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


lowerCAmelCase_     =	logging.get_logger(__name__)

lowerCAmelCase_     =	{
    'microsoft/conditional-detr-resnet-50': (
        'https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json'
    ),
}




class  _snake_case		(    __snake_case ):







				"""simple docstring"""






				a			=						'conditional_detr'
				a			=						['past_key_values']
				a			=						{
				    'hidden_size': 'd_model',
				    'num_attention_heads': 'encoder_attention_heads',
				}





				def __init__(      self							:							Tuple      ,    _A							:							Optional[int]=True      ,    _A							:							str=None      ,    _A							:							str=3      ,    _A							:							Any=3_0_0      ,    _A							:							Optional[int]=6      ,    _A							:							str=2_0_4_8      ,    _A							:							Optional[int]=8      ,    _A							:							Optional[int]=6      ,    _A							:							Optional[Any]=2_0_4_8      ,    _A							:							Any=8      ,    _A							:							Optional[int]=0.0      ,    _A							:							int=0.0      ,    _A							:							Optional[int]=True      ,    _A							:							Optional[int]="relu"      ,    _A							:							str=2_5_6      ,    _A							:							int=0.1      ,    _A							:							Dict=0.0      ,    _A							:							int=0.0      ,    _A							:							Optional[int]=0.02      ,    _A							:							List[str]=1.0      ,    _A							:							List[Any]=False      ,    _A							:							str="sine"      ,    _A							:							Tuple="resnet50"      ,    _A							:							int=True      ,    _A							:							Optional[int]=False      ,    _A							:							List[str]=2      ,    _A							:							Dict=5      ,    _A							:							Union[str, Any]=2      ,    _A							:							Dict=1      ,    _A							:							Union[str, Any]=1      ,    _A							:							Dict=2      ,    _A							:							Union[str, Any]=5      ,    _A							:							List[Any]=2      ,    _A							:							Dict=0.25      ,    **_A							:							int      ,    ):



											"""simple docstring"""







											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.""")
																									_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    CONFIG_MAPPING['''resnet'''](out_features=["""stage4"""])
																		elif isinstance(UpperCAmelCase__      ,    UpperCAmelCase__):
																									_SCREAMING_SNAKE_CASE		:						Tuple			  =    backbone_config.get("""model_type""")
																									_SCREAMING_SNAKE_CASE		:						str			  =    CONFIG_MAPPING[backbone_model_type]
																									_SCREAMING_SNAKE_CASE		:						str			  =    config_class.from_dict(UpperCAmelCase__)

											_SCREAMING_SNAKE_CASE		:						Dict			  =    use_timm_backbone
											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    backbone_config
											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    num_channels
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    num_queries
											_SCREAMING_SNAKE_CASE		:						str			  =    d_model
											_SCREAMING_SNAKE_CASE		:						int			  =    encoder_ffn_dim
											_SCREAMING_SNAKE_CASE		:						str			  =    encoder_layers
											_SCREAMING_SNAKE_CASE		:						int			  =    encoder_attention_heads
											_SCREAMING_SNAKE_CASE		:						Dict			  =    decoder_ffn_dim
											_SCREAMING_SNAKE_CASE		:						int			  =    decoder_layers
											_SCREAMING_SNAKE_CASE		:						Any			  =    decoder_attention_heads
											_SCREAMING_SNAKE_CASE		:						Any			  =    dropout
											_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    attention_dropout
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    activation_dropout
											_SCREAMING_SNAKE_CASE		:						str			  =    activation_function
											_SCREAMING_SNAKE_CASE		:						Any			  =    init_std
											_SCREAMING_SNAKE_CASE		:						Any			  =    init_xavier_std
											_SCREAMING_SNAKE_CASE		:						Tuple			  =    encoder_layerdrop
											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    decoder_layerdrop
											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    encoder_layers
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    auxiliary_loss
											_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    position_embedding_type
											_SCREAMING_SNAKE_CASE		:						Any			  =    backbone
											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    use_pretrained_backbone
											_SCREAMING_SNAKE_CASE		:						int			  =    dilation
											# Hungarian matcher
											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    class_cost
											_SCREAMING_SNAKE_CASE		:						Any			  =    bbox_cost
											_SCREAMING_SNAKE_CASE		:						Dict			  =    giou_cost
											# Loss coefficients
											_SCREAMING_SNAKE_CASE		:						List[Any]			  =    mask_loss_coefficient
											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    dice_loss_coefficient
											_SCREAMING_SNAKE_CASE		:						Tuple			  =    cls_loss_coefficient
											_SCREAMING_SNAKE_CASE		:						Dict			  =    bbox_loss_coefficient
											_SCREAMING_SNAKE_CASE		:						int			  =    giou_loss_coefficient
											_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    focal_alpha
											super().__init__(is_encoder_decoder=UpperCAmelCase__      ,    **UpperCAmelCase__)





