


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


_snake_case	:						Union[str, Any]         =							logging.get_logger(__name__)

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

_snake_case	:						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"
        ),
    },
}

_snake_case	:						Optional[Any]         =							{
    "roberta-base": 512,
    "roberta-large": 512,
    "roberta-large-mnli": 512,
    "distilroberta-base": 512,
    "roberta-base-openai-detector": 512,
    "roberta-large-openai-detector": 512,
}

class 							a						(_lowerCAmelCase ):




							"""simple docstring"""


							__UpperCAmelCase       :				Tuple	    =    VOCAB_FILES_NAMES
							__UpperCAmelCase       :				int	    =    PRETRAINED_VOCAB_FILES_MAP
							__UpperCAmelCase       :				List[str]	    =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__UpperCAmelCase       :				List[Any]	    =    ["input_ids", "attention_mask"]
							__UpperCAmelCase       :				Optional[int]	    =    RobertaTokenizer

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

														__snake_case						:     Optional[Any]									=  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
														if pre_tok_state.get("add_prefix_space"       ,      lowerCamelCase							) != add_prefix_space:
																					__snake_case						:     Any									=  getattr(lowerCamelCase       ,      pre_tok_state.pop("type"							)							)
																					__snake_case						:     List[Any]									=  add_prefix_space
																					__snake_case						:     Optional[Any]									=  pre_tok_class(**lowerCamelCase							)

														__snake_case						:     Any									=  add_prefix_space

														__snake_case						:     str									=  "post_processor"
														__snake_case						:     Optional[Any]									=  getattr(self.backend_tokenizer       ,      lowerCamelCase       ,      lowerCamelCase							)
														if tokenizer_component_instance:
																					__snake_case						:     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:
																												__snake_case						:     Tuple									=  tuple(state["sep"]							)
																					if "cls" in state:
																												__snake_case						:     List[Any]									=  tuple(state["cls"]							)

																					__snake_case						:     Union[str, Any]									=  False

																					if state.get("add_prefix_space"       ,      lowerCamelCase							) != add_prefix_space:
																												__snake_case						:     Dict									=  add_prefix_space
																												__snake_case						:     Optional[int]									=  True

																					if state.get("trim_offsets"       ,      lowerCamelCase							) != trim_offsets:
																												__snake_case						:     Optional[Any]									=  trim_offsets
																												__snake_case						:     Optional[Any]									=  True

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

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

							def        __snake_case   (				self			:    Optional[int]       ,      *lowerCamelCase			:    Union[str, Any]       ,      **lowerCamelCase			:    int							)      ->       BatchEncoding:
														__snake_case						:     Union[str, 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()._batch_encode_plus(*lowerCamelCase       ,      **lowerCamelCase							)

							def        __snake_case   (				self			:    Any       ,      *lowerCamelCase			:    List[str]       ,      **lowerCamelCase			:    Optional[Any]							)      ->       BatchEncoding:
														__snake_case						:     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()._encode_plus(*lowerCamelCase       ,      **lowerCamelCase							)

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

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









"""simple docstring"""







import unittest

from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_lowerCAmelCase            =	get_tests_dir('fixtures/test_sentencepiece.model')


@require_sentencepiece
class      UpperCamelCase		(__snake_case						,						unittest.TestCase     ):
						_SCREAMING_SNAKE_CASE  : Optional[Any]												=		XLMProphetNetTokenizer
						_SCREAMING_SNAKE_CASE  : Optional[int]												=		False
						_SCREAMING_SNAKE_CASE  : Optional[int]												=		True






						def      __snake_case      (		self  :Optional[int]				)      ->List[str]:
										super().setUp()

										# We have a SentencePiece fixture for testing
										lowercase    :      List[str]       = XLMProphetNetTokenizer(__magic_name__			, keep_accents=__magic_name__				)
										tokenizer.save_pretrained(self.tmpdirname				)






						def      __snake_case      (		self  :int				)      ->Any:
										lowercase    :      Dict       = """[PAD]"""
										lowercase    :      Tuple       = 0

