





"""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


__magic_name__					:				Optional[int]	= logging.get_logger(__name__)

__magic_name__					:				Tuple	= {
    """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__ (      __SCREAMING_SNAKE_CASE  ):

			"""simple docstring"""
			__lowerCAmelCase    :							Any								=     """vit-hybrid"""







			def __init__(			self	,      _A=None	,      _A=7_6_8	,      _A=1_2	,      _A=1_2	,      _A=3_0_7_2	,      _A="gelu"	,      _A=0.0	,      _A=0.0	,      _A=0.02	,      _A=1e-1_2	,      _A=2_2_4	,      _A=1	,      _A=3	,      _A=[1, 1_0_2_4, 2_4, 2_4]	,      _A=True	,      **_A	,      ):






									'''simple docstring'''







									super().__init__(**_A						)

									if backbone_config is None:
															logger.info("""`backbone_config` is `None`. Initializing the config with a `BiT` backbone."""						)
															UpperCamelCase							:		Union[str, Any]							      = {
															    """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							:		Union[str, Any]							      = 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							:		Tuple							      = backbone_featmap_shape
									UpperCamelCase							:		List[str]							      = backbone_config
									UpperCamelCase							:		List[Any]							      = hidden_size
									UpperCamelCase							:		Dict							      = num_hidden_layers
									UpperCamelCase							:		Union[str, Any]							      = num_attention_heads
									UpperCamelCase							:		Optional[int]							      = intermediate_size
									UpperCamelCase							:		Any							      = hidden_act
									UpperCamelCase							:		Optional[Any]							      = hidden_dropout_prob
									UpperCamelCase							:		Optional[Any]							      = attention_probs_dropout_prob
									UpperCamelCase							:		Tuple							      = initializer_range
									UpperCamelCase							:		List[Any]							      = layer_norm_eps
									UpperCamelCase							:		List[Any]							      = image_size
									UpperCamelCase							:		str							      = patch_size
									UpperCamelCase							:		List[str]							      = num_channels
									UpperCamelCase							:		Tuple							      = qkv_bias







			def      _a			(			self						):






									'''simple docstring'''







									UpperCamelCase							:		List[str]							      = copy.deepcopy(self.__dict__						)
									UpperCamelCase							:		Optional[Any]							      = self.backbone_config.to_dict()
									UpperCamelCase							:		str							      = self.__class__.model_type
									return output










"""simple docstring"""


def     UpperCamelCase       (SCREAMING_SNAKE_CASE    ):
						UpperCamelCase							:		Tuple							      = 0
						for plain_chr in plain_text:
												UpperCamelCase							:		List[str]							      = (
												    ord(SCREAMING_SNAKE_CASE    ) + (hash_value << 6) + (hash_value << 16) - hash_value
												)
						return hash_value



