




'''simple docstring'''







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


A			   =logging.get_logger(__name__)

A			   ={
    '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       _a  (     _a			):
       __a    :					Tuple           = '''yoso'''
       def __init__(     self						:     List[Any]       ,    lowercase						:     int=50_265       ,    lowercase						:     int=768       ,    lowercase						:     Optional[int]=12       ,    lowercase						:     Dict=12       ,    lowercase						:     Dict=3_072       ,    lowercase						:     List[Any]="gelu"       ,    lowercase						:     Any=0.1       ,    lowercase						:     Optional[Any]=0.1       ,    lowercase						:     Tuple=4_096       ,    lowercase						:     List[Any]=1       ,    lowercase						:     int=0.02       ,    lowercase						:     Union[str, Any]=1E-12       ,    lowercase						:     str="absolute"       ,    lowercase						:     Tuple=True       ,    lowercase						:     int=9       ,    lowercase						:     int=64       ,    lowercase						:     str=None       ,    lowercase						:     int=True       ,    lowercase						:     Tuple=True       ,    lowercase						:     Dict=1       ,    lowercase						:     List[str]=0       ,    lowercase						:     Any=2       ,    **lowercase						:     int       ,    ):



           '''simple docstring'''

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

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










'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A			   ={'configuration_dinat': ['DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DinatConfig']}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A			   =[
       'DINAT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'DinatForImageClassification',
       'DinatModel',
       'DinatPreTrainedModel',
       'DinatBackbone',
   ]

if TYPE_CHECKING:
   from .configuration_dinat import DINAT_PRETRAINED_CONFIG_ARCHIVE_MAP, DinatConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_dinat import (
          DINAT_PRETRAINED_MODEL_ARCHIVE_LIST,
          DinatBackbone,
          DinatForImageClassification,
          DinatModel,
          DinatPreTrainedModel,
      )

else:
   import sys

   A			   =_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




