






'''simple docstring'''

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


lowerCamelCase_     =       logging.get_logger(__name__)

lowerCamelCase_     =       {
    'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json',
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}






class     a_						(      lowerCamelCase    ):
  lowercase							=				"""vit_mae"""

  def __init__(				self      ,		_SCREAMING_SNAKE_CASE=768      ,		_SCREAMING_SNAKE_CASE=12      ,		_SCREAMING_SNAKE_CASE=12      ,		_SCREAMING_SNAKE_CASE=3072      ,		_SCREAMING_SNAKE_CASE="gelu"      ,		_SCREAMING_SNAKE_CASE=0.0      ,		_SCREAMING_SNAKE_CASE=0.0      ,		_SCREAMING_SNAKE_CASE=0.0_2      ,		_SCREAMING_SNAKE_CASE=1e-12      ,		_SCREAMING_SNAKE_CASE=224      ,		_SCREAMING_SNAKE_CASE=16      ,		_SCREAMING_SNAKE_CASE=3      ,		_SCREAMING_SNAKE_CASE=True      ,		_SCREAMING_SNAKE_CASE=16      ,		_SCREAMING_SNAKE_CASE=512      ,		_SCREAMING_SNAKE_CASE=8      ,		_SCREAMING_SNAKE_CASE=2048      ,		_SCREAMING_SNAKE_CASE=0.7_5      ,		_SCREAMING_SNAKE_CASE=False      ,		**_SCREAMING_SNAKE_CASE      ,		)  ->				List[Any]:



        """simple docstring"""






        super().__init__(**_snake_case				)

        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      = layer_norm_eps
        UpperCamelCase      = image_size
        UpperCamelCase      = patch_size
        UpperCamelCase      = num_channels
        UpperCamelCase      = qkv_bias
        UpperCamelCase      = decoder_num_attention_heads
        UpperCamelCase      = decoder_hidden_size
        UpperCamelCase      = decoder_num_hidden_layers
        UpperCamelCase      = decoder_intermediate_size
        UpperCamelCase      = mask_ratio
        UpperCamelCase      = norm_pix_loss








'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE__     =       {
    'configuration_nllb_moe': [
        'NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'NllbMoeConfig',
    ]
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE__     =       [
         'NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST',
         'NllbMoeForConditionalGeneration',
         'NllbMoeModel',
         'NllbMoePreTrainedModel',
         'NllbMoeTop2Router',
         'NllbMoeSparseMLP',
     ]


if TYPE_CHECKING:
     from .configuration_nllb_moe import (
         NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP,
         NllbMoeConfig,
     )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_nllb_moe import (
              NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST,
              NllbMoeForConditionalGeneration,
              NllbMoeModel,
              NllbMoePreTrainedModel,
              NllbMoeSparseMLP,
              NllbMoeTopaRouter,
          )


else:
     import sys

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