

"""simple docstring"""





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


__UpperCamelCase  :      int							      =		logging.get_logger(__name__)

__UpperCamelCase  :      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 				SCREAMING_SNAKE_CASE					(		a_       ):






					"""simple docstring"""



					lowercase__				 =       "cvt"







					def __init__(       self			:				Tuple   ,lowercase_			:				Union[str, Any]=3   ,lowercase_			:				Dict=[7, 3, 3]   ,lowercase_			:				Union[str, Any]=[4, 2, 2]   ,lowercase_			:				Optional[int]=[2, 1, 1]   ,lowercase_			:				List[str]=[6_4, 1_9_2, 3_8_4]   ,lowercase_			:				Tuple=[1, 3, 6]   ,lowercase_			:				Any=[1, 2, 1_0]   ,lowercase_			:				Any=[4.0, 4.0, 4.0]   ,lowercase_			:				str=[0.0, 0.0, 0.0]   ,lowercase_			:				str=[0.0, 0.0, 0.0]   ,lowercase_			:				int=[0.0, 0.0, 0.1]   ,lowercase_			:				str=[True, True, True]   ,lowercase_			:				Optional[Any]=[False, False, True]   ,lowercase_			:				Any=["dw_bn", "dw_bn", "dw_bn"]   ,lowercase_			:				Optional[int]=[3, 3, 3]   ,lowercase_			:				int=[1, 1, 1]   ,lowercase_			:				Tuple=[2, 2, 2]   ,lowercase_			:				Dict=[1, 1, 1]   ,lowercase_			:				List[Any]=[1, 1, 1]   ,lowercase_			:				List[Any]=0.02   ,lowercase_			:				Optional[Any]=1E-12   ,**lowercase_			:				str   ,):
						super().__init__(**lowercase_		)
						lowerCAmelCase__	:						List[str]  				=	num_channels
						lowerCAmelCase__	:						Union[str, Any]  				=	patch_sizes
						lowerCAmelCase__	:						int  				=	patch_stride
						lowerCAmelCase__	:						Union[str, Any]  				=	patch_padding
						lowerCAmelCase__	:						Optional[int]  				=	embed_dim
						lowerCAmelCase__	:						List[str]  				=	num_heads
						lowerCAmelCase__	:						List[str]  				=	depth
						lowerCAmelCase__	:						List[Any]  				=	mlp_ratio
						lowerCAmelCase__	:						List[Any]  				=	attention_drop_rate
						lowerCAmelCase__	:						str  				=	drop_rate
						lowerCAmelCase__	:						Union[str, Any]  				=	drop_path_rate
						lowerCAmelCase__	:						Optional[Any]  				=	qkv_bias
						lowerCAmelCase__	:						List[str]  				=	cls_token
						lowerCAmelCase__	:						str  				=	qkv_projection_method
						lowerCAmelCase__	:						List[str]  				=	kernel_qkv
						lowerCAmelCase__	:						Optional[Any]  				=	padding_kv
						lowerCAmelCase__	:						Any  				=	stride_kv
						lowerCAmelCase__	:						Dict  				=	padding_q
						lowerCAmelCase__	:						str  				=	stride_q
						lowerCAmelCase__	:						List[str]  				=	initializer_range
						lowerCAmelCase__	:						Tuple  				=	layer_norm_eps





"""simple docstring"""






from typing import TYPE_CHECKING

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


lowerCAmelCase__  :  str						     =	{
    'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'],
    'feature_extraction_mctct': ['MCTCTFeatureExtractor'],
    'processing_mctct': ['MCTCTProcessor'],
}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase__  :  Any						     =	[
						    'MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'MCTCTForCTC',
						    'MCTCTModel',
						    'MCTCTPreTrainedModel',
						]


if TYPE_CHECKING:
						from .configuration_mctct import MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP, MCTCTConfig
						from .feature_extraction_mctct import MCTCTFeatureExtractor
						from .processing_mctct import MCTCTProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_mctct import MCTCT_PRETRAINED_MODEL_ARCHIVE_LIST, MCTCTForCTC, MCTCTModel, MCTCTPreTrainedModel

else:
						import sys

						lowerCAmelCase__  :  Any						     =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



