


from collections import OrderedDict
from typing import Mapping

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


__lowerCAmelCase									=				logging.get_logger(__name__)

__lowerCAmelCase									=				{
    '''squeezebert/squeezebert-uncased''': (
        '''https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json'''
    ),
    '''squeezebert/squeezebert-mnli''': '''https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json''',
    '''squeezebert/squeezebert-mnli-headless''': (
        '''https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json'''
    ),
}





class     __a     (       UpperCAmelCase__ ):
 __lowercase					:				Tuple  	=					SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
 __lowercase					:				Tuple  	=					'squeezebert'
 def __init__(  self							,					lowerCAmelCase__=30_522							,					lowerCAmelCase__=768							,					lowerCAmelCase__=12							,					lowerCAmelCase__=12							,					lowerCAmelCase__=3_072							,					lowerCAmelCase__="gelu"							,					lowerCAmelCase__=0.1							,					lowerCAmelCase__=0.1							,					lowerCAmelCase__=512							,					lowerCAmelCase__=2							,					lowerCAmelCase__=0.0_2							,					lowerCAmelCase__=1E-12							,					lowerCAmelCase__=0							,					lowerCAmelCase__=768							,					lowerCAmelCase__=4							,					lowerCAmelCase__=4							,					lowerCAmelCase__=4							,					lowerCAmelCase__=1							,					lowerCAmelCase__=4							,					lowerCAmelCase__=4							,					**lowerCAmelCase__							,					)   ->							List[Any]:




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

        lowercase__:  Any         =  vocab_size
        lowercase__:  Optional[int]         =  hidden_size
        lowercase__:  Optional[Any]         =  num_hidden_layers
        lowercase__:  Tuple         =  num_attention_heads
        lowercase__:  Any         =  hidden_act
        lowercase__:  Tuple         =  intermediate_size
        lowercase__:  int         =  hidden_dropout_prob
        lowercase__:  int         =  attention_probs_dropout_prob
        lowercase__:  Any         =  max_position_embeddings
        lowercase__:  str         =  type_vocab_size
        lowercase__:  Optional[int]         =  initializer_range
        lowercase__:  Optional[Any]         =  layer_norm_eps
        lowercase__:  Tuple         =  embedding_size
        lowercase__:  Union[str, Any]         =  q_groups
        lowercase__:  str         =  k_groups
        lowercase__:  int         =  v_groups
        lowercase__:  Dict         =  post_attention_groups
        lowercase__:  Optional[Any]         =  intermediate_groups
        lowercase__:  Dict         =  output_groups





class     __a     (       UpperCAmelCase__ ):
 @property
 def 						SCREAMING_SNAKE_CASE__  (  self					)   ->							Mapping[str, Mapping[int, str]]:




        '''simple docstring'''






        if self.task == "multiple-choice":
               lowercase__:  List[str]         =  {0: 'batch', 1: 'choice', 2: 'sequence'}
        else:
               lowercase__:  List[str]         =  {0: 'batch', 1: 'sequence'}
        return OrderedDict(
            [
                ('input_ids', dynamic_axis),
                ('attention_mask', dynamic_axis),
                ('token_type_ids', dynamic_axis),
            ]					)







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__)

