






"""simple docstring"""



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        lowercase__      (							snake_case__,       unittest.TestCase       ):
			_UpperCAmelCase		:Union[str, Any]             =			LongformerTokenizer
			_UpperCAmelCase		:Optional[Any]             =			True
			_UpperCAmelCase		:Union[str, Any]             =			LongformerTokenizerFast
			_UpperCAmelCase		:Union[str, Any]             =			True


			def      UpperCAmelCase__						(				self					:  Union[str, Any] ):
										super().setUp()

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

										lowerCamelCase_	:							Optional[int]									=os.path.join(self.tmpdirname       ,	VOCAB_FILES_NAMES["vocab_file"] )
										lowerCamelCase_	:							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(snake_case__ ) + "\n" )
										with open(self.merges_file       ,	"w"       ,	encoding="utf-8" ) as fp:
																	fp.write("\n".join(snake_case__ ) )


			def      UpperCAmelCase__						(				self					:  Union[str, Any]       ,	**snake_case__					:  Optional[Any] ):
										kwargs.update(self.special_tokens_map )
										return self.tokenizer_class.from_pretrained(self.tmpdirname       ,	**snake_case__ )


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


			def      UpperCAmelCase__						(				self					:  int       ,	snake_case__					:  Optional[int] ):
										lowerCamelCase_	:							Any									="lower newer"
										lowerCamelCase_	:							Union[str, Any]									="lower newer"
										return input_text, output_text


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

										lowerCamelCase_	:							Dict									=tokens + [tokenizer.unk_token]
										lowerCamelCase_	:							str									=[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
										self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case__ )       ,	snake_case__ )


			def      UpperCAmelCase__						(				self					:  Optional[int] ):
										lowerCamelCase_	:							List[Any]									=self.get_tokenizer()

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


			@slow
			def      UpperCAmelCase__						(				self					:  Optional[Any] ):
										lowerCamelCase_	:							str									=self.tokenizer_class.from_pretrained("allenai/longformer-base-4096" )

										lowerCamelCase_	:							Dict									=tokenizer.encode("sequence builders"       ,	add_special_tokens=snake_case__ )
										lowerCamelCase_	:							Any									=tokenizer.encode("multi-sequence build"       ,	add_special_tokens=snake_case__ )

										lowerCamelCase_	:							str									=tokenizer.encode(
										    "sequence builders"       ,	add_special_tokens=snake_case__       ,	add_prefix_space=snake_case__ )
										lowerCamelCase_	:							Any									=tokenizer.encode(
										    "sequence builders"       ,	"multi-sequence build"       ,	add_special_tokens=snake_case__       ,	add_prefix_space=snake_case__ )

										lowerCamelCase_	:							Union[str, Any]									=tokenizer.build_inputs_with_special_tokens(snake_case__ )
										lowerCamelCase_	:							str									=tokenizer.build_inputs_with_special_tokens(snake_case__       ,	snake_case__ )

										assert encoded_sentence == encoded_text_from_decode
										assert encoded_pair == encoded_pair_from_decode


			def      UpperCAmelCase__						(				self					:  Tuple ):
										lowerCamelCase_	:							Optional[int]									=self.get_tokenizer()

										lowerCamelCase_	:							int									="Encode this sequence."
										lowerCamelCase_	:							Any									=tokenizer.byte_encoder[" ".encode("utf-8" )[0]]

										# Testing encoder arguments
										lowerCamelCase_	:							Union[str, Any]									=tokenizer.encode(snake_case__       ,	add_special_tokens=snake_case__       ,	add_prefix_space=snake_case__ )
										lowerCamelCase_	:							Dict									=tokenizer.convert_ids_to_tokens(encoded[0] )[0]
										self.assertNotEqual(snake_case__       ,	snake_case__ )

										lowerCamelCase_	:							List[Any]									=tokenizer.encode(snake_case__       ,	add_special_tokens=snake_case__       ,	add_prefix_space=snake_case__ )
										lowerCamelCase_	:							int									=tokenizer.convert_ids_to_tokens(encoded[0] )[0]
										self.assertEqual(snake_case__       ,	snake_case__ )

										tokenizer.add_special_tokens({"bos_token": "<s>"} )
										lowerCamelCase_	:							Dict									=tokenizer.encode(snake_case__       ,	add_special_tokens=snake_case__ )
										lowerCamelCase_	:							int									=tokenizer.convert_ids_to_tokens(encoded[1] )[0]
										self.assertNotEqual(snake_case__       ,	snake_case__ )

