





'''simple docstring'''






import collections
import os
from typing import List, Optional, Tuple

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
      import jieba

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__lowerCamelCase						: Tuple		=   logging.get_logger(__name__)

__lowerCamelCase						: Tuple		=   {'vocab_file': 'vocab.txt'}

__lowerCamelCase						: Optional[int]		=   {
    'vocab_file': {
        'openbmb/cpm-ant-10b': 'https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt',
    },
}

__lowerCamelCase						: Any		=   {
    'openbmb/cpm-ant-10b': 1024,
}


def 					_a   (__SCREAMING_SNAKE_CASE   ):


  """simple docstring"""

  _UpperCamelCase       			=collections.OrderedDict()
  with open(__SCREAMING_SNAKE_CASE  ,      '''r'''  ,      encoding='''utf-8'''   ) as reader:
    _UpperCamelCase       			=reader.readlines()
  for index, token in enumerate(__SCREAMING_SNAKE_CASE   ):
    _UpperCamelCase       			=token.rstrip('''\n'''   )
    _UpperCamelCase       			=index
  return vocab







class 		UpperCAmelCase   (				lowercase_):


  """simple docstring"""







  def __init__(				self    :					int							,	UpperCamelCase__    :					Tuple							,	UpperCamelCase__    :					str="<unk>"							,	UpperCamelCase__    :					Dict=200  )     ->						str:
    _UpperCamelCase       			=vocab
    _UpperCamelCase       			=unk_token
    _UpperCamelCase       			=max_input_chars_per_word




  def   UpperCamelCase__      (				self    :					Any							,	UpperCamelCase__    :					Union[str, Any]  )     ->						Tuple:
    _UpperCamelCase       			=list(UpperCamelCase__  )
    if len(UpperCamelCase__  ) > self.max_input_chars_per_word:
      return [self.unk_token]

    _UpperCamelCase       			=0
    _UpperCamelCase       			=[]
    while start < len(UpperCamelCase__  ):
      _UpperCamelCase       			=len(UpperCamelCase__  )
      _UpperCamelCase       			=None
      while start < end:
        _UpperCamelCase       			=''''''.join(chars[start:end]  )
        if substr in self.vocab:
          _UpperCamelCase       			=substr
          break
        end -= 1
      if cur_substr is None:
        sub_tokens.append(self.unk_token  )
        start += 1
      else:
        sub_tokens.append(UpperCamelCase__  )
        _UpperCamelCase       			=end

    return sub_tokens







class 		UpperCAmelCase   (				lowercase_):


  """simple docstring"""







  lowerCAmelCase_					=				VOCAB_FILES_NAMES
  lowerCAmelCase_					=				PRETRAINED_VOCAB_FILES_MAP
  lowerCAmelCase_					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  lowerCAmelCase_					=				["""input_ids""", """attention_mask"""]
  lowerCAmelCase_					=				False


  def __init__(				self    :					Optional[int]							,	UpperCamelCase__    :					Any							,	UpperCamelCase__    :					Dict="<d>"							,	UpperCamelCase__    :					Dict="</d>"							,	UpperCamelCase__    :					List[str]="<s>"							,	UpperCamelCase__    :					Tuple="</s>"							,	UpperCamelCase__    :					Union[str, Any]="<pad>"							,	UpperCamelCase__    :					Union[str, Any]="<unk>"							,	UpperCamelCase__    :					str="</n>"							,	UpperCamelCase__    :					Tuple="</_>"							,	UpperCamelCase__    :					int="left"							,	**UpperCamelCase__    :					Tuple							,	)     ->						Union[str, Any]:
    requires_backends(self							,	['''jieba''']  )
    super().__init__(
        bod_token=UpperCamelCase__							,	eod_token=UpperCamelCase__							,	bos_token=UpperCamelCase__							,	eos_token=UpperCamelCase__							,	pad_token=UpperCamelCase__							,	unk_token=UpperCamelCase__							,	line_token=UpperCamelCase__							,	space_token=UpperCamelCase__							,	padding_side=UpperCamelCase__							,	**UpperCamelCase__							,	)
    _UpperCamelCase       			=bod_token
    _UpperCamelCase       			=eod_token
    _UpperCamelCase       			=load_vocab(UpperCamelCase__  )
    _UpperCamelCase       			=self.encoder[space_token]
    _UpperCamelCase       			=self.encoder[line_token]

    del self.encoder[space_token]
    del self.encoder[line_token]

