


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

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


_SCREAMING_SNAKE_CASE    :				List[Any]       =					logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE    :				List[Any]       =					{"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

_SCREAMING_SNAKE_CASE    :				int       =					{
    """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 						A__      (					UpperCAmelCase__			):







    """simple docstring"""

    def __init__( self    ,      __snake_case=None    ,      __snake_case=None    ,      __snake_case=False    ,      __snake_case=True    ,      __snake_case=False    ,      __snake_case="<s>"    ,      __snake_case="</s>"    ,      __snake_case="<unk>"    ,      __snake_case="<sep>"    ,      __snake_case="<pad>"    ,      __snake_case="<cls>"    ,      __snake_case="<mask>"    ,      __snake_case=["<eop>", "<eod>"]    ,      **__snake_case    ,      ):
         snake_case					=       AddedToken(lowerCamelCase__    ,      lstrip=lowerCamelCase__    ,      rstrip=lowerCamelCase__					) if isinstance(lowerCamelCase__    ,      lowerCamelCase__					) else mask_token

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

         snake_case					=       3
         snake_case					=       do_lower_case
         snake_case					=       remove_space
         snake_case					=       keep_accents
         snake_case					=       vocab_file
         snake_case					=       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.'''					)
         snake_case					=       jieba
         snake_case					=       str.maketrans(''' \n'''    ,      '''\u2582\u2583'''					)
    def 	a_    ( self    ,      __snake_case    ,      __snake_case = None					):
         snake_case					=       [self.sep_token_id]
         snake_case					=       [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 	a_    ( self    ,      __snake_case    ,      __snake_case = None					):
         snake_case					=       [self.sep_token_id]
         snake_case					=       [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 	a_    ( self    ,      __snake_case    ,      __snake_case = None					):
         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(lowerCamelCase__					):
              logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''					)
              return
         snake_case					=       os.path.join(
             lowerCamelCase__    ,      (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']					)

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

         return (out_vocab_file,)
    def 	a_    ( self    ,      __snake_case    ,      *__snake_case    ,      **__snake_case					):
         snake_case					=       [
             " ".join([x.translate(self.translator					) for x in self.jieba.cut(lowerCamelCase__    ,      cut_all=lowerCamelCase__					)]					)
             for text in batch_text_or_text_pairs
         ]
         return super()._batch_encode_plus(lowerCamelCase__    ,      *lowerCamelCase__    ,      **lowerCamelCase__					)




    def 	a_    ( self    ,      *__snake_case    ,      **__snake_case					):
         snake_case					=       super()._decode(*lowerCamelCase__    ,      **lowerCamelCase__					)
         snake_case					=       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,
)


_SCREAMING_SNAKE_CASE    :				Optional[int]       =					{
    "configuration_layoutlm": ["LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMConfig", "LayoutLMOnnxConfig"],
    "tokenization_layoutlm": ["LayoutLMTokenizer"],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _SCREAMING_SNAKE_CASE    :				str       =					["LayoutLMTokenizerFast"]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _SCREAMING_SNAKE_CASE    :				List[str]       =					[
     "LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST",
     "LayoutLMForMaskedLM",
     "LayoutLMForSequenceClassification",
     "LayoutLMForTokenClassification",
     "LayoutLMForQuestionAnswering",
     "LayoutLMModel",
     "LayoutLMPreTrainedModel",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _SCREAMING_SNAKE_CASE    :				Optional[int]       =					[
     "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

 _SCREAMING_SNAKE_CASE    :				Optional[int]       =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




