


'''simple docstring'''



import json
from typing import Dict, List, Optional, Tuple, Union

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_led import LEDTokenizer


__UpperCAmelCase    :Dict				       =     logging.get_logger(__name__)


__UpperCAmelCase    :List[Any]				       =     {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

__UpperCAmelCase    :Any				       =     {
    "vocab_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json",
    },
    "merges_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json",
    },
}

__UpperCAmelCase    :List[str]				       =     {
    "allenai/led-base-16384": 1_6_3_8_4,
}



class 			a       (	snake_case__ ):


     """simple docstring"""






     SCREAMING_SNAKE_CASE :				List[str]							     =     VOCAB_FILES_NAMES
     SCREAMING_SNAKE_CASE :				str							     =     PRETRAINED_VOCAB_FILES_MAP
     SCREAMING_SNAKE_CASE :				Union[str, Any]							     =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     SCREAMING_SNAKE_CASE :				List[Any]							     =     LEDTokenizer
     SCREAMING_SNAKE_CASE :				Tuple							     =     ["input_ids", "attention_mask"]

     def __init__(       self  :	int							,				snake_case  :	List[Any]=None							,				snake_case  :	Union[str, Any]=None							,				snake_case  :	Any=None							,				snake_case  :	Tuple="replace"							,				snake_case  :	Optional[Any]="<s>"							,				snake_case  :	Any="</s>"							,				snake_case  :	Any="</s>"							,				snake_case  :	Optional[int]="<s>"							,				snake_case  :	Any="<unk>"							,				snake_case  :	Optional[int]="<pad>"							,				snake_case  :	str="<mask>"							,				snake_case  :	Any=False							,				snake_case  :	str=True							,				**snake_case  :	Any							,				)		->							Tuple:
          super().__init__(
              lowercase_							,				lowercase_							,				tokenizer_file=lowercase_							,				errors=lowercase_							,				bos_token=lowercase_							,				eos_token=lowercase_							,				sep_token=lowercase_							,				cls_token=lowercase_							,				unk_token=lowercase_							,				pad_token=lowercase_							,				mask_token=lowercase_							,				add_prefix_space=lowercase_							,				trim_offsets=lowercase_							,				**lowercase_							,				)

          __UpperCAmelCase			:				str													=    json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()    )
          if pre_tok_state.get('''add_prefix_space'''							,				lowercase_    ) != add_prefix_space:
               __UpperCAmelCase			:				str													=    getattr(lowercase_							,				pre_tok_state.pop('''type'''    )    )
               __UpperCAmelCase			:				int													=    add_prefix_space
               __UpperCAmelCase			:				List[Any]													=    pre_tok_class(**lowercase_    )

          __UpperCAmelCase			:				List[str]													=    add_prefix_space

          # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
          __UpperCAmelCase			:				str													=    "post_processor"
          __UpperCAmelCase			:				Tuple													=    getattr(self.backend_tokenizer							,				lowercase_							,				lowercase_    )
          if tokenizer_component_instance:
               __UpperCAmelCase			:				Dict													=    json.loads(tokenizer_component_instance.__getstate__()    )

               # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
               if "sep" in state:
                    __UpperCAmelCase			:				str													=    tuple(state['''sep''']    )
               if "cls" in state:
                    __UpperCAmelCase			:				Optional[Any]													=    tuple(state['''cls''']    )

               __UpperCAmelCase			:				Tuple													=    False

               if state.get('''add_prefix_space'''							,				lowercase_    ) != add_prefix_space:
                    __UpperCAmelCase			:				int													=    add_prefix_space
                    __UpperCAmelCase			:				int													=    True

               if state.get('''trim_offsets'''							,				lowercase_    ) != trim_offsets:
                    __UpperCAmelCase			:				Optional[Any]													=    trim_offsets
                    __UpperCAmelCase			:				Dict													=    True

               if changes_to_apply:
                    __UpperCAmelCase			:				Tuple													=    getattr(lowercase_							,				state.pop('''type'''    )    )
                    __UpperCAmelCase			:				int													=    component_class(**lowercase_    )
                    setattr(self.backend_tokenizer							,				lowercase_							,				lowercase_    )

     @property
     # Copied from transformers.models.bart.tokenization_bart_fast.BartTokenizerFast.mask_token with BART->LED
     def 				lowerCamelCase__				(       self  :	Optional[Any]    )		->							Optional[Any]:
          if self._mask_token is None:
               if self.verbose:
                    logger.error('''Using mask_token, but it is not set yet.'''    )
               return None
          return str(self._mask_token    )

