

'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


a=  logging.get_logger(__name__)

a=  {
    '''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json''',
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}






class 			__lowercase		(						_lowerCamelCase						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						'''vit_msn'''







     def __init__(		self     ,			_lowerCamelCase=7_6_8     ,			_lowerCamelCase=1_2     ,			_lowerCamelCase=1_2     ,			_lowerCamelCase=3_0_7_2     ,			_lowerCamelCase="gelu"     ,			_lowerCamelCase=0.0     ,			_lowerCamelCase=0.0     ,			_lowerCamelCase=0.0_2     ,			_lowerCamelCase=1E-0_6     ,			_lowerCamelCase=2_2_4     ,			_lowerCamelCase=1_6     ,			_lowerCamelCase=3     ,			_lowerCamelCase=True     ,			**_lowerCamelCase     ,			):
         super().__init__(**_lowerCamelCase    )

         __UpperCamelCase	:	Dict		    =  hidden_size
         __UpperCamelCase	:	int		    =  num_hidden_layers
         __UpperCamelCase	:	int		    =  num_attention_heads
         __UpperCamelCase	:	List[Any]		    =  intermediate_size
         __UpperCamelCase	:	int		    =  hidden_act
         __UpperCamelCase	:	Optional[int]		    =  hidden_dropout_prob
         __UpperCamelCase	:	Union[str, Any]		    =  attention_probs_dropout_prob
         __UpperCamelCase	:	List[str]		    =  initializer_range
         __UpperCamelCase	:	List[str]		    =  layer_norm_eps
         __UpperCamelCase	:	List[str]		    =  image_size
         __UpperCamelCase	:	Tuple		    =  patch_size
         __UpperCamelCase	:	Optional[Any]		    =  num_channels
         __UpperCamelCase	:	Tuple		    =  qkv_bias




'''simple docstring'''
from typing import TYPE_CHECKING

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


a=  {}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a=  ['''NllbTokenizer''']

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a=  ['''NllbTokenizerFast''']


if TYPE_CHECKING:
  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_nllb import NllbTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_nllb_fast import NllbTokenizerFast

else:
  import sys

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



