import copy
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
from ..auto import CONFIG_MAPPING


lowercase__			:				int		=	logging.get_logger(__name__)

lowercase__			:				Optional[int]		=	{
    '''microsoft/conditional-detr-resnet-50''': (
        '''https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json'''
    ),
}




class    lowercase_  (  _UpperCamelCase						):



	"""simple docstring"""





	UpperCAmelCase_  :					Any   =				'conditional_detr'
	UpperCAmelCase_  :					List[str]   =				['past_key_values']
	UpperCAmelCase_  :					Optional[int]   =				{
	    'hidden_size': 'd_model',
	    'num_attention_heads': 'encoder_attention_heads',
	}


	def __init__(							self		,			__SCREAMING_SNAKE_CASE=True		,			__SCREAMING_SNAKE_CASE=None		,			__SCREAMING_SNAKE_CASE=3		,			__SCREAMING_SNAKE_CASE=300		,			__SCREAMING_SNAKE_CASE=6		,			__SCREAMING_SNAKE_CASE=2048		,			__SCREAMING_SNAKE_CASE=8		,			__SCREAMING_SNAKE_CASE=6		,			__SCREAMING_SNAKE_CASE=2048		,			__SCREAMING_SNAKE_CASE=8		,			__SCREAMING_SNAKE_CASE=0.0		,			__SCREAMING_SNAKE_CASE=0.0		,			__SCREAMING_SNAKE_CASE=True		,			__SCREAMING_SNAKE_CASE="relu"		,			__SCREAMING_SNAKE_CASE=256		,			__SCREAMING_SNAKE_CASE=0.1		,			__SCREAMING_SNAKE_CASE=0.0		,			__SCREAMING_SNAKE_CASE=0.0		,			__SCREAMING_SNAKE_CASE=0.0_2		,			__SCREAMING_SNAKE_CASE=1.0		,			__SCREAMING_SNAKE_CASE=False		,			__SCREAMING_SNAKE_CASE="sine"		,			__SCREAMING_SNAKE_CASE="resnet50"		,			__SCREAMING_SNAKE_CASE=True		,			__SCREAMING_SNAKE_CASE=False		,			__SCREAMING_SNAKE_CASE=2		,			__SCREAMING_SNAKE_CASE=5		,			__SCREAMING_SNAKE_CASE=2		,			__SCREAMING_SNAKE_CASE=1		,			__SCREAMING_SNAKE_CASE=1		,			__SCREAMING_SNAKE_CASE=2		,			__SCREAMING_SNAKE_CASE=5		,			__SCREAMING_SNAKE_CASE=2		,			__SCREAMING_SNAKE_CASE=0.2_5		,			**__SCREAMING_SNAKE_CASE		,			)						->Optional[int]:
								if backbone_config is not None and use_timm_backbone:
															raise ValueError('''You can\'t specify both `backbone_config` and `use_timm_backbone`.'''				)

								if not use_timm_backbone:
															if backbone_config is None:
																						logger.info('''`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'''				)
																						lowerCAmelCase			=		CONFIG_MAPPING['resnet'](out_features=['''stage4''']				)
															elif isinstance(_UpperCAmelCase		,			_UpperCAmelCase				):
																						lowerCAmelCase			=		backbone_config.get('''model_type'''				)
																						lowerCAmelCase			=		CONFIG_MAPPING[backbone_model_type]
																						lowerCAmelCase			=		config_class.from_dict(_UpperCAmelCase				)

								lowerCAmelCase			=		use_timm_backbone
								lowerCAmelCase			=		backbone_config
								lowerCAmelCase			=		num_channels
								lowerCAmelCase			=		num_queries
								lowerCAmelCase			=		d_model
								lowerCAmelCase			=		encoder_ffn_dim
								lowerCAmelCase			=		encoder_layers
								lowerCAmelCase			=		encoder_attention_heads
								lowerCAmelCase			=		decoder_ffn_dim
								lowerCAmelCase			=		decoder_layers
								lowerCAmelCase			=		decoder_attention_heads
								lowerCAmelCase			=		dropout
								lowerCAmelCase			=		attention_dropout
								lowerCAmelCase			=		activation_dropout
								lowerCAmelCase			=		activation_function
								lowerCAmelCase			=		init_std
								lowerCAmelCase			=		init_xavier_std
								lowerCAmelCase			=		encoder_layerdrop
								lowerCAmelCase			=		decoder_layerdrop
								lowerCAmelCase			=		encoder_layers
								lowerCAmelCase			=		auxiliary_loss
								lowerCAmelCase			=		position_embedding_type
								lowerCAmelCase			=		backbone
								lowerCAmelCase			=		use_pretrained_backbone
								lowerCAmelCase			=		dilation
								# Hungarian matcher
								lowerCAmelCase			=		class_cost
								lowerCAmelCase			=		bbox_cost
								lowerCAmelCase			=		giou_cost
								# Loss coefficients
								lowerCAmelCase			=		mask_loss_coefficient
								lowerCAmelCase			=		dice_loss_coefficient
								lowerCAmelCase			=		cls_loss_coefficient
								lowerCAmelCase			=		bbox_loss_coefficient
								lowerCAmelCase			=		giou_loss_coefficient
								lowerCAmelCase			=		focal_alpha
								super().__init__(is_encoder_decoder=_UpperCAmelCase		,			**_UpperCAmelCase				)


	@property
	def 			SCREAMING_SNAKE_CASE_				(							self				)						->List[str]:
								return self.encoder_attention_heads


	@property
	def 			SCREAMING_SNAKE_CASE_				(							self				)						->int:
								return self.d_model




	def 			SCREAMING_SNAKE_CASE_				(							self				)						->Any:
								lowerCAmelCase			=		copy.deepcopy(self.__dict__				)
								if self.backbone_config is not None:
															lowerCAmelCase			=		self.backbone_config.to_dict()
								lowerCAmelCase			=		self.__class__.model_type
								return output




class    lowercase_  (  _UpperCamelCase						):



	"""simple docstring"""





	UpperCAmelCase_  :					str   =				version.parse("""1.11"""						)


	@property
	def 			SCREAMING_SNAKE_CASE_				(							self				)						->Tuple:
								return OrderedDict(
								    [
								        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
								        ('''pixel_mask''', {0: '''batch'''}),
								    ]				)


	@property
	def 			SCREAMING_SNAKE_CASE_				(							self				)						->Union[str, Any]:
								return 1e-5




	@property
	def 			SCREAMING_SNAKE_CASE_				(							self				)						->Any:
								return 12








'''simple docstring'''

from typing import TYPE_CHECKING

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


__lowerCAmelCase									=   {'''configuration_swin''': ['''SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SwinConfig''', '''SwinOnnxConfig''']}


try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase									=   [
							    '''SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''SwinForImageClassification''',
							    '''SwinForMaskedImageModeling''',
							    '''SwinModel''',
							    '''SwinPreTrainedModel''',
							    '''SwinBackbone''',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase									=   [
							    '''TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''TFSwinForImageClassification''',
							    '''TFSwinForMaskedImageModeling''',
							    '''TFSwinModel''',
							    '''TFSwinPreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_swin import (
														    SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
														    SwinBackbone,
														    SwinForImageClassification,
														    SwinForMaskedImageModeling,
														    SwinModel,
														    SwinPreTrainedModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_swin import (
														    TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFSwinForImageClassification,
														    TFSwinForMaskedImageModeling,
														    TFSwinModel,
														    TFSwinPreTrainedModel,
														)

else:
							import sys

							__lowerCAmelCase									=   _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




