

'''simple docstring'''



import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Optional, Tuple, Union, get_type_hints

import yaml


__snake_case			:     Dict										=      NewType('DataClass', Any)
__snake_case			:     List[Any]										=      NewType('DataClassType', Any)
def 						__lowerCamelCase	(       __snake_case					:		List[Any]	)	->							Optional[int]:






						"""simple docstring"""





						if isinstance(__snake_case,		__snake_case	):
												return v
						if v.lower() in ("yes", "true", "t", "y", "1"):
												return True
						elif v.lower() in ("no", "false", "f", "n", "0"):
												return False
						else:
												raise ArgumentTypeError(
												    f"Truthy value expected: got {v} but expected one of yes/no, true/false, t/f, y/n, 1/0 (case insensitive)."	)
def 						__lowerCamelCase	(       __snake_case					:		list	)	->							Callable[[str], Any]:






						"""simple docstring"""





						A__					:       Dict     ={str(__snake_case	): choice for choice in choices}
						return lambda __snake_case	: str_to_choice.get(__snake_case,		__snake_case	)
def 						__lowerCamelCase	(       *,
    __snake_case					:		Union[str, List[str]] = None,		__snake_case					:		str = None,		__snake_case					:		Any = dataclasses.MISSING,		__snake_case					:		Callable[[], Any] = dataclasses.MISSING,		__snake_case					:		dict = None,		**__snake_case					:		Dict,		)	->							dataclasses.Field:






						"""simple docstring"""





						if metadata is None:
												# Important, don't use as default param in function signature because dict is mutable and shared across function calls
												A__					:       Dict     ={}
						if aliases is not None:
												A__					:       Any     =aliases
						if help is not None:
												A__					:       List[Any]     =help

						return dataclasses.field(metadata=__snake_case,		default=__snake_case,		default_factory=__snake_case,		**__snake_case	)



class lowerCamelCase			(  lowercase_						):



			'''simple docstring'''






			__snake_case        =	42


			def __init__(				self	:						List[str]		,      lowerCAmelCase_	:						Union[DataClassType, Iterable[DataClassType]]		,      **lowerCAmelCase_	:						Dict			)      ->		List[Any]:





									'''simple docstring'''
									# To make the default appear when using --help
									if "formatter_class" not in kwargs:
															A__					:       Union[str, Any]     =ArgumentDefaultsHelpFormatter
									super().__init__(**lowerCAmelCase_			)
									if dataclasses.is_dataclass(lowerCAmelCase_			):
															A__					:       Tuple     =[dataclass_types]
									A__					:       Union[str, Any]     =list(lowerCAmelCase_			)
									for dtype in self.dataclass_types:
															self._add_dataclass_arguments(lowerCAmelCase_			)


			@staticmethod
			def lowercase__						(				lowerCAmelCase_	:						ArgumentParser		,      lowerCAmelCase_	:						dataclasses.Field			)      ->		int:





									'''simple docstring'''
									A__					:       Union[str, Any]     =f"--{field.name}"
									A__					:       Optional[Any]     =field.metadata.copy()
									# field.metadata is not used at all by Data Classes,
									# it is provided as a third-party extension mechanism.
									if isinstance(field.type		,      lowerCAmelCase_			):
															raise RuntimeError(
															    """Unresolved type detected, which should have been done with the help of """
															    """`typing.get_type_hints` method by default"""			)

									A__					:       int     =kwargs.pop("""aliases"""		,      []			)
									if isinstance(lowerCAmelCase_		,      lowerCAmelCase_			):
															A__					:       Dict     =[aliases]

									A__					:       List[Any]     =getattr(field.type		,      """__origin__"""		,      field.type			)
									if origin_type is Union or (hasattr(lowerCAmelCase_		,      """UnionType"""			) and isinstance(lowerCAmelCase_		,      types.UnionType			)):
															if str not in field.type.__args__ and (
															    len(field.type.__args__			) != 2 or type(lowerCAmelCase_			) not in field.type.__args__
															):
																					raise ValueError(
																					    """Only `Union[X, NoneType]` (i.e., `Optional[X]`) is allowed for `Union` because"""
																					    """ the argument parser only supports one type per argument."""
																					    f" Problem encountered in field '{field.name}'."			)
															if type(lowerCAmelCase_			) not in field.type.__args__:
																					# filter `str` in Union
																					A__					:       Any     =field.type.__args__[0] if field.type.__args__[1] == str else field.type.__args__[1]
																					A__					:       Optional[int]     =getattr(field.type		,      """__origin__"""		,      field.type			)
															elif bool not in field.type.__args__:
																					# filter `NoneType` in Union (except for `Union[bool, NoneType]`)
																					A__					:       Dict     =(
																					    field.type.__args__[0] if isinstance(lowerCAmelCase_		,      field.type.__args__[1]			) else field.type.__args__[1]
																					)
																					A__					:       Union[str, Any]     =getattr(field.type		,      """__origin__"""		,      field.type			)