				@property
				def 		_lowerCAmelCase		(      self							:							Dict):



											"""simple docstring"""







											return self.encoder_attention_heads





				@property
				def 		_lowerCAmelCase		(      self							:							Optional[Any]):



											"""simple docstring"""







											return self.d_model





				def 		_lowerCAmelCase		(      self							:							int):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						str			  =    copy.deepcopy(self.__dict__)
											if self.backbone_config is not None:
																		_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    self.backbone_config.to_dict()
											_SCREAMING_SNAKE_CASE		:						List[str]			  =    self.__class__.model_type
											return output




class  _snake_case		(    __snake_case ):







				"""simple docstring"""






				a			=						version.parse("1.11" )





				@property
				def 		_lowerCAmelCase		(      self							:							Optional[int]):



											"""simple docstring"""







											return OrderedDict(
											    [
											        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
											        ("""pixel_mask""", {0: """batch"""}),
											    ])





				@property
				def 		_lowerCAmelCase		(      self							:							Dict):



											"""simple docstring"""







											return 1e-5





				@property
				def 		_lowerCAmelCase		(      self							:							Dict):



											"""simple docstring"""







											return 1_2



"""simple docstring"""





import argparse
from collections import defaultdict



def      lowerCamelCase_(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE  )->    int:
							_SCREAMING_SNAKE_CASE		:						str			  =    F"""{file}_{class_name}_{test_name}"""
							done_test[_id] += 1

							with open(__SCREAMING_SNAKE_CASE     ,	"""r"""  ) as f:
														_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    f.readlines()

							_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    F"""class {class_name}("""
							_SCREAMING_SNAKE_CASE		:						List[Any]			  =    F"""{4 * " "}def {test_name}("""
							_SCREAMING_SNAKE_CASE		:						Tuple			  =    F"""{8 * " "}{correct_line.split()[0]}"""
							_SCREAMING_SNAKE_CASE		:						List[Any]			  =    F"""{16 * " "}{correct_line.split()[0]}"""
							_SCREAMING_SNAKE_CASE		:						List[str]			  =    False
							_SCREAMING_SNAKE_CASE		:						Tuple			  =    False
							_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    False
							_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    False
							_SCREAMING_SNAKE_CASE		:						Any			  =    0
							_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    0

							_SCREAMING_SNAKE_CASE		:						Dict			  =    []
							for line in lines:
														if line.startswith(__SCREAMING_SNAKE_CASE  ):
																					_SCREAMING_SNAKE_CASE		:						Any			  =    True
														elif in_class and line.startswith(__SCREAMING_SNAKE_CASE  ):
																					_SCREAMING_SNAKE_CASE		:						str			  =    True
														elif in_class and in_func and (line.startswith(__SCREAMING_SNAKE_CASE  ) or line.startswith(__SCREAMING_SNAKE_CASE  )):
																					_SCREAMING_SNAKE_CASE		:						Dict			  =    len(line.split(correct_line.split()[0]  )[0]  )
																					count += 1

																					if count == done_test[_id]:
																												_SCREAMING_SNAKE_CASE		:						int			  =    True

														if in_class and in_func and in_line:
																					if ")" not in line:
																												continue
																					else:
																												_SCREAMING_SNAKE_CASE		:						Any			  =    True

														if in_class and in_func and in_line and insert_line:
																					new_lines.append(F"""{spaces * " "}{correct_line}"""  )
																					_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    False
														else:
																					new_lines.append(__SCREAMING_SNAKE_CASE  )

							with open(__SCREAMING_SNAKE_CASE     ,	"""w"""  ) as f:
														for line in new_lines:
																					f.write(__SCREAMING_SNAKE_CASE  )



def      lowerCamelCase_(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE=None  )->    Optional[Any]:
							if fail is not None:
														with open(__SCREAMING_SNAKE_CASE     ,	"""r"""  ) as f:
																					_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    {l.strip() for l in f.readlines()}
							else:
														_SCREAMING_SNAKE_CASE		:						str			  =    None

							with open(__SCREAMING_SNAKE_CASE     ,	"""r"""  ) as f:
														_SCREAMING_SNAKE_CASE		:						str			  =    f.readlines()

							_SCREAMING_SNAKE_CASE		:						str			  =    defaultdict(__SCREAMING_SNAKE_CASE  )
							for line in correct_lines:
														_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE  ,				_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    line.split(""";"""  )
														if test_failures is None or "::".join([file, class_name, test_name]  ) in test_failures:
																					overwrite_file(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE  )


if __name__ == "__main__":
			lowerCAmelCase_     =	argparse.ArgumentParser()
			parser.add_argument('''--correct_filename''', help='''filename of tests with expected result''')
			parser.add_argument('''--fail_filename''', help='''filename of test failures''', type=str, default=None)
			lowerCAmelCase_     =	parser.parse_args()

			main(args.correct_filename, args.fail_filename)


