




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import AddedToken, PreTrainedTokenizerFast
from ...utils import logging


UpperCamelCase__						=		logging.get_logger(__name__)

UpperCamelCase__						=		{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

UpperCamelCase__						=		{
    'vocab_file': {
        'TsinghuaAI/CPM-Generate': 'https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'TsinghuaAI/CPM-Generate': 'https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/tokenizer.json',
    },
}


class 							__SCREAMING_SNAKE_CASE				(						lowerCamelCase    ):

					def __init__(							self					,			__lowercase=None					,			__lowercase=None					,			__lowercase=False					,			__lowercase=True					,			__lowercase=False					,			__lowercase="<s>"					,			__lowercase="</s>"					,			__lowercase="<unk>"					,			__lowercase="<sep>"					,			__lowercase="<pad>"					,			__lowercase="<cls>"					,			__lowercase="<mask>"					,			__lowercase=["<eop>", "<eod>"]					,			**__lowercase					,			):







						'''simple docstring'''




						lowerCamelCase_				:						List[str]				  =				AddedToken(__lowercase					,			lstrip=__lowercase					,			rstrip=__lowercase   ) if isinstance(__lowercase					,			__lowercase   ) else mask_token

						super().__init__(
						    vocab_file=__lowercase					,			tokenizer_file=__lowercase					,			do_lower_case=__lowercase					,			remove_space=__lowercase					,			keep_accents=__lowercase					,			bos_token=__lowercase					,			eos_token=__lowercase					,			unk_token=__lowercase					,			sep_token=__lowercase					,			pad_token=__lowercase					,			cls_token=__lowercase					,			mask_token=__lowercase					,			additional_special_tokens=__lowercase					,			**__lowercase					,			)

						lowerCamelCase_				:						int				  =				3
						lowerCamelCase_				:						Optional[Any]				  =				do_lower_case
						lowerCamelCase_				:						List[str]				  =				remove_space
						lowerCamelCase_				:						Union[str, Any]				  =				keep_accents
						lowerCamelCase_				:						Union[str, Any]				  =				vocab_file
						lowerCamelCase_				:						List[str]				  =				False if not self.vocab_file else True

						try:
							import jieba
						except ModuleNotFoundError as error:
							raise error.__class__(
							    'You need to install jieba to use CpmTokenizer or CpmTokenizerFast. '
							    'See https://pypi.org/project/jieba/ for installation.'   )
						lowerCamelCase_				:						Dict				  =				jieba
						lowerCamelCase_				:						Optional[Any]				  =				str.maketrans(' \n'					,			'\u2582\u2583'   )

					def       lowercase_				(							self					,			__lowercase					,			__lowercase = None   ):







						'''simple docstring'''




						lowerCamelCase_				:						Dict				  =				[self.sep_token_id]
						lowerCamelCase_				:						Optional[Any]				  =				[self.cls_token_id]
						if token_ids_a is None:
							return token_ids_a + sep + cls
						return token_ids_a + sep + token_ids_a + sep + cls

					def       lowercase_				(							self					,			__lowercase					,			__lowercase = None   ):







						'''simple docstring'''




						lowerCamelCase_				:						str				  =				[self.sep_token_id]
						lowerCamelCase_				:						Optional[int]				  =				[2]

						if token_ids_a is None:
							return len(token_ids_a + sep   ) * [0] + cls_segment_id
						return len(token_ids_a + sep   ) * [0] + len(token_ids_a + sep   ) * [1] + cls_segment_id

					def       lowercase_				(							self					,			__lowercase					,			__lowercase = None   ):







						'''simple docstring'''




						if not self.can_save_slow_tokenizer:
							raise ValueError(
							    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
							    'tokenizer.'   )

						if not os.path.isdir(__lowercase   ):
							logger.error(f"Vocabulary path ({save_directory}) should be a directory"   )
							return
						lowerCamelCase_				:						Optional[int]				  =				os.path.join(
						    __lowercase					,			(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

						if os.path.abspath(self.vocab_file   ) != os.path.abspath(__lowercase   ):
							copyfile(self.vocab_file					,			__lowercase   )

						return (out_vocab_file,)

					def       lowercase_				(							self					,			__lowercase					,			*__lowercase					,			**__lowercase   ):







						'''simple docstring'''




						lowerCamelCase_				:						Dict				  =				[
						    ' '.join([x.translate(self.translator   ) for x in self.jieba.cut(__lowercase					,			cut_all=__lowercase   )]   )
						    for text in batch_text_or_text_pairs
						]
						return super()._batch_encode_plus(__lowercase					,			*__lowercase					,			**__lowercase   )





					def       lowercase_				(							self					,			*__lowercase					,			**__lowercase   ):







						'''simple docstring'''




						lowerCamelCase_				:						Optional[Any]				  =				super()._decode(*__lowercase					,			**__lowercase   )
						lowerCamelCase_				:						Dict				  =				text.replace(' '					,			''   ).replace('\u2582'					,			' '   ).replace('\u2583'					,			'\n'   )
						return text






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase__						=		{
    'configuration_layoutlm': ['LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMConfig', 'LayoutLMOnnxConfig'],
    'tokenization_layoutlm': ['LayoutLMTokenizer'],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase__						=		['LayoutLMTokenizerFast']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase__						=		[
							    'LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'LayoutLMForMaskedLM',
							    'LayoutLMForSequenceClassification',
							    'LayoutLMForTokenClassification',
							    'LayoutLMForQuestionAnswering',
							    'LayoutLMModel',
							    'LayoutLMPreTrainedModel',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase__						=		[
							    'TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'TFLayoutLMForMaskedLM',
							    'TFLayoutLMForSequenceClassification',
							    'TFLayoutLMForTokenClassification',
							    'TFLayoutLMForQuestionAnswering',
							    'TFLayoutLMMainLayer',
							    'TFLayoutLMModel',
							    'TFLayoutLMPreTrainedModel',
							]


if TYPE_CHECKING:
							from .configuration_layoutlm import LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMConfig, LayoutLMOnnxConfig
							from .tokenization_layoutlm import LayoutLMTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_layoutlm_fast import LayoutLMTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_layoutlm import (
														    LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    LayoutLMForMaskedLM,
														    LayoutLMForQuestionAnswering,
														    LayoutLMForSequenceClassification,
														    LayoutLMForTokenClassification,
														    LayoutLMModel,
														    LayoutLMPreTrainedModel,
														)
							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_layoutlm import (
														    TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFLayoutLMForMaskedLM,
														    TFLayoutLMForQuestionAnswering,
														    TFLayoutLMForSequenceClassification,
														    TFLayoutLMForTokenClassification,
														    TFLayoutLMMainLayer,
														    TFLayoutLMModel,
														    TFLayoutLMPreTrainedModel,
														)

else:
							import sys

							UpperCamelCase__						=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
