





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


__A							   =							logging.get_logger(__name__)

__A							   =							{
    "microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
    # See all Cvt models at https://huggingface.co/models?filter=cvt
}



class   _SCREAMING_SNAKE_CASE		(      __SCREAMING_SNAKE_CASE       ):







 '''simple docstring'''
 lowercase_						=     "cvt"

 def __init__(self							:  List[str]			,					UpperCAmelCase_							:  int=3			,					UpperCAmelCase_							:  List[Any]=[7, 3, 3]			,					UpperCAmelCase_							:  List[Any]=[4, 2, 2]			,					UpperCAmelCase_							:  Union[str, Any]=[2, 1, 1]			,					UpperCAmelCase_							:  Optional[int]=[64, 192, 384]			,					UpperCAmelCase_							:  List[Any]=[1, 3, 6]			,					UpperCAmelCase_							:  Union[str, Any]=[1, 2, 10]			,					UpperCAmelCase_							:  List[Any]=[4.0, 4.0, 4.0]			,					UpperCAmelCase_							:  int=[0.0, 0.0, 0.0]			,					UpperCAmelCase_							:  Dict=[0.0, 0.0, 0.0]			,					UpperCAmelCase_							:  List[Any]=[0.0, 0.0, 0.1]			,					UpperCAmelCase_							:  str=[True, True, True]			,					UpperCAmelCase_							:  Optional[Any]=[False, False, True]			,					UpperCAmelCase_							:  Optional[Any]=["dw_bn", "dw_bn", "dw_bn"]			,					UpperCAmelCase_							:  Dict=[3, 3, 3]			,					UpperCAmelCase_							:  Optional[int]=[1, 1, 1]			,					UpperCAmelCase_							:  Optional[int]=[2, 2, 2]			,					UpperCAmelCase_							:  Any=[1, 1, 1]			,					UpperCAmelCase_							:  List[Any]=[1, 1, 1]			,					UpperCAmelCase_							:  Tuple=0.02			,					UpperCAmelCase_							:  Union[str, Any]=1E-1_2			,					**UpperCAmelCase_							:  Optional[Any]			,					)			->str:



   '''simple docstring'''



   super().__init__(**UpperCAmelCase_)
   lowerCamelCase__: Optional[int]         =num_channels
   lowerCamelCase__: Any         =patch_sizes
   lowerCamelCase__: List[Any]         =patch_stride
   lowerCamelCase__: List[str]         =patch_padding
   lowerCamelCase__: str         =embed_dim
   lowerCamelCase__: int         =num_heads
   lowerCamelCase__: int         =depth
   lowerCamelCase__: Dict         =mlp_ratio
   lowerCamelCase__: Union[str, Any]         =attention_drop_rate
   lowerCamelCase__: List[str]         =drop_rate
   lowerCamelCase__: Optional[Any]         =drop_path_rate
   lowerCamelCase__: Union[str, Any]         =qkv_bias
   lowerCamelCase__: List[str]         =cls_token
   lowerCamelCase__: Dict         =qkv_projection_method
   lowerCamelCase__: Tuple         =kernel_qkv
   lowerCamelCase__: Any         =padding_kv
   lowerCamelCase__: List[Any]         =stride_kv
   lowerCamelCase__: str         =padding_q
   lowerCamelCase__: int         =stride_q
   lowerCamelCase__: str         =initializer_range
   lowerCamelCase__: List[str]         =layer_norm_eps





"""simple docstring"""






from collections.abc import Callable

import numpy as np





def 				A_       ( snake_case__       ,					snake_case__       ,					snake_case__       ,					snake_case__       ,					snake_case__		)					->  np.ndarray:
			_UpperCamelCase					:str					     =	int(np.ceil((x_end - xa) / step_size		)		)
			_UpperCamelCase					:Union[str, Any]					     =	np.zeros((n + 1,)		)
			_UpperCamelCase					:List[str]					     =	ya
			_UpperCamelCase					:Any					     =	xa

			for k in range(snake_case__		):
						_UpperCamelCase					:Union[str, Any]					     =	y[k] + step_size * ode_func(snake_case__       ,					y[k]		)
						x += step_size

			return y


if __name__ == "__main__":
					import doctest

					doctest.testmod()

