise ValueError(__A						)

    # Validate word
    if not isinstance(__A			,							__A						) or len(__A						) == 0:
        raise ValueError(
            "The word parameter should be a string of length greater than 0."						)

    SCREAMING_SNAKE_CASE__         =    len(board[0]						)
    for i in range(__A						):
        for j in range(__A						):
            if exits_word(
                __A			,							__A			,							__A			,							__A			,							0			,							{get_point_key(__A			,							__A			,							__A			,							__A						)}						):
                return True

    return False


if __name__ == "__main__":
  import doctest

  doctest.testmod()