        # A variable to store kwargs for a boolean field, if needed
        # so that we can init a `no_*` complement argument (see below)
									A__					:       List[Any]     ={}
									if origin_type is Literal or (isinstance(field.type		,      lowerCAmelCase_			) and issubclass(field.type		,      lowerCAmelCase_			)):
															if origin_type is Literal:
																					A__					:       Any     =field.type.__args__
															else:
																					A__					:       str     =[x.value for x in field.type]

															A__					:       List[Any]     =make_choice_type_function(kwargs["""choices"""]			)

															if field.default is not dataclasses.MISSING:
																					A__					:       Tuple     =field.default
															else:
																					A__					:       List[str]     =True
									elif field.type is bool or field.type == Optional[bool]:
															# Copy the currect kwargs to use to instantiate a `no_*` complement argument below.
															# We do not initialize it here because the `no_*` alternative must be instantiated after the real argument
															A__					:       Optional[Any]     =copy(lowerCAmelCase_			)

															# Hack because type=bool in argparse does not behave as we want.
															A__					:       Any     =string_to_bool
															if field.type is bool or (field.default is not None and field.default is not dataclasses.MISSING):
																					# Default value is False if we have no default when of type bool.
																					A__					:       Dict     =False if field.default is dataclasses.MISSING else field.default
																					# This is the value that will get picked if we don't include --field_name in any way
																					A__					:       Optional[int]     =default
																					# This tells argparse we accept 0 or 1 value after --field_name
																					A__					:       List[str]     ="""?"""
																					# This is the value that will get picked if we do --field_name (without value)
																					A__					:       int     =True
									elif isclass(lowerCAmelCase_			) and issubclass(lowerCAmelCase_		,      lowerCAmelCase_			):
															A__					:       List[Any]     =field.type.__args__[0]
															A__					:       str     ="""+"""
															if field.default_factory is not dataclasses.MISSING:
																					A__					:       str     =field.default_factory()
															elif field.default is dataclasses.MISSING:
																					A__					:       List[Any]     =True
									else:
															A__					:       int     =field.type
															if field.default is not dataclasses.MISSING:
																					A__					:       Optional[Any]     =field.default
															elif field.default_factory is not dataclasses.MISSING:
																					A__					:       str     =field.default_factory()
															else:
																					A__					:       List[Any]     =True
									parser.add_argument(lowerCAmelCase_		,      *lowerCAmelCase_		,      **lowerCAmelCase_			)

									# Add a complement `no_*` argument for a boolean field AFTER the initial field has already been added.
									# Order is important for arguments with the same destination!
									# We use a copy of earlier kwargs because the original kwargs have changed a lot before reaching down
									# here and we do not need those changes/additional keys.
									if field.default is True and (field.type is bool or field.type == Optional[bool]):
															A__					:       int     =False
															parser.add_argument(f"--no_{field.name}"		,      action="""store_false"""		,      dest=field.name		,      **lowerCAmelCase_			)


			def lowercase__						(				self	:						Optional[Any]		,      lowerCAmelCase_	:						DataClassType			)      ->		Tuple:





