



'''simple docstring'''






def 					snake_case_      (  lowerCAmelCase_	)->	Tuple:





       '''simple docstring'''


       _UpperCAmelCase						:		List[str]      =				len(UpperCamelCase__	)
       for i in range(length - 1	):
              _UpperCAmelCase						:		List[Any]      =				False
              for j in range(length - 1 - i	):
                     if collection[j] > collection[j + 1]:
                            _UpperCAmelCase						:		str      =				True
                            _UpperCAmelCase						:		Tuple      =				collection[j + 1], collection[j]
              if not swapped:
                     break  # Stop iteration if the collection is sorted.
       return collection


if __name__ == "__main__":
   import doctest
   import time

   doctest.testmod()

   A_							:				List[Any]						=			input("""Enter numbers separated by a comma:""").strip()
   A_							:				Optional[int]						=			[int(item) for item in user_input.split(""",""")]
   A_							:				Union[str, Any]						=			time.process_time()
   print(*bubble_sort(unsorted), sep=""",""")
   print(f"""Processing time: {(time.process_time() - start)%1e9 + 7}""")








'''simple docstring'''






import copy
from typing import Dict

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
from ..bit import BitConfig


A_							:				List[str]						=			logging.get_logger(__name__)

A_							:				Optional[int]						=			{
    """google/vit-hybrid-base-bit-384""": """https://huggingface.co/vit-hybrid-base-bit-384/resolve/main/config.json""",
    # See all ViT hybrid models at https://huggingface.co/models?filter=vit
}



class 							lowercase (						_lowerCamelCase       ):


 """simple docstring"""


 UpperCAmelCase					=						"""vit-hybrid"""







 def __init__(							self						,a_=None						,a_=768						,a_=12						,a_=12						,a_=3_072						,a_="gelu"						,a_=0.0						,a_=0.0						,a_=0.02						,a_=1E-1_2						,a_=224						,a_=1						,a_=3						,a_=[1, 1_024, 24, 24]						,a_=True						,**a_						,)	->     Union[str, Any]:
        super().__init__(**a_							)

        if backbone_config is None:
               logger.info("""`backbone_config` is `None`. Initializing the config with a `BiT` backbone."""							)
               _UpperCAmelCase						:		Dict      =				{
                   """global_padding""": """same""",
                   """layer_type""": """bottleneck""",
                   """depths""": [3, 4, 9],
                   """out_features""": ["""stage3"""],
                   """embedding_dynamic_padding""": True,
               }

        if isinstance(a_						,a_							):
               if "model_type" in backbone_config:
                      _UpperCAmelCase						:		Dict      =				CONFIG_MAPPING[backbone_config["""model_type"""]]
               else:
                      logger.info(
                          """`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class."""							)
                      _UpperCAmelCase						:		str      =				BitConfig
               _UpperCAmelCase						:		List[str]      =				backbone_config_class(**a_							)

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







 def _snake_case				(							self							)	->     Dict[str, any]:
        _UpperCAmelCase						:		Optional[Any]      =				copy.deepcopy(self.__dict__							)
        _UpperCAmelCase						:		Optional[Any]      =				self.backbone_config.to_dict()
        _UpperCAmelCase						:		Tuple      =				self.__class__.model_type
        return output



