


'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


A__:    Optional[Any]					    =       {
    '''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''],
    '''tokenization_ctrl''': ['''CTRLTokenizer'''],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A__:    List[str]					    =       [
       '''CTRL_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''CTRLForSequenceClassification''',
       '''CTRLLMHeadModel''',
       '''CTRLModel''',
       '''CTRLPreTrainedModel''',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A__:    List[str]					    =       [
       '''TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''TFCTRLForSequenceClassification''',
       '''TFCTRLLMHeadModel''',
       '''TFCTRLModel''',
       '''TFCTRLPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_ctrl import CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP, CTRLConfig
   from .tokenization_ctrl import CTRLTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_ctrl import (
          CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
          CTRLForSequenceClassification,
          CTRLLMHeadModel,
          CTRLModel,
          CTRLPreTrainedModel,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_ctrl import (
          TF_CTRL_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFCTRLForSequenceClassification,
          TFCTRLLMHeadModel,
          TFCTRLModel,
          TFCTRLPreTrainedModel,
      )

else:
   import sys

   A__:    Optional[Any]					    =       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






'''simple docstring'''







from ...configuration_utils import PretrainedConfig
from ...utils import logging


A__:    Dict					    =       logging.get_logger(__name__)

A__:    Tuple					    =       {
    '''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json''',
}







class A__       (						UpperCAmelCase__      ):
      __UpperCamelCase       :  Tuple	       =							"roc_bert"






      def __init__( self			:Optional[int]     ,						SCREAMING_SNAKE_CASE			:Tuple=3_0_5_2_2     ,						SCREAMING_SNAKE_CASE			:List[str]=7_6_8     ,						SCREAMING_SNAKE_CASE			:Dict=1_2     ,						SCREAMING_SNAKE_CASE			:List[str]=1_2     ,						SCREAMING_SNAKE_CASE			:Tuple=3_0_7_2     ,						SCREAMING_SNAKE_CASE			:List[Any]="gelu"     ,						SCREAMING_SNAKE_CASE			:Union[str, Any]=0.1     ,						SCREAMING_SNAKE_CASE			:List[Any]=0.1     ,						SCREAMING_SNAKE_CASE			:int=5_1_2     ,						SCREAMING_SNAKE_CASE			:Optional[Any]=2     ,						SCREAMING_SNAKE_CASE			:Union[str, Any]=0.02     ,						SCREAMING_SNAKE_CASE			:Optional[Any]=1e-12     ,						SCREAMING_SNAKE_CASE			:Any=True     ,						SCREAMING_SNAKE_CASE			:List[Any]=0     ,						SCREAMING_SNAKE_CASE			:Optional[int]="absolute"     ,						SCREAMING_SNAKE_CASE			:Union[str, Any]=None     ,						SCREAMING_SNAKE_CASE			:List[Any]=True     ,						SCREAMING_SNAKE_CASE			:int=True     ,						SCREAMING_SNAKE_CASE			:Optional[int]=7_6_8     ,						SCREAMING_SNAKE_CASE			:Optional[Any]=9_1_0     ,						SCREAMING_SNAKE_CASE			:Union[str, Any]=5_1_2     ,						SCREAMING_SNAKE_CASE			:str=2_4_8_5_8     ,						SCREAMING_SNAKE_CASE			:List[Any]=True     ,						**SCREAMING_SNAKE_CASE			:Tuple     ,						)       ->					Optional[int]:




             '''simple docstring'''
             _a    : List[str]     					=vocab_size
             _a    : List[str]     					=max_position_embeddings
             _a    : Optional[Any]     					=hidden_size
             _a    : List[Any]     					=num_hidden_layers
             _a    : List[str]     					=num_attention_heads
             _a    : int     					=intermediate_size
             _a    : Any     					=hidden_act
             _a    : Dict     					=hidden_dropout_prob
             _a    : int     					=attention_probs_dropout_prob
             _a    : str     					=initializer_range
             _a    : Optional[int]     					=type_vocab_size
             _a    : Any     					=layer_norm_eps
             _a    : Any     					=use_cache
             _a    : Optional[int]     					=enable_pronunciation
             _a    : Optional[Any]     					=enable_shape
             _a    : Optional[Any]     					=pronunciation_embed_dim
             _a    : Tuple     					=pronunciation_vocab_size
             _a    : Union[str, Any]     					=shape_embed_dim
             _a    : Any     					=shape_vocab_size
             _a    : Tuple     					=concat_input
             _a    : List[str]     					=position_embedding_type
             _a    : List[str]     					=classifier_dropout
             super().__init__(pad_token_id=SCREAMING_SNAKE_CASE     ,						**SCREAMING_SNAKE_CASE	)


