



"""simple docstring"""






import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


_lowercase : List[str]      						=						logging.get_logger(__name__)

_lowercase : Any      						=						{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

_lowercase : Union[str, Any]      						=						{
    "vocab_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/vocab.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/vocab.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/vocab.json",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/merges.txt",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/merges.txt",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/merges.txt",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt"
        ),
    },
    "tokenizer_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/tokenizer.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/tokenizer.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json",
        "roberta-base-openai-detector": (
            "https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json"
        ),
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json"
        ),
    },
}

_lowercase : Optional[int]      						=						{
    "roberta-base": 5_1_2,
    "roberta-large": 5_1_2,
    "roberta-large-mnli": 5_1_2,
    "distilroberta-base": 5_1_2,
    "roberta-base-openai-detector": 5_1_2,
    "roberta-large-openai-detector": 5_1_2,
}

class        __SCREAMING_SNAKE_CASE	(      lowerCAmelCase_   ):


					'''simple docstring'''





					_a   			=							VOCAB_FILES_NAMES
					_a   			=							PRETRAINED_VOCAB_FILES_MAP
					_a   			=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					_a   			=							['input_ids', 'attention_mask']
					_a   			=							RobertaTokenizer



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

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

								lowerCamelCase__		:		str			=add_prefix_space

								lowerCamelCase__		:		List[Any]			='''post_processor'''
								lowerCamelCase__		:		Any			=getattr(self.backend_tokenizer,  lowerCamelCase,  lowerCamelCase     )
								if tokenizer_component_instance:
											lowerCamelCase__		:		int			=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:
														lowerCamelCase__		:		Optional[Any]			=tuple(state['''sep''']     )
											if "cls" in state:
														lowerCamelCase__		:		Dict			=tuple(state['''cls''']     )

											lowerCamelCase__		:		Tuple			=False

											if state.get('''add_prefix_space''',  lowerCamelCase     ) != add_prefix_space:
														lowerCamelCase__		:		Dict			=add_prefix_space
														lowerCamelCase__		:		int			=True

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

											if changes_to_apply:
														lowerCamelCase__		:		str			=getattr(lowerCamelCase,  state.pop('''type'''     )     )
														lowerCamelCase__		:		Dict			=component_class(**lowerCamelCase     )
														setattr(self.backend_tokenizer,  lowerCamelCase,  lowerCamelCase     )



					@property
					def 		snake_case       (       self							:  str     )->					str:
								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 		snake_case       (       self							:  Optional[Any],  lowerCamelCase							:  str     )->					Any:
								lowerCamelCase__		:		List[str]			=AddedToken(lowerCamelCase,  lstrip=lowerCamelCase,  rstrip=lowerCamelCase     ) if isinstance(lowerCamelCase,  lowerCamelCase     ) else value
								lowerCamelCase__		:		List[Any]			=value



					def 		snake_case       (       self							:  str,  *lowerCamelCase							:  List[str],  **lowerCamelCase							:  List[str]     )->					BatchEncoding:
								lowerCamelCase__		:		Dict			=kwargs.get('''is_split_into_words''',  lowerCamelCase     )
								assert self.add_prefix_space or not is_split_into_words, (
								    F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
								    "to use it with pretokenized inputs."
								)

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



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

								assert self.add_prefix_space or not is_split_into_words, (
								    F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
								    "to use it with pretokenized inputs."
								)

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



					def 		snake_case       (       self							:  Tuple,  lowerCamelCase							:  str,  lowerCamelCase							:  Optional[str] = None     )->					Tuple[str]:
								lowerCamelCase__		:		Union[str, Any]			=self._tokenizer.model.save(lowerCamelCase,  name=lowerCamelCase     )
								return tuple(lowerCamelCase     )



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









"""simple docstring"""






def      snake_case__   (		):
			"""simple docstring"""
			return [list(range(1000 - i							,		-1000 - i							,		-1	)	) for i in range(1000	)]


_lowercase : str      						=						generate_large_matrix()
_lowercase : str      						=						(
    [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
    [[3, 2], [1, 0]],
    [[7, 7, 6]],
    [[7, 7, 6], [-1, -2, -3]],
    grid,
)






def      snake_case__   (		__lowerCamelCase				:    list[list[int]]	):
			"""simple docstring"""
			assert all(row == sorted(__lowerCamelCase							,		reverse=__lowerCamelCase	) for row in grid	)
			assert all(list(__lowerCamelCase	) == sorted(__lowerCamelCase							,		reverse=__lowerCamelCase	) for col in zip(*__lowerCamelCase	)	)






def      snake_case__   (		__lowerCamelCase				:    list[int]	):
			"""simple docstring"""
			lowerCamelCase__		:		int			=0
			lowerCamelCase__		:		Optional[int]			=len(__lowerCamelCase	) - 1

			# Edge cases such as no values or all numbers are negative.
			if not array or array[0] < 0:
						return 0

			while right + 1 > left:
						lowerCamelCase__		:		List[str]			=(left + right) // 2
						lowerCamelCase__		:		Union[str, Any]			=array[mid]

						# Num must be negative and the index must be greater than or equal to 0.
						if num < 0 and array[mid - 1] >= 0:
									return mid

						if num >= 0:
									lowerCamelCase__		:		Union[str, Any]			=mid + 1
						else:
									lowerCamelCase__		:		Dict			=mid - 1
    # No negative numbers so return the last index of the array + 1 which is the length.
			return len(__lowerCamelCase	)






def      snake_case__   (		__lowerCamelCase				:    list[list[int]]	):
			"""simple docstring"""
			lowerCamelCase__		:		Union[str, Any]			=0
			lowerCamelCase__		:		str			=len(grid[0]	)

			for i in range(len(__lowerCamelCase	)	):
						lowerCamelCase__		:		Any			=find_negative_index(grid[i][:bound]	)
						total += bound
			return (len(__lowerCamelCase	) * len(grid[0]	)) - total






def      snake_case__   (		__lowerCamelCase				:    list[list[int]]	):
			"""simple docstring"""
			return len([number for row in grid for number in row if number < 0]	)






def      snake_case__   (		__lowerCamelCase				:    list[list[int]]	):
			"""simple docstring"""
			lowerCamelCase__		:		Tuple			=0
			for row in grid:
						for i, number in enumerate(__lowerCamelCase	):
									if number < 0:
												total += len(__lowerCamelCase	) - i
												break
			return total






def      snake_case__   (		):
			"""simple docstring"""
			from timeit import timeit

			print('''Running benchmarks'''	)
			lowerCamelCase__		:		List[str]			=(
			    '''from __main__ import count_negatives_binary_search, '''
			    '''count_negatives_brute_force, count_negatives_brute_force_with_break, grid'''
			)
			for func in (
			    "count_negatives_binary_search",  # took 0.7727 seconds
			    "count_negatives_brute_force_with_break",  # took 4.6505 seconds
			    "count_negatives_brute_force",  # took 12.8160 seconds
			):
						lowerCamelCase__		:		Union[str, Any]			=timeit(f'''{func}(grid=grid)'''							,		setup=__lowerCamelCase							,		number=500	)
						print(f'''{func}() took {time:0.4f} seconds'''	)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		benchmark()