									'''simple docstring'''
									if hasattr(lowerCAmelCase_		,      """_argument_group_name"""			):
															A__					:       Union[str, Any]     =self.add_argument_group(dtype._argument_group_name			)
									else:
															A__					:       Dict     =self

									try:
															A__					:       Dict[str, type]     =get_type_hints(lowerCAmelCase_			)
									except NameError:
															raise RuntimeError(
															    f"Type resolution failed for {dtype}. Try declaring the class in global scope or "
															    """removing line of `from __future__ import annotations` which opts in Postponed """
															    """Evaluation of Annotations (PEP 563)"""			)
									except TypeError as ex:
															# Remove this block when we drop Python 3.9 support
															if sys.version_info[:2] < (3, 10) and "unsupported operand type(s) for |" in str(lowerCAmelCase_			):
																					A__					:       List[str]     =""".""".join(map(lowerCAmelCase_		,      sys.version_info[:3]			)			)
																					raise RuntimeError(
																					    f"Type resolution failed for {dtype} on Python {python_version}. Try removing "
																					    """line of `from __future__ import annotations` which opts in union types as """
																					    """`X | Y` (PEP 604) via Postponed Evaluation of Annotations (PEP 563). To """
																					    """support Python versions that lower than 3.10, you need to use """
																					    """`typing.Union[X, Y]` instead of `X | Y` and `typing.Optional[X]` instead of """
																					    """`X | None`."""			) from ex
															raise

									for field in dataclasses.fields(lowerCAmelCase_			):
															if not field.init:
																					continue
															A__					:       Dict     =type_hints[field.name]
															self._parse_dataclass_field(lowerCAmelCase_		,      lowerCAmelCase_			)


			def lowercase__						(				self	:						Union[str, Any]		,      lowerCAmelCase_	:						List[str]=None		,      lowerCAmelCase_	:						Dict=False		,      lowerCAmelCase_	:						int=True		,      lowerCAmelCase_	:						int=None		,      lowerCAmelCase_	:						Union[str, Any]=None		,      )      ->		Tuple[DataClass, ...]:





									'''simple docstring'''

									if args_file_flag or args_filename or (look_for_args_file and len(sys.argv			)):
															A__					:       Optional[int]     =[]

															if args_filename:
																					args_files.append(Path(lowerCAmelCase_			)			)
															elif look_for_args_file and len(sys.argv			):
																					args_files.append(Path(sys.argv[0]			).with_suffix(""".args"""			)			)

															# args files specified via command line flag should overwrite default args files so we add them last
															if args_file_flag:
																					# Create special parser just to extract the args_file_flag values
																					A__					:       Union[str, Any]     =ArgumentParser()
																					args_file_parser.add_argument(lowerCAmelCase_		,      type=lowerCAmelCase_		,      action="""append"""			)

																					# Use only remaining args for further parsing (remove the args_file_flag)
																					A__   ,						A__					:       Optional[Any]     =args_file_parser.parse_known_args(args=lowerCAmelCase_			)
																					A__					:       Optional[Any]     =vars(lowerCAmelCase_			).get(args_file_flag.lstrip("""-"""			)		,      lowerCAmelCase_			)

																					if cmd_args_file_paths:
																											args_files.extend([Path(lowerCAmelCase_			) for p in cmd_args_file_paths]			)

															A__					:       List[Any]     =[]
															for args_file in args_files:
																					if args_file.exists():
																											file_args += args_file.read_text().split()

            # in case of duplicate arguments the last one has precedence
            # args specified via the command line should overwrite args from files, so we add them last
															A__					:       Union[str, Any]     =file_args + args if args is not None else file_args + sys.argv[1:]
									A__   ,						A__					:       Dict     =self.parse_known_args(args=lowerCAmelCase_			)
									A__					:       Dict     =[]
									for dtype in self.dataclass_types:
															A__					:       Optional[Any]     ={f.name for f in dataclasses.fields(lowerCAmelCase_			) if f.init}
															A__					:       Any     ={k: v for k, v in vars(lowerCAmelCase_			).items() if k in keys}
															for k in keys:
																					delattr(lowerCAmelCase_		,      lowerCAmelCase_			)
															A__					:       List[str]     =dtype(**lowerCAmelCase_			)
															outputs.append(lowerCAmelCase_			)
									if len(namespace.__dict__			) > 0:
															# additional namespace.
															outputs.append(lowerCAmelCase_			)
									if return_remaining_strings:
															return (*outputs, remaining_args)
									else:
															if remaining_args:
																					raise ValueError(f"Some specified arguments are not used by the HfArgumentParser: {remaining_args}"			)

															return (*outputs,)


			def lowercase__						(				self	:						Dict		,      lowerCAmelCase_	:						Dict[str, Any]		,      lowerCAmelCase_	:						bool = False			)      ->		Tuple[DataClass, ...]:





