



'''simple docstring'''





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


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

__A							:							Optional[Any]  							=		{
    """microsoft/swinv2-tiny-patch4-window8-256""": (
        """https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"""
    ),
}
class 				lowercase       (							_a      ):


    '''simple docstring'''

    lowerCAmelCase__      				=							"swinv2"

    lowerCAmelCase__      				=							{
        "num_attention_heads": "num_heads",
        "num_hidden_layers": "num_layers",
    }

    def __init__(					self     :     List[str]				,     __lowerCamelCase     :     Tuple=224				,     __lowerCamelCase     :     Tuple=4				,     __lowerCamelCase     :     Optional[Any]=3				,     __lowerCamelCase     :     int=96				,     __lowerCamelCase     :     Union[str, Any]=[2, 2, 6, 2]				,     __lowerCamelCase     :     Optional[int]=[3, 6, 12, 24]				,     __lowerCamelCase     :     Optional[int]=7				,     __lowerCamelCase     :     List[str]=4.0				,     __lowerCamelCase     :     Union[str, Any]=True				,     __lowerCamelCase     :     Dict=0.0				,     __lowerCamelCase     :     Optional[Any]=0.0				,     __lowerCamelCase     :     Union[str, Any]=0.1				,     __lowerCamelCase     :     List[Any]="gelu"				,     __lowerCamelCase     :     Union[str, Any]=False				,     __lowerCamelCase     :     str=0.0_2				,     __lowerCamelCase     :     Union[str, Any]=1E-5				,     __lowerCamelCase     :     Union[str, Any]=32				,     **__lowerCamelCase     :     Any				,     )							->							List[Any]:

     '''simple docstring'''




     super().__init__(**_A     )

     lowerCamelCase__  =     image_size
     lowerCamelCase__  =     patch_size
     lowerCamelCase__  =     num_channels
     lowerCamelCase__  =     embed_dim
     lowerCamelCase__  =     depths
     lowerCamelCase__  =     len(_A     )
     lowerCamelCase__  =     num_heads
     lowerCamelCase__  =     window_size
     lowerCamelCase__  =     mlp_ratio
     lowerCamelCase__  =     qkv_bias
     lowerCamelCase__  =     hidden_dropout_prob
     lowerCamelCase__  =     attention_probs_dropout_prob
     lowerCamelCase__  =     drop_path_rate
     lowerCamelCase__  =     hidden_act
     lowerCamelCase__  =     use_absolute_embeddings
     lowerCamelCase__  =     layer_norm_eps
     lowerCamelCase__  =     initializer_range
     lowerCamelCase__  =     encoder_stride
     # we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
     # this indicates the channel dimension after the last stage of the model
     lowerCamelCase__  =     int(embed_dim * 2 ** (len(_A     ) - 1)     )
     lowerCamelCase__  =     (0, 0, 0, 0)









'''simple docstring'''





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

__A							:							Tuple  							=		{
    """google/mobilenet_v1_1.0_224""": """https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json""",
    """google/mobilenet_v1_0.75_192""": """https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json""",
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}
class 				lowercase       (							_lowerCamelCase      ):


    '''simple docstring'''

    lowerCAmelCase__      				=							"mobilenet_v1"

    def __init__(					self     :     Union[str, Any]				,     __lowerCamelCase     :     Tuple=3				,     __lowerCamelCase     :     Any=224				,     __lowerCamelCase     :     Tuple=1.0				,     __lowerCamelCase     :     Optional[int]=8				,     __lowerCamelCase     :     str="relu6"				,     __lowerCamelCase     :     Any=True				,     __lowerCamelCase     :     Union[str, Any]=0.9_9_9				,     __lowerCamelCase     :     List[Any]=0.0_2				,     __lowerCamelCase     :     str=0.0_0_1				,     **__lowerCamelCase     :     str				,     )							->							Dict:

     '''simple docstring'''




     super().__init__(**__lowerCamelCase     )

     if depth_multiplier <= 0:
      raise ValueError("depth_multiplier must be greater than zero."     )

     lowerCamelCase__  =     num_channels
     lowerCamelCase__  =     image_size
     lowerCamelCase__  =     depth_multiplier
     lowerCamelCase__  =     min_depth
     lowerCamelCase__  =     hidden_act
     lowerCamelCase__  =     tf_padding
     lowerCamelCase__  =     classifier_dropout_prob
     lowerCamelCase__  =     initializer_range
     lowerCamelCase__  =     layer_norm_eps
class 				lowercase       (							_lowerCamelCase      ):


    '''simple docstring'''

    lowerCAmelCase__      				=							version.parse("1.11"      )

    @property
    def    a__				(					self     :     List[str]     )							->							Mapping[str, Mapping[int, str]]:

     '''simple docstring'''




     return OrderedDict([("pixel_values", {0: "batch"})]     )

    @property
    def    a__				(					self     :     str     )							->							Mapping[str, Mapping[int, str]]:

     '''simple docstring'''




     if self.task == "image-classification":
      return OrderedDict([("logits", {0: "batch"})]     )
     else:
      return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]     )




    @property
    def    a__				(					self     :     List[Any]     )							->							float:

     '''simple docstring'''




     return 1E-4

