'''simple docstring'''






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


_UpperCAmelCase						:    Any     					=					logging.get_logger(__name__)

_UpperCAmelCase						:    Tuple     					=					{
    '''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 lowercase_					(		_UpperCamelCase ):







   """simple docstring"""

   __lowerCAmelCase    						=      "cpmant"
   def __init__(			self			: Optional[Any],   UpperCamelCase__			: Union[str, Any] = 3_07_20,   UpperCamelCase__			: Tuple = 40_96,   UpperCamelCase__			: Union[str, Any] = 32,   UpperCamelCase__			: Tuple = 1_28,   UpperCamelCase__			: List[str] = 1_02_40,   UpperCamelCase__			: Union[str, Any] = 48,   UpperCamelCase__			: str = 0.0,   UpperCamelCase__			: List[Any] = 5_12,   UpperCamelCase__			: Optional[Any] = 20_48,   UpperCamelCase__			: Dict = 1e-6,   UpperCamelCase__			: List[str] = 1.0,   UpperCamelCase__			: Tuple = 32,   UpperCamelCase__			: Dict = 32,   UpperCamelCase__			: Union[str, Any] = 32,   UpperCamelCase__			: Dict = True,   **UpperCamelCase__			: Union[str, Any],   )     -> Any:
        super().__init__(**UpperCamelCase__    )
        _A								=     prompt_types
        _A								=     prompt_length
        _A								=     segment_types
        _A								=     hidden_size
        _A								=     num_attention_heads
        _A								=     dim_head
        _A								=     dim_ff
        _A								=     num_hidden_layers
        _A								=     position_bias_num_buckets
        _A								=     position_bias_max_distance
        _A								=     dropout_p
        _A								=     eps
        _A								=     use_cache
        _A								=     vocab_size
        _A								=     init_std




'''simple docstring'''






from typing import TYPE_CHECKING

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


_UpperCAmelCase						:    Optional[Any]     					=					{
    '''configuration_unispeech_sat''': ['''UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechSatConfig'''],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCAmelCase						:    Dict     					=					[
       '''UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''UniSpeechSatForAudioFrameClassification''',
       '''UniSpeechSatForCTC''',
       '''UniSpeechSatForPreTraining''',
       '''UniSpeechSatForSequenceClassification''',
       '''UniSpeechSatForXVector''',
       '''UniSpeechSatModel''',
       '''UniSpeechSatPreTrainedModel''',
   ]

if TYPE_CHECKING:
   from .configuration_unispeech_sat import UNISPEECH_SAT_PRETRAINED_CONFIG_ARCHIVE_MAP, UniSpeechSatConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_unispeech_sat import (
          UNISPEECH_SAT_PRETRAINED_MODEL_ARCHIVE_LIST,
          UniSpeechSatForAudioFrameClassification,
          UniSpeechSatForCTC,
          UniSpeechSatForPreTraining,
          UniSpeechSatForSequenceClassification,
          UniSpeechSatForXVector,
          UniSpeechSatModel,
          UniSpeechSatPreTrainedModel,
      )

else:
   import sys

   _UpperCAmelCase						:    int     					=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



