




from collections import OrderedDict
from typing import Mapping

from packaging import version

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


UpperCAmelCase_									=	logging.get_logger(__name__)

UpperCAmelCase_									=	{
    '''microsoft/beit-base-patch16-224-pt22k''': (
        '''https://huggingface.co/microsoft/beit-base-patch16-224-pt22k/resolve/main/config.json'''
    ),
    # See all BEiT models at https://huggingface.co/models?filter=beit
}





class     lowerCamelCase__(					__lowerCamelCase):
      UpperCAmelCase__      :	Tuple    		=   "beit"
      def __init__(				self: List[Any]    ,       UpperCamelCase_: List[Any]=81_92    ,       UpperCamelCase_: int=7_68    ,       UpperCamelCase_: Tuple=12    ,       UpperCamelCase_: Optional[Any]=12    ,       UpperCamelCase_: Union[str, Any]=30_72    ,       UpperCamelCase_: Optional[Any]="gelu"    ,       UpperCamelCase_: Tuple=0.0    ,       UpperCamelCase_: int=0.0    ,       UpperCamelCase_: Optional[int]=0.02    ,       UpperCamelCase_: Tuple=1E-12    ,       UpperCamelCase_: Union[str, Any]=2_24    ,       UpperCamelCase_: Tuple=16    ,       UpperCamelCase_: Any=3    ,       UpperCamelCase_: List[Any]=False    ,       UpperCamelCase_: str=False    ,       UpperCamelCase_: Any=False    ,       UpperCamelCase_: Optional[Any]=False    ,       UpperCamelCase_: Optional[Any]=0.1    ,       UpperCamelCase_: Optional[int]=0.1    ,       UpperCamelCase_: Optional[Any]=True    ,       UpperCamelCase_: Any=[3, 5, 7, 11]    ,       UpperCamelCase_: str=[1, 2, 3, 6]    ,       UpperCamelCase_: List[str]=True    ,       UpperCamelCase_: Union[str, Any]=0.4    ,       UpperCamelCase_: Dict=2_56    ,       UpperCamelCase_: Any=1    ,       UpperCamelCase_: List[str]=False    ,       UpperCamelCase_: Tuple=2_55    ,       **UpperCamelCase_: List[str]    ,       ):
             super().__init__(**__A   )

             __lowerCamelCase   =						vocab_size
             __lowerCamelCase   =						hidden_size
             __lowerCamelCase   =						num_hidden_layers
             __lowerCamelCase   =						num_attention_heads
             __lowerCamelCase   =						intermediate_size
             __lowerCamelCase   =						hidden_act
             __lowerCamelCase   =						hidden_dropout_prob
             __lowerCamelCase   =						attention_probs_dropout_prob
             __lowerCamelCase   =						initializer_range
             __lowerCamelCase   =						layer_norm_eps

             __lowerCamelCase   =						image_size
             __lowerCamelCase   =						patch_size
             __lowerCamelCase   =						num_channels
             __lowerCamelCase   =						use_mask_token
             __lowerCamelCase   =						use_absolute_position_embeddings
             __lowerCamelCase   =						use_relative_position_bias
             __lowerCamelCase   =						use_shared_relative_position_bias
             __lowerCamelCase   =						layer_scale_init_value
             __lowerCamelCase   =						drop_path_rate
             __lowerCamelCase   =						use_mean_pooling
             # decode head attributes (semantic segmentation)
             __lowerCamelCase   =						out_indices
             __lowerCamelCase   =						pool_scales
             # auxiliary head attributes (semantic segmentation)
             __lowerCamelCase   =						use_auxiliary_head
             __lowerCamelCase   =						auxiliary_loss_weight
             __lowerCamelCase   =						auxiliary_channels
             __lowerCamelCase   =						auxiliary_num_convs
             __lowerCamelCase   =						auxiliary_concat_input
             __lowerCamelCase   =						semantic_loss_ignore_index





class     lowerCamelCase__(					__lowerCamelCase):
      UpperCAmelCase__      :	Any    		=   version.parse('1.11')
      @property
      def 			lowerCAmelCase__						(				self: Union[str, Any]   ):
             return OrderedDict(
                 [
                     ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
                 ]   )




      @property
      def 			lowerCAmelCase__						(				self: Tuple   ):
             return 1E-4








'''simple docstring'''
import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
    'split_dict'				,  [
        SplitDict(),
        SplitDict({'train': SplitInfo(name='train'				,  num_bytes=1337				,  num_examples=42				,  dataset_name='my_dataset'     )}     ),
        SplitDict({'train': SplitInfo(name='train'				,  num_bytes=1337				,  num_examples=42     )}     ),
        SplitDict({'train': SplitInfo()}     ),
    ]				,  )
def 				lowercase__   (   __lowercase						:  SplitDict     ) ->      int:



       """simple docstring"""






       __UpperCamelCase       =  split_dict._to_yaml_list()
       assert len(__lowercase     ) == len(__lowercase     )
       __UpperCamelCase       =  SplitDict._from_yaml_list(__lowercase     )
       for split_name, split_info in split_dict.items():
              # dataset_name field is deprecated, and is therefore not part of the YAML dump
              __UpperCamelCase       =  None
              # the split name of split_dict takes over the name of the split info object
              __UpperCamelCase       =  split_name
       assert split_dict == reloaded


@pytest.mark.parametrize(
    'split_info'				,  [SplitInfo(), SplitInfo(dataset_name=__lowercase     ), SplitInfo(dataset_name='my_dataset'     )]     )
def 				lowercase__   (   __lowercase						:  Dict     ) ->      Any:



       """simple docstring"""






       __UpperCamelCase       =  asdict(SplitDict({'train': split_info}     )     )
       assert "dataset_name" in split_dict_asdict["train"]
       assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name
