



import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 							lowerCAmelCase__  (	UpperCamelCase					,							unittest.TestCase						):
					__A     :    int           =						LongformerTokenizer
					__A     :    Any           =						True
					__A     :    Optional[int]           =						LongformerTokenizerFast
					__A     :    Tuple           =						True







					def  _lowercase			(       self      :     Dict):
											super().setUp()

											# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
											A__	:							Optional[Any]						    = [
											    "l",
											    "o",
											    "w",
											    "e",
											    "r",
											    "s",
											    "t",
											    "i",
											    "d",
											    "n",
											    "\u0120",
											    "\u0120l",
											    "\u0120n",
											    "\u0120lo",
											    "\u0120low",
											    "er",
											    "\u0120lowest",
											    "\u0120newer",
											    "\u0120wider",
											    "<unk>",
											]
											A__	:							Any						    = dict(zip(_A			,		range(len(_A))))
											A__	:							Tuple						    = ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
											A__	:							Optional[int]						    = {"unk_token": "<unk>"}

											A__	:							Any						    = os.path.join(self.tmpdirname			,		VOCAB_FILES_NAMES["vocab_file"])
											A__	:							Union[str, Any]						    = os.path.join(self.tmpdirname			,		VOCAB_FILES_NAMES["merges_file"])
											with open(self.vocab_file			,		"w"			,		encoding="utf-8") as fp:
																	fp.write(json.dumps(_A) + "\n")
											with open(self.merges_file			,		"w"			,		encoding="utf-8") as fp:
																	fp.write("\n".join(_A))







					def  _lowercase			(       self      :     List[str]			,		**_A      :     Optional[Any]):
											kwargs.update(self.special_tokens_map)
											return self.tokenizer_class.from_pretrained(self.tmpdirname			,		**_A)







					def  _lowercase			(       self      :     List[str]			,		**_A      :     Dict):
											kwargs.update(self.special_tokens_map)
											return self.rust_tokenizer_class.from_pretrained(self.tmpdirname			,		**_A)







					def  _lowercase			(       self      :     Optional[int]			,		_A      :     Dict):
											A__	:							Optional[Any]						    = "lower newer"
											A__	:							Union[str, Any]						    = "lower newer"
											return input_text, output_text







					def  _lowercase			(       self      :     Tuple):
											A__	:							Union[str, Any]						    = self.tokenizer_class(self.vocab_file			,		self.merges_file			,		**self.special_tokens_map)
											A__	:							Optional[int]						    = "lower newer"
											A__	:							int						    = ["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
											A__	:							List[str]						    = tokenizer.tokenize(_A)  # , add_prefix_space=True)
											self.assertListEqual(_A			,		_A)

											A__	:							Any						    = tokens + [tokenizer.unk_token]
											A__	:							Optional[int]						    = [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
											self.assertListEqual(tokenizer.convert_tokens_to_ids(_A)			,		_A)







					def  _lowercase			(       self      :     Optional[int]):
											A__	:							Optional[Any]						    = self.get_tokenizer()

											self.assertListEqual(tokenizer.encode("Hello world!"			,		add_special_tokens=_A)			,		[0, 3_1414, 232, 328, 2])
											self.assertListEqual(
											    tokenizer.encode("Hello world! cécé herlolip 418"			,		add_special_tokens=_A)			,		[0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]			,		)







					@slow
					def  _lowercase			(       self      :     str):
											A__	:							List[str]						    = self.tokenizer_class.from_pretrained("allenai/longformer-base-4096")

											A__	:							Optional[Any]						    = tokenizer.encode("sequence builders"			,		add_special_tokens=_A)
											A__	:							Optional[int]						    = tokenizer.encode("multi-sequence build"			,		add_special_tokens=_A)

											A__	:							Tuple						    = tokenizer.encode(
											    "sequence builders"			,		add_special_tokens=_A			,		add_prefix_space=_A)
											A__	:							str						    = tokenizer.encode(
											    "sequence builders"			,		"multi-sequence build"			,		add_special_tokens=_A			,		add_prefix_space=_A)

											A__	:							Dict						    = tokenizer.build_inputs_with_special_tokens(_A)
											A__	:							Optional[int]						    = tokenizer.build_inputs_with_special_tokens(_A			,		_A)

											assert encoded_sentence == encoded_text_from_decode
											assert encoded_pair == encoded_pair_from_decode







					def  _lowercase			(       self      :     Union[str, Any]):
											A__	:							Any						    = self.get_tokenizer()

											A__	:							List[str]						    = "Encode this sequence."
											A__	:							Dict						    = tokenizer.byte_encoder[" ".encode("utf-8")[0]]