									'''simple docstring'''
									A__					:       str     =set(args.keys()			)
									A__					:       Any     =[]
									for dtype in self.dataclass_types:
															A__					:       List[str]     ={f.name for f in dataclasses.fields(lowerCAmelCase_			) if f.init}
															A__					:       Union[str, Any]     ={k: v for k, v in args.items() if k in keys}
															unused_keys.difference_update(inputs.keys()			)
															A__					:       str     =dtype(**lowerCAmelCase_			)
															outputs.append(lowerCAmelCase_			)
									if not allow_extra_keys and unused_keys:
															raise ValueError(f"Some keys are not used by the HfArgumentParser: {sorted(lowerCAmelCase_			)}"			)
									return tuple(lowerCAmelCase_			)


			def lowercase__						(				self	:						List[Any]		,      lowerCAmelCase_	:						str		,      lowerCAmelCase_	:						bool = False			)      ->		Tuple[DataClass, ...]:





									'''simple docstring'''
									with open(Path(lowerCAmelCase_			)		,      encoding="""utf-8"""			) as open_json_file:
															A__					:       int     =json.loads(open_json_file.read()			)
									A__					:       Tuple     =self.parse_dict(lowerCAmelCase_		,      allow_extra_keys=lowerCAmelCase_			)
									return tuple(lowerCAmelCase_			)



			def lowercase__						(				self	:						List[Any]		,      lowerCAmelCase_	:						str		,      lowerCAmelCase_	:						bool = False			)      ->		Tuple[DataClass, ...]:





									'''simple docstring'''
									A__					:       Dict     =self.parse_dict(yaml.safe_load(Path(lowerCAmelCase_			).read_text()			)		,      allow_extra_keys=lowerCAmelCase_			)
									return tuple(lowerCAmelCase_			)




'''simple docstring'''



import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__snake_case			:     List[str]										=      get_tests_dir('fixtures/test_sentencepiece.model')



@require_sentencepiece
@require_tokenizers
class lowerCamelCase			(  lowercase_	,						unittest.TestCase						):



			'''simple docstring'''






			__snake_case        =	XLMRobertaTokenizer
			__snake_case        =	XLMRobertaTokenizerFast
			__snake_case        =	True
			__snake_case        =	True


			def lowercase__						(				self	:						Any			)      ->		Union[str, Any]:





									'''simple docstring'''
									super().setUp()

									# We have a SentencePiece fixture for testing
									A__					:       Any     =XLMRobertaTokenizer(lowerCAmelCase_		,      keep_accents=lowerCAmelCase_			)
									tokenizer.save_pretrained(self.tmpdirname			)


			def lowercase__						(				self	:						Optional[Any]			)      ->		Tuple:





									'''simple docstring'''
									A__					:       Union[str, Any]     ="""<pad>"""
									A__					:       Any     =1

									self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase_			)		,      lowerCAmelCase_			)
									self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase_			)		,      lowerCAmelCase_			)


			def lowercase__						(				self	:						List[Any]			)      ->		Any:





									'''simple docstring'''
									A__					:       int     =list(self.get_tokenizer().get_vocab().keys()			)

									self.assertEqual(vocab_keys[0]		,      """<s>"""			)
									self.assertEqual(vocab_keys[1]		,      """<pad>"""			)
									self.assertEqual(vocab_keys[-1]		,      """<mask>"""			)
									self.assertEqual(len(lowerCAmelCase_			)		,      10_02			)


			def lowercase__						(				self	:						Optional[int]			)      ->		Optional[Any]:





									'''simple docstring'''
									self.assertEqual(self.get_tokenizer().vocab_size		,      10_02			)


			def lowercase__						(				self	:						Tuple			)      ->		Any:





									'''simple docstring'''
									A__					:       List[Any]     =XLMRobertaTokenizer(lowerCAmelCase_		,      keep_accents=lowerCAmelCase_			)

									A__					:       Tuple     =tokenizer.tokenize("""This is a test"""			)
									self.assertListEqual(lowerCAmelCase_		,      ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]			)

									self.assertListEqual(
									    tokenizer.convert_tokens_to_ids(lowerCAmelCase_			)		,      [value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]		,      )

