



"""simple docstring"""







import functools
from math import sqrt
from time import time


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase					,							*__UpperCAmelCase					,							**__UpperCAmelCase	):
		_lowercase							:      Tuple			=					time()
		_lowercase							:      Union[str, Any]			=					func(*__UpperCAmelCase					,							**__UpperCAmelCase	)
		_lowercase							:      Dict			=					time()
		if int(end - start	) > 0:
				print(F"""{func.__name__} runtime: {(end - start):0.4f} s"""	)
		else:
				print(F"""{func.__name__} runtime: {(end - start) * 1000:0.4f} ms"""	)
		return output


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase	):
		if n < 0:
				raise Exception("""n is negative"""	)
		if n == 0:
				return [0]
		_lowercase							:      Union[str, Any]			=					[0, 1]
		for _ in range(n - 1	):
				fib.append(fib[-1] + fib[-2]	)
		return fib


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase	):

		def fib_recursive_term(__UpperCAmelCase	) -> int:
				if i < 0:
						raise Exception("""n is negative"""	)
				if i < 2:
						return i
				return fib_recursive_term(i - 1	) + fib_recursive_term(i - 2	)

		if n < 0:
				raise Exception("""n is negative"""	)
		return [fib_recursive_term(__UpperCAmelCase	) for i in range(n + 1	)]


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase	):

		@functools.cache
		def fib_recursive_term(__UpperCAmelCase	) -> int:
				if i < 0:
						raise Exception("""n is negative"""	)
				if i < 2:
						return i
				return fib_recursive_term(i - 1	) + fib_recursive_term(i - 2	)

		if n < 0:
				raise Exception("""n is negative"""	)
		return [fib_recursive_term(__UpperCAmelCase	) for i in range(n + 1	)]


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase	):
		if n < 0:
				raise Exception("""n is negative"""	)
		# Cache must be outside recursuive function
		# other it will reset every time it calls itself.
		_lowercase							:      dict[int, int]			=					{0: 0, 1: 1, 2: 1}  # Prefilled cache

		def rec_fn_memoized(__UpperCAmelCase	) -> int:
				if num in cache:
						return cache[num]

				_lowercase							:      List[Any]			=					rec_fn_memoized(num - 1	) + rec_fn_memoized(num - 2	)
				_lowercase							:      Dict			=					value
				return value

		return [rec_fn_memoized(__UpperCAmelCase	) for i in range(n + 1	)]


def       __SCREAMING_SNAKE_CASE      (   __UpperCAmelCase	):
		if n < 0:
				raise Exception("""n is negative"""	)
		if n >= 1475:
				raise Exception("""n is too large"""	)
		_lowercase							:      Optional[Any]			=					sqrt(5	)
		_lowercase							:      List[str]			=					(1 + sqrt_a) / 2
		return [round(phi**i / sqrt_a	) for i in range(n + 1	)]


if __name__ == "__main__":
		UpperCAmelCase:   Optional[Any]       			=							30
		time_func(fib_iterative, num)
		time_func(fib_recursive, num)  # Around 3s runtime
		time_func(fib_recursive_cached, num)  # Around 0ms runtime
		time_func(fib_memoization, num)
		time_func(fib_binet, num)









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_longformer import LongformerTokenizer


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

_lowerCamelCase					:     Dict					  =  {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

_lowerCamelCase					:     List[str]					  =  {
    "vocab_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
    },
    "tokenizer_file": {
        "allenai/longformer-base-4096": (
            "https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json"
        ),
    },
}

_lowerCamelCase					:     Dict					  =  {
    "allenai/longformer-base-4096": 4_0_9_6,
    "allenai/longformer-large-4096": 4_0_9_6,
    "allenai/longformer-large-4096-finetuned-triviaqa": 4_0_9_6,
    "allenai/longformer-base-4096-extra.pos.embd.only": 4_0_9_6,
    "allenai/longformer-large-4096-extra.pos.embd.only": 4_0_9_6,
}
class 				__snake_case     (_a						):
				lowerCAmelCase__			=   VOCAB_FILES_NAMES
				lowerCAmelCase__			=   PRETRAINED_VOCAB_FILES_MAP
				lowerCAmelCase__			=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCAmelCase__			=   ["input_ids", "attention_mask"]
				lowerCAmelCase__			=   LongformerTokenizer



				def __init__(					self					:						Optional[Any]						,		_UpperCAmelCase					:						Tuple=None						,		_UpperCAmelCase					:						List[str]=None						,		_UpperCAmelCase					:						List[str]=None						,		_UpperCAmelCase					:						Union[str, Any]="replace"						,		_UpperCAmelCase					:						str="<s>"						,		_UpperCAmelCase					:						str="</s>"						,		_UpperCAmelCase					:						int="</s>"						,		_UpperCAmelCase					:						str="<s>"						,		_UpperCAmelCase					:						Optional[Any]="<unk>"						,		_UpperCAmelCase					:						Optional[Any]="<pad>"						,		_UpperCAmelCase					:						Any="<mask>"						,		_UpperCAmelCase					:						Optional[int]=False						,		_UpperCAmelCase					:						List[str]=True						,		**_UpperCAmelCase					:						Optional[int]						,		)     ->			str:





