





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


a__			:    Optional[int]			      =		logging.get_logger(__name__)

a__			:    str			      =		{
    'uw-madison/yoso-4096': 'https://huggingface.co/uw-madison/yoso-4096/resolve/main/config.json',
    # See all YOSO models at https://huggingface.co/models?filter=yoso
}





class UpperCAmelCase_							(   _SCREAMING_SNAKE_CASE   ):
  __lowerCAmelCase      :	Dict  	=      """yoso"""


  def __init__(       self   ,__snake_case=5_0_2_6_5   ,__snake_case=7_6_8   ,__snake_case=1_2   ,__snake_case=1_2   ,__snake_case=3_0_7_2   ,__snake_case="gelu"   ,__snake_case=0.1   ,__snake_case=0.1   ,__snake_case=4_0_9_6   ,__snake_case=1   ,__snake_case=0.02   ,__snake_case=1E-12   ,__snake_case="absolute"   ,__snake_case=True   ,__snake_case=9   ,__snake_case=6_4   ,__snake_case=None   ,__snake_case=True   ,__snake_case=True   ,__snake_case=1   ,__snake_case=0   ,__snake_case=2   ,**__snake_case   ,):



       """simple docstring"""





       super().__init__(pad_token_id=__lowerCamelCase   ,bos_token_id=__lowerCamelCase   ,eos_token_id=__lowerCamelCase   ,**__lowerCamelCase   )

       A_					      =					vocab_size
       A_					      =					max_position_embeddings
       A_					      =					hidden_size
       A_					      =					num_hidden_layers
       A_					      =					num_attention_heads
       A_					      =					intermediate_size
       A_					      =					hidden_act
       A_					      =					hidden_dropout_prob
       A_					      =					attention_probs_dropout_prob
       A_					      =					initializer_range
       A_					      =					type_vocab_size
       A_					      =					layer_norm_eps
       A_					      =					position_embedding_type
       A_					      =					use_expectation
       A_					      =					hash_code_len
       A_					      =					num_hash
       A_					      =					conv_window
       A_					      =					use_fast_hash
       A_					      =					lsh_backward






from typing import TYPE_CHECKING

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


a__			:    Tuple			      =		{'configuration_yoso': ['YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YosoConfig']}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a__			:    Optional[int]			      =		[
          'YOSO_PRETRAINED_MODEL_ARCHIVE_LIST',
          'YosoForMaskedLM',
          'YosoForMultipleChoice',
          'YosoForQuestionAnswering',
          'YosoForSequenceClassification',
          'YosoForTokenClassification',
          'YosoLayer',
          'YosoModel',
          'YosoPreTrainedModel',
      ]


if TYPE_CHECKING:
      from .configuration_yoso import YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP, YosoConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_yoso import (
                YOSO_PRETRAINED_MODEL_ARCHIVE_LIST,
                YosoForMaskedLM,
                YosoForMultipleChoice,
                YosoForQuestionAnswering,
                YosoForSequenceClassification,
                YosoForTokenClassification,
                YosoLayer,
                YosoModel,
                YosoPreTrainedModel,
            )


else:
      import sys

      a__			:    Union[str, Any]			      =		_LazyModule(__name__, globals()['__file__'], _import_structure)



