






"""simple docstring"""
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_bart import BartTokenizer


_lowerCAmelCase         =							logging.get_logger(__name__)


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

# See all BART models at https://huggingface.co/models?filter=bart
_lowerCAmelCase         =							{
    "vocab_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/vocab.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/vocab.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json",
    },
    "merges_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/merges.txt",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/merges.txt",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json",
    },
}

_lowerCAmelCase         =							{
    "facebook/bart-base": 1_024,
    "facebook/bart-large": 1_024,
    "facebook/bart-large-mnli": 1_024,
    "facebook/bart-large-cnn": 1_024,
    "facebook/bart-large-xsum": 1_024,
    "yjernite/bart_eli5": 1_024,
}



class      SCREAMING_SNAKE_CASE  (				_SCREAMING_SNAKE_CASE						):





	"""simple docstring"""




	_A       :				List[str]    =				VOCAB_FILES_NAMES
	_A       :				Union[str, Any]    =				PRETRAINED_VOCAB_FILES_MAP
	_A       :				str    =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_A       :				List[str]    =				["""input_ids""", """attention_mask"""]
	_A       :				List[Any]    =				BartTokenizer





	def __init__(self     ,     lowerCAmelCase_=None     ,     lowerCAmelCase_=None     ,     lowerCAmelCase_=None     ,     lowerCAmelCase_="replace"     ,     lowerCAmelCase_="<s>"     ,     lowerCAmelCase_="</s>"     ,     lowerCAmelCase_="</s>"     ,     lowerCAmelCase_="<s>"     ,     lowerCAmelCase_="<unk>"     ,     lowerCAmelCase_="<pad>"     ,     lowerCAmelCase_="<mask>"     ,     lowerCAmelCase_=False     ,     lowerCAmelCase_=True     ,     **lowerCAmelCase_     ,     ):
		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_     ,     )

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

		A_		:						int	    =   add_prefix_space

		# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
		A_		:						List[str]	    =   """post_processor"""
		A_		:						Tuple	    =   getattr(self.backend_tokenizer     ,     lowerCAmelCase_     ,     lowerCAmelCase_							)
		if tokenizer_component_instance:
			A_		:						List[str]	    =   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:
				A_		:						Tuple	    =   tuple(state["""sep"""]							)
			if "cls" in state:
				A_		:						List[Any]	    =   tuple(state["""cls"""]							)

			A_		:						Optional[Any]	    =   False

			if state.get("""add_prefix_space"""     ,     lowerCAmelCase_							) != add_prefix_space:
				A_		:						Optional[int]	    =   add_prefix_space
				A_		:						Any	    =   True

			if state.get("""trim_offsets"""     ,     lowerCAmelCase_							) != trim_offsets:
				A_		:						Optional[Any]	    =   trim_offsets
				A_		:						Tuple	    =   True

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





	@property
	def    lowerCamelCase(self							):
		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    lowerCamelCase(self     ,     lowerCAmelCase_							):
		A_		:						int	    =   AddedToken(lowerCAmelCase_     ,     lstrip=lowerCAmelCase_     ,     rstrip=lowerCAmelCase_							) if isinstance(lowerCAmelCase_     ,     lowerCAmelCase_							) else value
		A_		:						Dict	    =   value





	def    lowerCamelCase(self     ,     *lowerCAmelCase_     ,     **lowerCAmelCase_							):
		A_		:						int	    =   kwargs.get("""is_split_into_words"""     ,     lowerCAmelCase_							)

		if is_split_into_words and not self.add_prefix_space:
			raise ValueError(
			    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    lowerCamelCase(self     ,     *lowerCAmelCase_     ,     **lowerCAmelCase_							):
		A_		:						Any	    =   kwargs.get("""is_split_into_words"""     ,     lowerCAmelCase_							)

		if is_split_into_words and not self.add_prefix_space:
			raise ValueError(
			    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    lowerCamelCase(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_ = None							):
		A_		:						Any	    =   self._tokenizer.model.save(lowerCAmelCase_     ,     name=lowerCAmelCase_							)
		return tuple(lowerCAmelCase_							)





	def    lowerCamelCase(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_=None							):
		A_		:						Dict	    =   [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    lowerCamelCase(self     ,     lowerCAmelCase_     ,     lowerCAmelCase_ = None							):
		A_		:						Any	    =   [self.sep_token_id]
		A_		:						Tuple	    =   [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"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCAmelCase         =							{
    "configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
    "tokenization_luke": ["LukeTokenizer"],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowerCAmelCase         =							[
							    "LUKE_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "LukeForEntityClassification",
							    "LukeForEntityPairClassification",
							    "LukeForEntitySpanClassification",
							    "LukeForMultipleChoice",
							    "LukeForQuestionAnswering",
							    "LukeForSequenceClassification",
							    "LukeForTokenClassification",
							    "LukeForMaskedLM",
							    "LukeModel",
							    "LukePreTrainedModel",
							]


if TYPE_CHECKING:
							from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
							from .tokenization_luke import LukeTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_luke import (
														    LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    LukeForEntityClassification,
														    LukeForEntityPairClassification,
														    LukeForEntitySpanClassification,
														    LukeForMaskedLM,
														    LukeForMultipleChoice,
														    LukeForQuestionAnswering,
														    LukeForSequenceClassification,
														    LukeForTokenClassification,
														    LukeModel,
														    LukePreTrainedModel,
														)

else:
							import sys

							_lowerCAmelCase         =							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