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

										lowerCamelCase_	:							Tuple									="Encode <mask> sequence"
										lowerCamelCase_	:							Union[str, Any]									="Encode <mask>sequence"

										lowerCamelCase_	:							str									=tokenizer.encode(snake_case__ )
										lowerCamelCase_	:							Tuple									=encoded.index(snake_case__ )
										lowerCamelCase_	:							Dict									=tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1] )[0]
										self.assertEqual(snake_case__       ,	snake_case__ )

										lowerCamelCase_	:							List[Any]									=tokenizer.encode(snake_case__ )
										lowerCamelCase_	:							Optional[Any]									=encoded.index(snake_case__ )
										lowerCamelCase_	:							Union[str, Any]									=tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1] )[0]
										self.assertNotEqual(snake_case__       ,	snake_case__ )


			def      UpperCAmelCase__						(				self					:  Dict ):
										pass


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

																								# 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"] )       ,	)

																								lowerCamelCase_	:							Optional[Any]									=tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"] )
																								lowerCamelCase_	:							str									=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(
																								    snake_case__       ,	["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"] )
																								self.assertSequenceEqual(
																								    snake_case__       ,	["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"] )


			def      UpperCAmelCase__						(				self					:  int ):
										for trim_offsets, add_prefix_space in itertools.product([True, False]       ,	repeat=2 ):
																	lowerCamelCase_	:							List[Any]									=self.rust_tokenizer_class.from_pretrained(
																	    self.tmpdirname       ,	use_fast=snake_case__       ,	add_prefix_space=snake_case__       ,	trim_offsets=snake_case__ )

																	lowerCamelCase_	:							List[str]									=json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__() )
																	lowerCamelCase_	:							List[str]									=json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__() )

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

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


			def      UpperCAmelCase__						(				self					:  int ):
										# 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})""" ):
																								lowerCamelCase_	:							Any									="hello"  # `hello` is a token in the vocabulary of `pretrained_name`
																								lowerCamelCase_	:							Any									=F"""{text_of_1_token} {text_of_1_token}"""

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

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

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

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

																								lowerCamelCase_	:							Any									=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)),
																								# )

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

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

																								lowerCamelCase_	:							List[str]									=self.rust_tokenizer_class.from_pretrained(
																								    snake_case__       ,	use_fast=snake_case__       ,	add_prefix_space=snake_case__       ,	trim_offsets=snake_case__ )
																								lowerCamelCase_	:							Optional[int]									=tokenizer_r(snake_case__       ,	return_offsets_mapping=snake_case__       ,	add_special_tokens=snake_case__ )
																								self.assertEqual(encoding.offset_mapping[0]       ,	(0, 1 + len(snake_case__ )) )
																								self.assertEqual(
																								    encoding.offset_mapping[1]       ,	(1 + len(snake_case__ ), 1 + len(snake_case__ ) + 1 + len(snake_case__ ))       ,	)











"""simple docstring"""



def 			_snake_case    (					lowerCamelCase__     :   int  )    ->     int:

							if not isinstance(lowerCamelCase__    ,						lowerCamelCase__  ):
														raise TypeError("only integers accepted as input"  )
							else:
														lowerCamelCase_	:							str									=str(abs(lowerCamelCase__  )  )
														lowerCamelCase_	:							Tuple									=[list(lowerCamelCase__  ) for char in range(len(lowerCamelCase__  )  )]
														for index in range(len(lowerCamelCase__  )  ):
																					num_transpositions[index].pop(lowerCamelCase__  )
														return max(
														    int("".join(list(lowerCamelCase__  )  )  ) for transposition in num_transpositions  )


if __name__ == "__main__":
						__import__('doctest').testmod()



