code: 
  
  
  
  
  from ...configuration_utils import PretrainedConfig
  from ...utils import logging
  
  
  UpperCamelCase__				       =			logging.get_logger(__name__)
  
  UpperCamelCase__				       =			{
      'openbmb/cpm-ant-10b': 'https://huggingface.co/openbmb/cpm-ant-10b/blob/main/config.json'
      # See all CPMAnt models at https://huggingface.co/models?filter=cpmant
  }
  
  class 						UpperCAmelCase__   (      UpperCamelCase__		):
  
  
  
       '''simple docstring'''
       UpperCAmelCase_         =  '''cpmant'''
  
  
  
  
       def __init__( self       :       Dict	,      UpperCamelCase       :       Optional[Any] = 3_07_20	,      UpperCamelCase       :       Optional[int] = 40_96	,      UpperCamelCase       :       str = 32	,      UpperCamelCase       :       Tuple = 1_28	,      UpperCamelCase       :       Union[str, Any] = 1_02_40	,      UpperCamelCase       :       Dict = 48	,      UpperCamelCase       :       List[str] = 0.0	,      UpperCamelCase       :       Optional[Any] = 5_12	,      UpperCamelCase       :       Union[str, Any] = 20_48	,      UpperCamelCase       :       Optional[Any] = 1E-6	,      UpperCamelCase       :       Optional[int] = 1.0	,      UpperCamelCase       :       Union[str, Any] = 32	,      UpperCamelCase       :       List[Any] = 32	,      UpperCamelCase       :       List[Any] = 32	,      UpperCamelCase       :       str = True	,      **UpperCamelCase       :       str	,      ):
  
  
  
  
  
              """simple docstring"""
  
  
  
              super().__init__(**snake_case_		)
              _lowercase					:				Tuple           =			prompt_types
              _lowercase					:				Tuple           =			prompt_length
              _lowercase					:				Optional[Any]           =			segment_types
              _lowercase					:				Tuple           =			hidden_size
              _lowercase					:				Optional[Any]           =			num_attention_heads
              _lowercase					:				str           =			dim_head
              _lowercase					:				Tuple           =			dim_ff
              _lowercase					:				Any           =			num_hidden_layers
              _lowercase					:				Tuple           =			position_bias_num_buckets
              _lowercase					:				Tuple           =			position_bias_max_distance
              _lowercase					:				Optional[int]           =			dropout_p
              _lowercase					:				int           =			eps
              _lowercase					:				Any           =			use_cache
              _lowercase					:				Optional[int]           =			vocab_size
              _lowercase					:				List[Any]           =			init_std
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
  
  
  UpperCamelCase__				       =			{
      'configuration_wav2vec2_conformer': [
          'WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
          'Wav2Vec2ConformerConfig',
      ],
  }
  
  
  try:
     if not is_torch_available():
        raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
     pass
  else:
     UpperCamelCase__				       =			[
         'WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'Wav2Vec2ConformerForAudioFrameClassification',
         'Wav2Vec2ConformerForCTC',
         'Wav2Vec2ConformerForPreTraining',
         'Wav2Vec2ConformerForSequenceClassification',
         'Wav2Vec2ConformerForXVector',
         'Wav2Vec2ConformerModel',
         'Wav2Vec2ConformerPreTrainedModel',
     ]
  
  if TYPE_CHECKING:
     from .configuration_wavaveca_conformer import (
         WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
         WavaVecaConformerConfig,
     )
  
     try:
        if not is_torch_available():
           raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
        pass
     else:
        from .modeling_wavaveca_conformer import (
            WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            WavaVecaConformerForAudioFrameClassification,
            WavaVecaConformerForCTC,
            WavaVecaConformerForPreTraining,
            WavaVecaConformerForSequenceClassification,
            WavaVecaConformerForXVector,
            WavaVecaConformerModel,
            WavaVecaConformerPreTrainedModel,
        )
  
  else:
     import sys
  
     UpperCamelCase__				       =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)