    _UpperCamelCase       			=collections.OrderedDict(sorted(self.encoder.items()							,	key=lambda UpperCamelCase__  : x[1]  )  )
    _UpperCamelCase       			={v: k for k, v in self.encoder.items()}

    _UpperCamelCase       			=WordpieceTokenizer(vocab=self.encoder							,	unk_token=self.unk_token  )


  @property
  def   UpperCamelCase__      (				self    :					Any  )     ->						str:
    return self.encoder[self.bod_token]


  @property
  def   UpperCamelCase__      (				self    :					List[str]  )     ->						Union[str, Any]:
    return self.encoder[self.eod_token]


  @property
  def   UpperCamelCase__      (				self    :					List[str]  )     ->						Tuple:
    return self.encoder["\n"]


  @property
  def   UpperCamelCase__      (				self    :					Optional[int]  )     ->						int:
    return len(self.encoder  )


  def   UpperCamelCase__      (				self    :					str  )     ->						Optional[int]:
    return dict(self.encoder							,	**self.added_tokens_encoder  )


  def   UpperCamelCase__      (				self    :					str							,	UpperCamelCase__    :					Optional[int]  )     ->						Union[str, Any]:
    _UpperCamelCase       			=[]
    for x in jieba.cut(UpperCamelCase__							,	cut_all=UpperCamelCase__  ):
      output_tokens.extend(self.wordpiece_tokenizer.tokenize(UpperCamelCase__  )  )
    return output_tokens


  def   UpperCamelCase__      (				self    :					List[Any]							,	UpperCamelCase__    :					Optional[int]							,	**UpperCamelCase__    :					List[str]  )     ->						Dict:
    _UpperCamelCase       			=[i for i in token_ids if i >= 0]
    _UpperCamelCase       			=[
        x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
    ]
    return super()._decode(UpperCamelCase__							,	**UpperCamelCase__  )


  def   UpperCamelCase__      (				self    :					Optional[int]							,	UpperCamelCase__    :					Union[str, Any]  )     ->						Union[str, Any]:
    return token in self.encoder


  def   UpperCamelCase__      (				self    :					List[str]							,	UpperCamelCase__    :					List[str]  )     ->						str:
    return "".join(UpperCamelCase__  )


  def   UpperCamelCase__      (				self    :					List[str]							,	UpperCamelCase__    :					List[Any]  )     ->						List[Any]:
    return self.encoder.get(UpperCamelCase__							,	self.encoder.get(self.unk_token  )  )


  def   UpperCamelCase__      (				self    :					Optional[int]							,	UpperCamelCase__    :					Dict  )     ->						int:
    return self.decoder.get(UpperCamelCase__							,	self.unk_token  )


  def   UpperCamelCase__      (				self    :					Dict							,	UpperCamelCase__    :					str							,	UpperCamelCase__    :					Optional[str] = None  )     ->						Tuple[str]:
    if os.path.isdir(UpperCamelCase__  ):
      _UpperCamelCase       			=os.path.join(
          UpperCamelCase__							,	(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )
    else:
      _UpperCamelCase       			=(filename_prefix + '''-''' if filename_prefix else '''''') + save_directory
    _UpperCamelCase       			=0
    if " " in self.encoder:
      _UpperCamelCase       			=self.encoder[''' ''']
      del self.encoder[" "]
    if "\n" in self.encoder:
      _UpperCamelCase       			=self.encoder['''\n''']
      del self.encoder["\n"]
    _UpperCamelCase       			=collections.OrderedDict(sorted(self.encoder.items()							,	key=lambda UpperCamelCase__  : x[1]  )  )
    with open(UpperCamelCase__							,	'''w'''							,	encoding='''utf-8'''  ) as writer:
      for token, token_index in self.encoder.items():
        if index != token_index:
          logger.warning(
              F'''Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'''
              ''' Please check that the vocabulary is not corrupted!'''  )
          _UpperCamelCase       			=token_index
        writer.write(token + '''\n'''  )
        index += 1
    return (vocab_file,)