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






						def      __snake_case      (		self  :Any				)      ->Union[str, Any]:
										lowercase    :      Optional[int]       = list(self.get_tokenizer().get_vocab().keys()				)

										self.assertEqual(vocab_keys[0]			, """[PAD]"""				)
										self.assertEqual(vocab_keys[1]			, """[CLS]"""				)
										self.assertEqual(vocab_keys[-1]			, """j"""				)
										self.assertEqual(len(__magic_name__				)			, 1_012				)






						def      __snake_case      (		self  :int				)      ->int:
										self.assertEqual(self.get_tokenizer().vocab_size			, 1_012				)






						def      __snake_case      (		self  :Optional[Any]				)      ->List[Any]:
										lowercase    :      Optional[Any]       = XLMProphetNetTokenizer(__magic_name__			, keep_accents=__magic_name__				)

										lowercase    :      Union[str, Any]       = tokenizer.tokenize("""This is a test"""				)
										self.assertListEqual(__magic_name__			, ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]				)

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(__magic_name__				)			, [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]			, )

										lowercase    :      Optional[Any]       = tokenizer.tokenize("""I was born in 92000, and this is falsé."""				)
										self.assertListEqual(
										    __magic_name__			, [
										        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""",
										        """.""",
										    ]			, )
										lowercase    :      Optional[int]       = tokenizer.convert_tokens_to_ids(__magic_name__				)
										self.assertListEqual(
										    __magic_name__			, [
										        value + tokenizer.fairseq_offset
										        for value in [8, 21, 84, 55, 24, 19, 7, -9, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, -9, 4]
										    ]			, )

										lowercase    :      Union[str, Any]       = tokenizer.convert_ids_to_tokens(__magic_name__				)
										self.assertListEqual(
										    __magic_name__			, [
										        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]""",
										        """.""",
										    ]			, )






						@cached_property
						def      __snake_case      (		self  :List[Any]				)      ->str:
										return XLMProphetNetTokenizer.from_pretrained("""microsoft/xprophetnet-large-wiki100-cased"""				)






						@slow
						def      __snake_case      (		self  :int				)      ->Optional[Any]:
										lowercase    :      str       = """Hello World!"""
										lowercase    :      Optional[Any]       = [35_389, 6_672, 49, 2]
										self.assertListEqual(__magic_name__			, self.big_tokenizer.encode(__magic_name__				)				)






						@slow
						def      __snake_case      (		self  :Optional[int]				)      ->Union[str, Any]:
										# fmt: off
										lowercase    :      Optional[int]       = {"""input_ids""": [[11_073, 82_783, 18, 26, 82_783, 549, 51_540, 248, 17_209, 1_301, 217, 20, 215_186, 1_325, 147, 17_209, 1_301, 217, 20, 56_370, 53, 122_020, 20, 16_477, 27, 87_355, 4_548, 20, 4_728, 78_392, 17, 159_969, 18, 26, 24_491, 629, 15, 538, 22_704, 5_439, 15, 2_788, 24_491, 9_885, 15, 43_534, 605, 15, 814, 18_403, 33_200, 29, 15, 43_534, 24_458, 12_410, 111, 24_966, 83_669, 9_637, 144_068, 26, 850, 22_346, 27, 147, 24_966, 83_669, 83_490, 26, 39_113, 735, 27, 689, 656, 2_800, 1_339, 4_600, 53, 122_020, 115_785, 34, 816, 1_339, 46_887, 18, 147, 53_905, 1_951, 42_238, 41_170, 17_732, 834, 436, 15, 27_523, 98_733, 217, 147, 5_542, 4_981, 930, 17_347, 16, 2], [20_091, 629, 94, 82_786, 58, 490, 20, 1_528, 84, 53_905, 344, 80_592, 110_128, 18_822, 5_267, 1_306, 62, 152_537, 308, 7_997, 401, 124_427, 549, 35_442, 225, 109, 15_055, 25_748, 147, 7_119, 43_712, 34, 767, 135_366, 18, 16, 2, 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], [592, 63_784, 119_466, 17, 147_808, 88_214, 18, 656, 81, 32, 3_296, 10_280, 16, 2, 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]], """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, 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, 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=__magic_name__			, model_name="""microsoft/xprophetnet-large-wiki100-cased"""			, revision="""1acad1643ddd54a44df6a1b797ada8373685d90e"""			, )