     @mask_token.setter
     def 				lowerCamelCase__				(       self  :	Optional[int]							,				snake_case  :	Optional[int]    )		->							List[str]:
          __UpperCAmelCase			:				Tuple													=    AddedToken(lowercase_							,				lstrip=lowercase_							,				rstrip=lowercase_    ) if isinstance(lowercase_							,				lowercase_    ) else value
          __UpperCAmelCase			:				Tuple													=    value

     def 				lowerCamelCase__				(       self  :	int							,				*snake_case  :	List[str]							,				**snake_case  :	Optional[int]    )		->							List[Any]:
          __UpperCAmelCase			:				Union[str, Any]													=    kwargs.get('''is_split_into_words'''							,				lowercase_    )

          if is_split_into_words and not self.add_prefix_space:
               raise ValueError(
                   f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
                   '''to use it with pretokenized inputs.'''    )

          return super()._batch_encode_plus(*lowercase_							,				**lowercase_    )

     def 				lowerCamelCase__				(       self  :	Optional[Any]							,				*snake_case  :	Any							,				**snake_case  :	Any    )		->							Union[str, Any]:
          __UpperCAmelCase			:				Optional[Any]													=    kwargs.get('''is_split_into_words'''							,				lowercase_    )

          if is_split_into_words and not self.add_prefix_space:
               raise ValueError(
                   f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
                   '''to use it with pretokenized inputs.'''    )

          return super()._encode_plus(*lowercase_							,				**lowercase_    )

     def 				lowerCamelCase__				(       self  :	Dict							,				snake_case  :	Optional[int]							,				snake_case  :	Tuple = None    )		->							List[str]:
          __UpperCAmelCase			:				Any													=    self._tokenizer.model.save(lowercase_							,				name=lowercase_    )
          return tuple(lowercase_    )

     def 				lowerCamelCase__				(       self  :	int							,				snake_case  :	List[Any]							,				snake_case  :	Dict=None    )		->							Tuple:
          __UpperCAmelCase			:				str													=    [self.bos_token_id] + token_ids_a + [self.eos_token_id]
          if token_ids_a is None:
               return output

          return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]

     def 				lowerCamelCase__				(       self  :	int							,				snake_case  :	Optional[int]							,				snake_case  :	List[str] = None    )		->							Optional[int]:
          __UpperCAmelCase			:				int													=    [self.sep_token_id]
          __UpperCAmelCase			:				List[Any]													=    [self.cls_token_id]

          if token_ids_a is None:
               return len(cls + token_ids_a + sep    ) * [0]
          return len(cls + token_ids_a + sep + sep + token_ids_a + sep    ) * [0]






     def 				lowerCamelCase__				(       self  :	Any							,				snake_case  :	Any							,				snake_case  :	List[Any] = None							,				snake_case  :	Optional[Any] = PaddingStrategy.DO_NOT_PAD							,				snake_case  :	str = None							,				snake_case  :	Any = None							,				)		->							Optional[int]:
          __UpperCAmelCase			:				str													=    super()._pad(
              encoded_inputs=lowercase_							,				max_length=lowercase_							,				padding_strategy=lowercase_							,				pad_to_multiple_of=lowercase_							,				return_attention_mask=lowercase_							,				)

          # Load from model defaults
          if return_attention_mask is None:
               __UpperCAmelCase			:				str													=    "attention_mask" in self.model_input_names

          if return_attention_mask and "global_attention_mask" in encoded_inputs:
               __UpperCAmelCase			:				Tuple													=    encoded_inputs[self.model_input_names[0]]
               # `global_attention_mask` need to have the same length as other (sequential) inputs.
               __UpperCAmelCase			:				List[str]													=    len(encoded_inputs['''global_attention_mask''']    ) != len(lowercase_    )

               if needs_to_be_padded:
                    __UpperCAmelCase			:				Optional[int]													=    len(lowercase_    ) - len(encoded_inputs['''global_attention_mask''']    )

                    if self.padding_side == "right":
                         # Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
                         __UpperCAmelCase			:				Union[str, Any]													=    (
                             encoded_inputs["global_attention_mask"] + [-1] * difference
                         )
                    elif self.padding_side == "left":
                         __UpperCAmelCase			:				List[str]													=    [-1] * difference + encoded_inputs[
                             "global_attention_mask"
                         ]
                    else:
                         raise ValueError('''Invalid padding strategy:''' + str(self.padding_side    )    )

          return encoded_inputs








'''simple docstring'''



def 			_a			(		_lowercase      :			list[list[int]]    ,      _lowercase      :			int    ,      _lowercase      :			int    ,      _lowercase      :			set						):





     '''simple docstring'''






     __UpperCAmelCase							,     __UpperCAmelCase			:				Any													=    len(_lowercase						), len(grid[0]						)
     if (
         min(_lowercase    ,      _lowercase						) < 0
         or row == row_length
         or col == col_length
         or (row, col) in visit
         or grid[row][col] == 1
     ):
          return 0
     if row == row_length - 1 and col == col_length - 1:
          return 1

     visit.add((row, col)						)

     __UpperCAmelCase			:				Optional[Any]													=    0
     count += depth_first_search(_lowercase    ,      row + 1    ,      _lowercase    ,      _lowercase						)
     count += depth_first_search(_lowercase    ,      row - 1    ,      _lowercase    ,      _lowercase						)
     count += depth_first_search(_lowercase    ,      _lowercase    ,      col + 1    ,      _lowercase						)
     count += depth_first_search(_lowercase    ,      _lowercase    ,      col - 1    ,      _lowercase						)

     visit.remove((row, col)						)
     return count


if __name__ == "__main__":
      import doctest

      doctest.testmod()