									A__					:       Optional[int]     =tokenizer.tokenize("""I was born in 92000, and this is falsé."""			)
									self.assertListEqual(
									    lowerCAmelCase_		,      [
									        SPIECE_UNDERLINE + """I""",
									        SPIECE_UNDERLINE + """was""",
									        SPIECE_UNDERLINE + """b""",
									        """or""",
									        """n""",
									        SPIECE_UNDERLINE + """in""",
									        SPIECE_UNDERLINE + """""",
									        """9""",
									        """2""",
									        """0""",
									        """0""",
									        """0""",
									        """,""",
									        SPIECE_UNDERLINE + """and""",
									        SPIECE_UNDERLINE + """this""",
									        SPIECE_UNDERLINE + """is""",
									        SPIECE_UNDERLINE + """f""",
									        """al""",
									        """s""",
									        """é""",
									        """.""",
									    ]		,      )
									A__					:       Optional[int]     =tokenizer.convert_tokens_to_ids(lowerCAmelCase_			)
									self.assertListEqual(
									    lowerCAmelCase_		,      [
									        value + tokenizer.fairseq_offset
									        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
									        #                                       ^ unk: 2 + 1 = 3                  unk: 2 + 1 = 3 ^
									    ]		,      )

									A__					:       Union[str, Any]     =tokenizer.convert_ids_to_tokens(lowerCAmelCase_			)
									self.assertListEqual(
									    lowerCAmelCase_		,      [
									        SPIECE_UNDERLINE + """I""",
									        SPIECE_UNDERLINE + """was""",
									        SPIECE_UNDERLINE + """b""",
									        """or""",
									        """n""",
									        SPIECE_UNDERLINE + """in""",
									        SPIECE_UNDERLINE + """""",
									        """<unk>""",
									        """2""",
									        """0""",
									        """0""",
									        """0""",
									        """,""",
									        SPIECE_UNDERLINE + """and""",
									        SPIECE_UNDERLINE + """this""",
									        SPIECE_UNDERLINE + """is""",
									        SPIECE_UNDERLINE + """f""",
									        """al""",
									        """s""",
									        """<unk>""",
									        """.""",
									    ]		,      )


			def lowercase__						(				self	:						List[Any]			)      ->		Optional[int]:





									'''simple docstring'''
									if not self.test_slow_tokenizer:
															# as we don't have a slow version, we can't compare the outputs between slow and fast versions
															return

									A__					:       Dict     =(self.rust_tokenizer_class, """hf-internal-testing/tiny-xlm-roberta""", {})
									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
															with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"			):
																					A__					:       List[str]     =self.rust_tokenizer_class.from_pretrained(lowerCAmelCase_		,      **lowerCAmelCase_			)
																					A__					:       Union[str, Any]     =self.tokenizer_class.from_pretrained(lowerCAmelCase_		,      **lowerCAmelCase_			)

																					A__					:       Optional[Any]     =tempfile.mkdtemp()

																					A__					:       Union[str, Any]     =tokenizer_r.save_pretrained(lowerCAmelCase_			)
																					A__					:       Union[str, Any]     =tokenizer_p.save_pretrained(lowerCAmelCase_			)

																					# Checks it save with the same files + the tokenizer.json file for the fast one
																					self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files			)			)
																					A__					:       List[str]     =tuple(f for f in tokenizer_r_files if """tokenizer.json""" not in f			)
																					self.assertSequenceEqual(lowerCAmelCase_		,      lowerCAmelCase_			)

																					# Checks everything loads correctly in the same way
																					A__					:       Any     =tokenizer_r.from_pretrained(lowerCAmelCase_			)
																					A__					:       Union[str, Any]     =tokenizer_p.from_pretrained(lowerCAmelCase_			)

																					# Check special tokens are set accordingly on Rust and Python
																					for key in tokenizer_pp.special_tokens_map:
																											self.assertTrue(hasattr(lowerCAmelCase_		,      lowerCAmelCase_			)			)
																											# self.assertEqual(getattr(tokenizer_rp, key), getattr(tokenizer_pp, key))
																											# self.assertEqual(getattr(tokenizer_rp, key + "_id"), getattr(tokenizer_pp, key + "_id"))

																					shutil.rmtree(lowerCAmelCase_			)

																					# Save tokenizer rust, legacy_format=True
																					A__					:       List[str]     =tempfile.mkdtemp()

																					A__					:       List[str]     =tokenizer_r.save_pretrained(lowerCAmelCase_		,      legacy_format=lowerCAmelCase_			)
																					A__					:       List[Any]     =tokenizer_p.save_pretrained(lowerCAmelCase_			)