  def   UpperCamelCase__      (				self    :					List[Any]							,	UpperCamelCase__    :					List[int]							,	UpperCamelCase__    :					List[int] = None  )     ->						List[int]:
    if token_ids_a is None:
      return [self.bos_token_id] + token_ids_a
    return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a




  def   UpperCamelCase__      (				self    :					Tuple							,	UpperCamelCase__    :					List[int]							,	UpperCamelCase__    :					Optional[List[int]] = None							,	UpperCamelCase__    :					bool = False  )     ->						List[int]:

    if already_has_special_tokens:
      return super().get_special_tokens_mask(
          token_ids_a=UpperCamelCase__							,	token_ids_a=UpperCamelCase__							,	already_has_special_tokens=UpperCamelCase__  )

    if token_ids_a is not None:
      return [1] + ([0] * len(UpperCamelCase__  )) + [1] + ([0] * len(UpperCamelCase__  ))
    return [1] + ([0] * len(UpperCamelCase__  ))













'''simple docstring'''






from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


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

__lowerCamelCase						: int		=   {
    'google/mobilenet_v2_1.4_224': 'https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json',
    'google/mobilenet_v2_1.0_224': 'https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json',
    'google/mobilenet_v2_0.75_160': 'https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json',
    'google/mobilenet_v2_0.35_96': 'https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json',
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}







class 		UpperCAmelCase   (				lowercase_):


  """simple docstring"""







  lowerCAmelCase_					=				"""mobilenet_v2"""


  def __init__(				self    :					Tuple							,	UpperCamelCase__    :					Union[str, Any]=3							,	UpperCamelCase__    :					Dict=224							,	UpperCamelCase__    :					str=1.0							,	UpperCamelCase__    :					List[Any]=8							,	UpperCamelCase__    :					Union[str, Any]=8							,	UpperCamelCase__    :					str=6							,	UpperCamelCase__    :					str=32							,	UpperCamelCase__    :					str=True							,	UpperCamelCase__    :					int=True							,	UpperCamelCase__    :					str="relu6"							,	UpperCamelCase__    :					Tuple=True							,	UpperCamelCase__    :					List[str]=0.8							,	UpperCamelCase__    :					List[str]=0.02							,	UpperCamelCase__    :					str=0.001							,	UpperCamelCase__    :					Dict=255							,	**UpperCamelCase__    :					Tuple							,	)     ->						List[Any]:
    super().__init__(**UpperCamelCase__  )

    if depth_multiplier <= 0:
      raise ValueError('''depth_multiplier must be greater than zero.'''  )

    _UpperCamelCase       			=num_channels
    _UpperCamelCase       			=image_size
    _UpperCamelCase       			=depth_multiplier
    _UpperCamelCase       			=depth_divisible_by
    _UpperCamelCase       			=min_depth
    _UpperCamelCase       			=expand_ratio
    _UpperCamelCase       			=output_stride
    _UpperCamelCase       			=first_layer_is_expansion
    _UpperCamelCase       			=finegrained_output
    _UpperCamelCase       			=hidden_act
    _UpperCamelCase       			=tf_padding
    _UpperCamelCase       			=classifier_dropout_prob
    _UpperCamelCase       			=initializer_range
    _UpperCamelCase       			=layer_norm_eps
    _UpperCamelCase       			=semantic_loss_ignore_index







class 		UpperCAmelCase   (				lowercase_):


  """simple docstring"""







  lowerCAmelCase_					=				version.parse("""1.11""")


  @property
  def   UpperCamelCase__      (				self    :					str  )     ->						Mapping[str, Mapping[int, str]]:
    return OrderedDict([('''pixel_values''', {0: '''batch'''})]  )


  @property
  def   UpperCamelCase__      (				self    :					Optional[Any]  )     ->						Mapping[str, Mapping[int, str]]:
    if self.task == "image-classification":
      return OrderedDict([('''logits''', {0: '''batch'''})]  )
    else:
      return OrderedDict([('''last_hidden_state''', {0: '''batch'''}), ('''pooler_output''', {0: '''batch'''})]  )




  @property
  def   UpperCamelCase__      (				self    :					List[Any]  )     ->						float:
    return 1E-4