								'''simple docstring'''




								super().__init__(
								    _UpperCAmelCase						,		_UpperCAmelCase						,		tokenizer_file=_UpperCAmelCase						,		errors=_UpperCAmelCase						,		bos_token=_UpperCAmelCase						,		eos_token=_UpperCAmelCase						,		sep_token=_UpperCAmelCase						,		cls_token=_UpperCAmelCase						,		unk_token=_UpperCAmelCase						,		pad_token=_UpperCAmelCase						,		mask_token=_UpperCAmelCase						,		add_prefix_space=_UpperCAmelCase						,		trim_offsets=_UpperCAmelCase						,		**_UpperCAmelCase						,		)

								_lowerCAmelCase			:			Tuple        =					json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()					)
								if pre_tok_state.get("""add_prefix_space"""						,		_UpperCAmelCase					) != add_prefix_space:
												_lowerCAmelCase			:			str        =					getattr(_UpperCAmelCase						,		pre_tok_state.pop("""type"""					)					)
												_lowerCAmelCase			:			Dict        =					add_prefix_space
												_lowerCAmelCase			:			Union[str, Any]        =					pre_tok_class(**_UpperCAmelCase					)

								_lowerCAmelCase			:			List[Any]        =					add_prefix_space

								_lowerCAmelCase			:			List[str]        =					"""post_processor"""
								_lowerCAmelCase			:			str        =					getattr(self.backend_tokenizer						,		_UpperCAmelCase						,		_UpperCAmelCase					)
								if tokenizer_component_instance:
												_lowerCAmelCase			:			Any        =					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			:			str        =					tuple(state["""sep"""]					)
												if "cls" in state:
																_lowerCAmelCase			:			int        =					tuple(state["""cls"""]					)

												_lowerCAmelCase			:			Any        =					False

												if state.get("""add_prefix_space"""						,		_UpperCAmelCase					) != add_prefix_space:
																_lowerCAmelCase			:			int        =					add_prefix_space
																_lowerCAmelCase			:			List[str]        =					True

												if state.get("""trim_offsets"""						,		_UpperCAmelCase					) != trim_offsets:
																_lowerCAmelCase			:			List[str]        =					trim_offsets
																_lowerCAmelCase			:			List[str]        =					True

												if changes_to_apply:
																_lowerCAmelCase			:			List[str]        =					getattr(_UpperCAmelCase						,		state.pop("""type"""					)					)
																_lowerCAmelCase			:			Any        =					component_class(**_UpperCAmelCase					)
																setattr(self.backend_tokenizer						,		_UpperCAmelCase						,		_UpperCAmelCase					)



				@property
				def 					SCREAMING_SNAKE_CASE				(					self					:						List[Any]					)     ->			str:





								'''simple docstring'''




								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 					SCREAMING_SNAKE_CASE				(					self					:						Any						,		_UpperCAmelCase					:						Any					)     ->			Tuple:





								'''simple docstring'''




								_lowerCAmelCase			:			Tuple        =					AddedToken(_UpperCAmelCase						,		lstrip=_UpperCAmelCase						,		rstrip=_UpperCAmelCase					) if isinstance(_UpperCAmelCase						,		_UpperCAmelCase					) else value
								_lowerCAmelCase			:			List[Any]        =					value



				def 					SCREAMING_SNAKE_CASE				(					self					:						int						,		*_UpperCAmelCase					:						str						,		**_UpperCAmelCase					:						Union[str, Any]					)     ->			BatchEncoding:





								'''simple docstring'''




								_lowerCAmelCase			:			Dict        =					kwargs.get("""is_split_into_words"""						,		_UpperCAmelCase					)
								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(*_UpperCAmelCase						,		**_UpperCAmelCase					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						str						,		*_UpperCAmelCase					:						Any						,		**_UpperCAmelCase					:						Optional[Any]					)     ->			BatchEncoding:





								'''simple docstring'''




								_lowerCAmelCase			:			Any        =					kwargs.get("""is_split_into_words"""						,		_UpperCAmelCase					)

								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(*_UpperCAmelCase						,		**_UpperCAmelCase					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						Dict						,		_UpperCAmelCase					:						str						,		_UpperCAmelCase					:						Optional[str] = None					)     ->			Tuple[str]:





								'''simple docstring'''




								_lowerCAmelCase			:			int        =					self._tokenizer.model.save(_UpperCAmelCase						,		name=_UpperCAmelCase					)
								return tuple(_UpperCAmelCase					)



				def 					SCREAMING_SNAKE_CASE				(					self					:						Any						,		_UpperCAmelCase					:						Any						,		_UpperCAmelCase					:						str=None					)     ->			List[Any]:





								'''simple docstring'''




								_lowerCAmelCase			:			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 					SCREAMING_SNAKE_CASE				(					self					:						List[Any]						,		_UpperCAmelCase					:						List[int]						,		_UpperCAmelCase					:						Optional[List[int]] = None					)     ->			List[int]:





								'''simple docstring'''




								_lowerCAmelCase			:			Dict        =					[self.sep_token_id]
								_lowerCAmelCase			:			Optional[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]

