


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


_A		       =						logging.get_logger(__name__)

_A		       =						{
    '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     UpperCAmelCase__       (					A_		):



    """simple docstring"""






    UpperCAmelCase__						:		Union[str, Any]      =  "beit"






    def __init__(			self					,   A_=8192					,   A_=768					,   A_=12					,   A_=12					,   A_=3072					,   A_="gelu"					,   A_=0.0					,   A_=0.0					,   A_=0.02					,   A_=1E-12					,   A_=224					,   A_=16					,   A_=3					,   A_=False					,   A_=False					,   A_=False					,   A_=False					,   A_=0.1					,   A_=0.1					,   A_=True					,   A_=[3, 5, 7, 11]					,   A_=[1, 2, 3, 6]					,   A_=True					,   A_=0.4					,   A_=256					,   A_=1					,   A_=False					,   A_=255					,   **A_					,   )  ->       List[str]:
         super().__init__(**A_    )

         __UpperCamelCase    							=vocab_size
         __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    							=use_mask_token
         __UpperCamelCase    							=use_absolute_position_embeddings
         __UpperCamelCase    							=use_relative_position_bias
         __UpperCamelCase    							=use_shared_relative_position_bias
         __UpperCamelCase    							=layer_scale_init_value
         __UpperCamelCase    							=drop_path_rate
         __UpperCamelCase    							=use_mean_pooling
         # decode head attributes (semantic segmentation)
         __UpperCamelCase    							=out_indices
         __UpperCamelCase    							=pool_scales
         # auxiliary head attributes (semantic segmentation)
         __UpperCamelCase    							=use_auxiliary_head
         __UpperCamelCase    							=auxiliary_loss_weight
         __UpperCamelCase    							=auxiliary_channels
         __UpperCamelCase    							=auxiliary_num_convs
         __UpperCamelCase    							=auxiliary_concat_input
         __UpperCamelCase    							=semantic_loss_ignore_index






class     UpperCAmelCase__       (					A_		):



    """simple docstring"""






    UpperCAmelCase__						:		Tuple      =  version.parse("1.11"		)






    @property
    def _a					(			self    )  ->       Mapping[str, Mapping[int, str]]:
         return OrderedDict(
             [
                 ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
             ]    )






    @property
    def _a					(			self    )  ->       float:
         return 1E-4












def      _A       (		SCREAMING_SNAKE_CASE     :   int = 50						):





  """simple docstring"""



  a__	:					Any										=[1] * (length + 1)

  for row_length in range(3       ,       length + 1						):
    for block_length in range(3       ,       row_length + 1						):
      for block_start in range(row_length - block_length						):
        ways_number[row_length] += ways_number[
            row_length - block_start - block_length - 1
        ]

      ways_number[row_length] += 1

  return ways_number[length]


if __name__ == "__main__":
     print(F"""{solution() = }""")