																					# Checks it save with the same files
																					self.assertSequenceEqual(lowerCAmelCase_		,      lowerCAmelCase_			)

																					# Checks everything loads correctly in the same way
																					A__					:       str     =tokenizer_r.from_pretrained(lowerCAmelCase_			)
																					A__					:       List[Any]     =tokenizer_p.from_pretrained(lowerCAmelCase_			)

																					# Check special tokens are set accordingly on Rust and Python
																					for key in tokenizer_pp.special_tokens_map:
																											self.assertTrue(hasattr(lowerCAmelCase_		,      lowerCAmelCase_			)			)

																					shutil.rmtree(lowerCAmelCase_			)

																					# Save tokenizer rust, legacy_format=False
																					A__					:       List[str]     =tempfile.mkdtemp()

																					A__					:       Dict     =tokenizer_r.save_pretrained(lowerCAmelCase_		,      legacy_format=lowerCAmelCase_			)
																					A__					:       List[Any]     =tokenizer_p.save_pretrained(lowerCAmelCase_			)

																					# Checks it saved the tokenizer.json file
																					self.assertTrue(any("""tokenizer.json""" in f for f in tokenizer_r_files			)			)

																					# Checks everything loads correctly in the same way
																					A__					:       Optional[int]     =tokenizer_r.from_pretrained(lowerCAmelCase_			)
																					A__					:       str     =tokenizer_p.from_pretrained(lowerCAmelCase_			)

																					# Check special tokens are set accordingly on Rust and Python
																					for key in tokenizer_pp.special_tokens_map:
																											self.assertTrue(hasattr(lowerCAmelCase_		,      lowerCAmelCase_			)			)

																					shutil.rmtree(lowerCAmelCase_			)


			@cached_property
			def lowercase__						(				self	:						Optional[Any]			)      ->		List[str]:





									'''simple docstring'''
									return XLMRobertaTokenizer.from_pretrained("""xlm-roberta-base"""			)


			def lowercase__						(				self	:						Tuple			)      ->		Tuple:





									'''simple docstring'''
									with tempfile.NamedTemporaryFile() as f:
															shutil.copyfile(lowerCAmelCase_		,      f.name			)
															A__					:       Dict     =XLMRobertaTokenizer(f.name		,      keep_accents=lowerCAmelCase_			)
															A__					:       Optional[Any]     =pickle.dumps(lowerCAmelCase_			)
									pickle.loads(lowerCAmelCase_			)


			def lowercase__						(				self	:						Optional[Any]			)      ->		List[Any]:





									'''simple docstring'''
									if not self.test_rust_tokenizer:
															return

									A__					:       Any     =self.get_tokenizer()
									A__					:       Any     =self.get_rust_tokenizer()

									A__					:       Optional[Any]     ="""I was born in 92000, and this is falsé."""

									A__					:       List[str]     =tokenizer.tokenize(lowerCAmelCase_			)
									A__					:       int     =rust_tokenizer.tokenize(lowerCAmelCase_			)
									self.assertListEqual(lowerCAmelCase_		,      lowerCAmelCase_			)

									A__					:       str     =tokenizer.encode(lowerCAmelCase_		,      add_special_tokens=lowerCAmelCase_			)
									A__					:       Dict     =rust_tokenizer.encode(lowerCAmelCase_		,      add_special_tokens=lowerCAmelCase_			)
									self.assertListEqual(lowerCAmelCase_		,      lowerCAmelCase_			)

									A__					:       Union[str, Any]     =self.get_rust_tokenizer()
									A__					:       Union[str, Any]     =tokenizer.encode(lowerCAmelCase_			)
									A__					:       Optional[Any]     =rust_tokenizer.encode(lowerCAmelCase_			)
									self.assertListEqual(lowerCAmelCase_		,      lowerCAmelCase_			)


			@slow
			def lowercase__						(				self	:						Dict			)      ->		int:





									'''simple docstring'''
									A__					:       Optional[Any]     ="""Hello World!"""
									A__					:       Optional[Any]     =[0, 3_53_78, 66_61, 38, 2]
									# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
									# xlmr.eval()
									# xlmr.encode(symbols)

									self.assertListEqual(lowerCAmelCase_		,      self.big_tokenizer.encode(lowerCAmelCase_			)			)


			@slow
			def lowercase__						(				self	:						List[Any]			)      ->		int:





