


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


__lowerCAmelCase									=				logging.get_logger(__name__)

__lowerCAmelCase									=				{
    '''microsoft/mpnet-base''': '''https://huggingface.co/microsoft/mpnet-base/resolve/main/config.json''',
}





class     __a     (       UpperCAmelCase__ ):
 __lowercase					:				Union[str, Any]  	=					'mpnet'
 def __init__(  self							,					lowerCAmelCase__=30_527							,					lowerCAmelCase__=768							,					lowerCAmelCase__=12							,					lowerCAmelCase__=12							,					lowerCAmelCase__=3_072							,					lowerCAmelCase__="gelu"							,					lowerCAmelCase__=0.1							,					lowerCAmelCase__=0.1							,					lowerCAmelCase__=512							,					lowerCAmelCase__=0.0_2							,					lowerCAmelCase__=1E-12							,					lowerCAmelCase__=32							,					lowerCAmelCase__=1							,					lowerCAmelCase__=0							,					lowerCAmelCase__=2							,					**lowerCAmelCase__							,					)   ->							Dict:




        '''simple docstring'''
        super().__init__(pad_token_id=__lowerCAmelCase							,					bos_token_id=__lowerCAmelCase							,					eos_token_id=__lowerCAmelCase							,					**__lowerCAmelCase					)

        lowercase__:  str         =  vocab_size
        lowercase__:  Optional[int]         =  hidden_size
        lowercase__:  Union[str, Any]         =  num_hidden_layers
        lowercase__:  Tuple         =  num_attention_heads
        lowercase__:  Tuple         =  hidden_act
        lowercase__:  List[Any]         =  intermediate_size
        lowercase__:  str         =  hidden_dropout_prob
        lowercase__:  Union[str, Any]         =  attention_probs_dropout_prob
        lowercase__:  Union[str, Any]         =  max_position_embeddings
        lowercase__:  List[str]         =  initializer_range
        lowercase__:  str         =  layer_norm_eps
        lowercase__:  List[str]         =  relative_attention_num_buckets







from typing import TYPE_CHECKING

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


A_		:  Any										=  {
    '''configuration_align''': [
        '''ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''AlignConfig''',
        '''AlignTextConfig''',
        '''AlignVisionConfig''',
    ],
    '''processing_align''': ['''AlignProcessor'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:  Optional[int]										=  [
         '''ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''AlignModel''',
         '''AlignPreTrainedModel''',
         '''AlignTextModel''',
         '''AlignVisionModel''',
     ]

if TYPE_CHECKING:
     from .configuration_align import (
         ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP,
         AlignConfig,
         AlignTextConfig,
         AlignVisionConfig,
     )
     from .processing_align import AlignProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_align import (
              ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST,
              AlignModel,
              AlignPreTrainedModel,
              AlignTextModel,
              AlignVisionModel,
          )

else:
     import sys

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