											# Testing encoder arguments
											A__	:							List[str]						    = tokenizer.encode(_A			,		add_special_tokens=_A			,		add_prefix_space=_A)
											A__	:							Optional[int]						    = tokenizer.convert_ids_to_tokens(encoded[0])[0]
											self.assertNotEqual(_A			,		_A)

											A__	:							str						    = tokenizer.encode(_A			,		add_special_tokens=_A			,		add_prefix_space=_A)
											A__	:							Optional[Any]						    = tokenizer.convert_ids_to_tokens(encoded[0])[0]
											self.assertEqual(_A			,		_A)

											tokenizer.add_special_tokens({"bos_token": "<s>"})
											A__	:							str						    = tokenizer.encode(_A			,		add_special_tokens=_A)
											A__	:							Any						    = tokenizer.convert_ids_to_tokens(encoded[1])[0]
											self.assertNotEqual(_A			,		_A)

											# Testing spaces after special tokens
											A__	:							str						    = "<mask>"
											tokenizer.add_special_tokens(
											    {"mask_token": AddedToken(_A			,		lstrip=_A			,		rstrip=_A)})  # mask token has a left space
											A__	:							Dict						    = tokenizer.convert_tokens_to_ids(_A)

											A__	:							Dict						    = "Encode <mask> sequence"
											A__	:							Tuple						    = "Encode <mask>sequence"

											A__	:							List[str]						    = tokenizer.encode(_A)
											A__	:							Tuple						    = encoded.index(_A)
											A__	:							List[Any]						    = tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1])[0]
											self.assertEqual(_A			,		_A)

											A__	:							Any						    = tokenizer.encode(_A)
											A__	:							Dict						    = encoded.index(_A)
											A__	:							str						    = tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1])[0]
											self.assertNotEqual(_A			,		_A)







					def  _lowercase			(       self      :     Union[str, Any]):
											pass







					def  _lowercase			(       self      :     Any):
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'):
																							A__	:							List[Any]						    = self.rust_tokenizer_class.from_pretrained(_A			,		**_A)
																							A__	:							Tuple						    = self.tokenizer_class.from_pretrained(_A			,		**_A)
																							A__	:							Tuple						    = "A, <mask> AllenNLP sentence."
																							A__	:							int						    = tokenizer_r.encode_plus(_A			,		add_special_tokens=_A			,		return_token_type_ids=_A)
																							A__	:							str						    = tokenizer_p.encode_plus(_A			,		add_special_tokens=_A			,		return_token_type_ids=_A)

																							# token_type_ids should put 0 everywhere
																							self.assertEqual(sum(tokens_r["token_type_ids"])			,		sum(tokens_p["token_type_ids"]))

																							# attention_mask should put 1 everywhere, so sum over length should be 1
																							self.assertEqual(
																							    sum(tokens_r["attention_mask"]) / len(tokens_r["attention_mask"])			,		sum(tokens_p["attention_mask"]) / len(tokens_p["attention_mask"])			,		)

																							A__	:							str						    = tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"])
																							A__	:							Optional[int]						    = tokenizer_p.convert_ids_to_tokens(tokens_p["input_ids"])

																							# Rust correctly handles the space before the mask while python doesnt
																							self.assertSequenceEqual(tokens_p["input_ids"]			,		[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2])
																							self.assertSequenceEqual(tokens_r["input_ids"]			,		[0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2])

																							self.assertSequenceEqual(
																							    _A			,		["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"])
																							self.assertSequenceEqual(
																							    _A			,		["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"])







					def  _lowercase			(       self      :     int):
											for trim_offsets, add_prefix_space in itertools.product([True, False]			,		repeat=2):
																	A__	:							Dict						    = self.rust_tokenizer_class.from_pretrained(
																	    self.tmpdirname			,		use_fast=_A			,		add_prefix_space=_A			,		trim_offsets=_A)

																	A__	:							int						    = json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__())
																	A__	:							Dict						    = json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__())

																	self.assertEqual(pre_tokenizer_state["add_prefix_space"]			,		_A)

																	self.assertEqual(post_processor_state["add_prefix_space"]			,		_A)
																	self.assertEqual(post_processor_state["trim_offsets"]			,		_A)







					def  _lowercase			(       self      :     Optional[Any]):
											# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
											# `trim_offsets`
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'):
																							A__	:							str						    = "hello"  # `hello` is a token in the vocabulary of `pretrained_name`
																							A__	:							List[Any]						    = F'{text_of_1_token} {text_of_1_token}'

																							A__	:							Union[str, Any]						    = self.rust_tokenizer_class.from_pretrained(
																							    _A			,		use_fast=_A			,		add_prefix_space=_A			,		trim_offsets=_A)
																							A__	:							Any						    = tokenizer_r(_A			,		return_offsets_mapping=_A			,		add_special_tokens=_A)
																							self.assertEqual(encoding.offset_mapping[0]			,		(0, len(_A)))
																							self.assertEqual(
																							    encoding.offset_mapping[1]			,		(len(_A) + 1, len(_A) + 1 + len(_A))			,		)

