



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


__lowerCamelCase     :							int  							=				logging.get_logger(__name__)

__lowerCamelCase     :							List[Any]  							=				{
    "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  __magic_name__   (							_UpperCAmelCase						):
		lowercase      :       Optional[Any]          ='''cvt'''






		def __init__(						self      :     Union[str, Any]				,		UpperCamelCase__      :     Any=3				,		UpperCamelCase__      :     str=[7, 3, 3]				,		UpperCamelCase__      :     List[Any]=[4, 2, 2]				,		UpperCamelCase__      :     Dict=[2, 1, 1]				,		UpperCamelCase__      :     Optional[Any]=[64, 1_92, 3_84]				,		UpperCamelCase__      :     Dict=[1, 3, 6]				,		UpperCamelCase__      :     List[str]=[1, 2, 10]				,		UpperCamelCase__      :     Tuple=[4.0, 4.0, 4.0]				,		UpperCamelCase__      :     Dict=[0.0, 0.0, 0.0]				,		UpperCamelCase__      :     Optional[Any]=[0.0, 0.0, 0.0]				,		UpperCamelCase__      :     str=[0.0, 0.0, 0.1]				,		UpperCamelCase__      :     Union[str, Any]=[True, True, True]				,		UpperCamelCase__      :     int=[False, False, True]				,		UpperCamelCase__      :     int=["dw_bn", "dw_bn", "dw_bn"]				,		UpperCamelCase__      :     Optional[Any]=[3, 3, 3]				,		UpperCamelCase__      :     Optional[int]=[1, 1, 1]				,		UpperCamelCase__      :     Optional[Any]=[2, 2, 2]				,		UpperCamelCase__      :     Tuple=[1, 1, 1]				,		UpperCamelCase__      :     List[Any]=[1, 1, 1]				,		UpperCamelCase__      :     List[Any]=0.02				,		UpperCamelCase__      :     List[str]=1e-1_2				,		**UpperCamelCase__      :     Tuple				,		)				->					Tuple:
								'''simple docstring'''







								super().__init__(**lowercase__      )
								UpperCAmelCase         =     num_channels
								UpperCAmelCase         =     patch_sizes
								UpperCAmelCase         =     patch_stride
								UpperCAmelCase         =     patch_padding
								UpperCAmelCase         =     embed_dim
								UpperCAmelCase         =     num_heads
								UpperCAmelCase         =     depth
								UpperCAmelCase         =     mlp_ratio
								UpperCAmelCase         =     attention_drop_rate
								UpperCAmelCase         =     drop_rate
								UpperCAmelCase         =     drop_path_rate
								UpperCAmelCase         =     qkv_bias
								UpperCAmelCase         =     cls_token
								UpperCAmelCase         =     qkv_projection_method
								UpperCAmelCase         =     kernel_qkv
								UpperCAmelCase         =     padding_kv
								UpperCAmelCase         =     stride_kv
								UpperCAmelCase         =     padding_q
								UpperCAmelCase         =     stride_q
								UpperCAmelCase         =     initializer_range
								UpperCAmelCase         =     layer_norm_eps








from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__lowerCamelCase     :							Any  							=				{
    "configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase     :							Optional[int]  							=				[
		    "MEGA_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "MegaForCausalLM",
		    "MegaForMaskedLM",
		    "MegaForMultipleChoice",
		    "MegaForQuestionAnswering",
		    "MegaForSequenceClassification",
		    "MegaForTokenClassification",
		    "MegaModel",
		    "MegaPreTrainedModel",
		]

if TYPE_CHECKING:
		from .configuration_mega import MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP, MegaConfig, MegaOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mega import (
				    MEGA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    MegaForCausalLM,
				    MegaForMaskedLM,
				    MegaForMultipleChoice,
				    MegaForQuestionAnswering,
				    MegaForSequenceClassification,
				    MegaForTokenClassification,
				    MegaModel,
				    MegaPreTrainedModel,
				)

else:
		import sys

		__lowerCamelCase     :							int  							=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



