
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       =					{
    "MBZUAI/swiftformer-xs": "https://huggingface.co/MBZUAI/swiftformer-xs/resolve/main/config.json",
}







class 	lowerCamelCase						(    A_    ):
     UpperCAmelCase__							:				Dict 	=						"swiftformer"





     def __init__(self :       Dict							,       _A :       int=3							,       _A :       List[str]=[3, 3, 6, 4]							,       _A :       Optional[int]=[4_8, 5_6, 1_1_2, 2_2_0]							,       _A :       Union[str, Any]=4							,       _A :       Optional[int]=[True, True, True, True]							,       _A :       str="gelu"							,       _A :       int=3							,       _A :       Tuple=2							,       _A :       List[Any]=1							,       _A :       str=0.0							,       _A :       Any=True							,       _A :       Optional[Any]=1E-5							,       _A :       Any=1E-5							,       **_A :       Dict							,       )		->		List[Any]:
         super().__init__(**_A  )
         snake_case						=   num_channels
         snake_case						=   depths
         snake_case						=   embed_dims
         snake_case						=   mlp_ratio
         snake_case						=   downsamples
         snake_case						=   hidden_act
         snake_case						=   down_patch_size
         snake_case						=   down_stride
         snake_case						=   down_pad
         snake_case						=   drop_path_rate
         snake_case						=   use_layer_scale
         snake_case						=   layer_scale_init_value
         snake_case						=   batch_norm_eps







class 	lowerCamelCase						(    A_    ):
     UpperCAmelCase__							:				Tuple 	=						version.parse("1.11"    )





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





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



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_A       =					{
    "configuration_splinter": ["SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SplinterConfig"],
    "tokenization_splinter": ["SplinterTokenizer"],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A       =					["SplinterTokenizerFast"]

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A       =					[
       "SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST",
       "SplinterForQuestionAnswering",
       "SplinterForPreTraining",
       "SplinterLayer",
       "SplinterModel",
       "SplinterPreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
   from .tokenization_splinter import SplinterTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .tokenization_splinter_fast import SplinterTokenizerFast

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_splinter import (
          SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
          SplinterForPreTraining,
          SplinterForQuestionAnswering,
          SplinterLayer,
          SplinterModel,
          SplinterPreTrainedModel,
      )


else:
   import sys

   _A       =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