																							A__	:							Tuple						    = self.rust_tokenizer_class.from_pretrained(
																							    _A			,		use_fast=_A			,		add_prefix_space=_A			,		trim_offsets=_A)
																							A__	:							int						    = tokenizer_r(_A			,		return_offsets_mapping=_A			,		add_special_tokens=_A)
																							self.assertEqual(encoding.offset_mapping[0]			,		(0, len(_A)))
																							self.assertEqual(
																							    encoding.offset_mapping[1]			,		(len(_A) + 1, len(_A) + 1 + len(_A))			,		)

																							A__	:							Union[str, Any]						    = self.rust_tokenizer_class.from_pretrained(
																							    _A			,		use_fast=_A			,		add_prefix_space=_A			,		trim_offsets=_A)
																							A__	:							Tuple						    = tokenizer_r(_A			,		return_offsets_mapping=_A			,		add_special_tokens=_A)
																							self.assertEqual(encoding.offset_mapping[0]			,		(0, len(_A)))
																							self.assertEqual(
																							    encoding.offset_mapping[1]			,		(len(_A), len(_A) + 1 + len(_A))			,		)

																							A__	:							Optional[Any]						    = self.rust_tokenizer_class.from_pretrained(
																							    _A			,		use_fast=_A			,		add_prefix_space=_A			,		trim_offsets=_A)
																							A__	:							List[Any]						    = tokenizer_r(_A			,		return_offsets_mapping=_A			,		add_special_tokens=_A)
																							self.assertEqual(encoding.offset_mapping[0]			,		(0, len(_A)))
																							self.assertEqual(
																							    encoding.offset_mapping[1]			,		(len(_A), len(_A) + 1 + len(_A))			,		)

																							A__	:							List[str]						    = F' {text}'

																							# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
																							#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
																							# )
																							# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
																							# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
																							# self.assertEqual(
																							#     encoding.offset_mapping[1],
																							#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
																							# )

																							A__	:							Union[str, Any]						    = self.rust_tokenizer_class.from_pretrained(
																							    _A			,		use_fast=_A			,		add_prefix_space=_A			,		trim_offsets=_A)
																							A__	:							Union[str, Any]						    = tokenizer_r(_A			,		return_offsets_mapping=_A			,		add_special_tokens=_A)
																							self.assertEqual(encoding.offset_mapping[0]			,		(1, 1 + len(_A)))
																							self.assertEqual(
																							    encoding.offset_mapping[1]			,		(1 + len(_A) + 1, 1 + len(_A) + 1 + len(_A))			,		)

																							A__	:							Tuple						    = self.rust_tokenizer_class.from_pretrained(
																							    _A			,		use_fast=_A			,		add_prefix_space=_A			,		trim_offsets=_A)
																							A__	:							int						    = tokenizer_r(_A			,		return_offsets_mapping=_A			,		add_special_tokens=_A)
																							self.assertEqual(encoding.offset_mapping[0]			,		(0, 1 + len(_A)))
																							self.assertEqual(
																							    encoding.offset_mapping[1]			,		(1 + len(_A), 1 + len(_A) + 1 + len(_A))			,		)

																							A__	:							List[Any]						    = self.rust_tokenizer_class.from_pretrained(
																							    _A			,		use_fast=_A			,		add_prefix_space=_A			,		trim_offsets=_A)
																							A__	:							Dict						    = tokenizer_r(_A			,		return_offsets_mapping=_A			,		add_special_tokens=_A)
																							self.assertEqual(encoding.offset_mapping[0]			,		(0, 1 + len(_A)))
																							self.assertEqual(
																							    encoding.offset_mapping[1]			,		(1 + len(_A), 1 + len(_A) + 1 + len(_A))			,		)




def 	snake_case__       (					__lowercase       )		->		int:







						"""simple docstring"""

						if divisor % 5 == 0 or divisor % 2 == 0:
												return 0
						A__	:							Tuple						    = 1
						A__	:							Union[str, Any]						    = 1
						while repunit:
												A__	:							Union[str, Any]						    = (1_0 * repunit + 1) % divisor
												repunit_index += 1
						return repunit_index
def 	snake_case__       (					__lowercase = 1_0_0_0_0_0_0       )		->		int:







						"""simple docstring"""

						A__	:							Dict						    = limit - 1
						if divisor % 2 == 0:
												divisor += 1
						while least_divisible_repunit(__lowercase       ) <= limit:
												divisor += 2
						return divisor


if __name__ == "__main__":
		print(f"""{solution() = }""")