									'''simple docstring'''
									A__					:       List[Any]     =(
									    """This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"""
									    """ add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"""
									)
									A__					:       Optional[Any]     =[
									    0,
									    32_93,
									    83,
									    10,
									    45_52,
									    49_89,
									    79_86,
									    6_78,
									    10,
									    59_15,
									    1_11,
									    17_94_59,
									    12_48_50,
									    4,
									    60_44,
									    2_37,
									    12,
									    6,
									    5,
									    6,
									    4,
									    67_80,
									    7_05,
									    15,
									    13_88,
									    44,
									    3_78,
									    1_01_14,
									    7_11,
									    1_52,
									    20,
									    6,
									    5,
									    2_23_76,
									    6_42,
									    12_21,
									    1_51_90,
									    3_41_53,
									    4_50,
									    56_08,
									    9_59,
									    11_19,
									    5_77_02,
									    1_36,
									    1_86,
									    47,
									    10_98,
									    2_93_67,
									    47,
									    # 4426, # What fairseq tokenizes from "<unk>": "_<"
									    # 3678, # What fairseq tokenizes from "<unk>": "unk"
									    # 2740, # What fairseq tokenizes from "<unk>": ">"
									    3,  # What we tokenize from "<unk>": "<unk>"
									    6,  # Residue from the tokenization: an extra sentencepiece underline
									    4,
									    60_44,
									    2_37,
									    62_84,
									    5_09_01,
									    5_28,
									    31,
									    90,
									    34,
									    9_27,
									    2,
									]
									# xlmr = torch.hub.load('pytorch/fairseq', 'xlmr.base')  # xlmr.large has same tokenizer
									# xlmr.eval()
									# xlmr.encode(symbols)

									self.assertListEqual(lowerCAmelCase_		,      self.big_tokenizer.encode(lowerCAmelCase_			)			)



			@slow
			def lowercase__						(				self	:						int			)      ->		Optional[Any]:





									'''simple docstring'''
									# fmt: off
									A__					:       List[Any]     ={"""input_ids""": [[0, 1_10_62, 8_27_72, 7, 15, 8_27_72, 5_38, 5_15_29, 2_37, 1_71_98, 12_90, 2_06, 9, 21_51_75, 13_14, 1_36, 1_71_98, 12_90, 2_06, 9, 5_63_59, 42, 12_20_09, 9, 1_64_66, 16, 8_73_44, 45_37, 9, 47_17, 7_83_81, 6, 15_99_58, 7, 15, 2_44_80, 6_18, 4, 5_27, 2_26_93, 54_28, 4, 27_77, 2_44_80, 98_74, 4, 4_35_23, 5_94, 4, 8_03, 1_83_92, 3_31_89, 18, 4, 4_35_23, 2_44_47, 1_23_99, 1_00, 2_49_55, 8_36_58, 96_26, 14_40_57, 15, 8_39, 2_23_35, 16, 1_36, 2_49_55, 8_36_58, 8_34_79, 15, 3_91_02, 7_24, 16, 6_78, 6_45, 27_89, 13_28, 45_89, 42, 12_20_09, 11_57_74, 23, 8_05, 13_28, 4_68_76, 7, 1_36, 5_38_94, 19_40, 4_22_27, 4_11_59, 1_77_21, 8_23, 4_25, 4, 2_75_12, 9_87_22, 2_06, 1_36, 55_31, 49_70, 9_19, 1_73_36, 5, 2], [0, 2_00_80, 6_18, 83, 8_27_75, 47, 4_79, 9, 15_17, 73, 5_38_94, 3_33, 8_05_81, 11_01_17, 1_88_11, 52_56, 12_95, 51, 15_25_26, 2_97, 79_86, 3_90, 12_44_16, 5_38, 3_54_31, 2_14, 98, 1_50_44, 2_57_37, 1_36, 71_08, 4_37_01, 23, 7_56, 13_53_55, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 5_81, 6_37_73, 11_94_55, 6, 14_77_97, 8_82_03, 7, 6_45, 70, 21, 32_85, 1_02_69, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
									# fmt: on

									self.tokenizer_integration_test_util(
									    expected_encoding=lowerCAmelCase_		,      model_name="""xlm-roberta-base"""		,      revision="""d9d8a8ea5eb94b1c6654ae9249df7793cd2933d3"""		,      )

