





'''simple docstring'''


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

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






class       UpperCamelCase__  (		__lowerCAmelCase     ):
	lowerCAmelCase__					:			Dict								=						"conditional_detr"
	lowerCAmelCase__					:			List[str]								=						["past_key_values"]
	lowerCAmelCase__					:			Any								=						{
	    "hidden_size": "d_model",
	    "num_attention_heads": "encoder_attention_heads",
	}







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




				'''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."		)
										a__     = CONFIG_MAPPING["resnet"](out_features=["stage4"]		)
							elif isinstance(lowerCamelCase , lowerCamelCase		):
										a__     = backbone_config.get("model_type"		)
										a__     = CONFIG_MAPPING[backbone_model_type]
										a__     = config_class.from_dict(lowerCamelCase		)

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







	@property
	def 						__a   (				self			:   Union[str, Any]		):




				'''simple docstring'''
				return self.encoder_attention_heads







	@property
	def 						__a   (				self			:   str		):




				'''simple docstring'''
				return self.d_model







	def 						__a   (				self			:   int		):




				'''simple docstring'''
				a__     = copy.deepcopy(self.__dict__		)
				if self.backbone_config is not None:
							a__     = self.backbone_config.to_dict()
				a__     = self.__class__.model_type
				return output






class       UpperCamelCase__  (		__lowerCAmelCase     ):
	lowerCAmelCase__					:			str								=						version.parse("1.11"     )







	@property
	def 						__a   (				self			:   List[Any]		):




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







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




				'''simple docstring'''
				return 1e-5







	@property
	def 						__a   (				self			:   List[str]		):




				'''simple docstring'''
				return 1_2










'''simple docstring'''


import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")







def    _lowerCamelCase  (__lowerCamelCase  :     List[str]     )   ->    List[str]:
			a__     = test_file.split(os.path.sep     )
			if components[0:2] != ["tests", "models"]:
						raise ValueError(
						    "`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got "
						    f'''{test_file} instead.'''     )
			a__     = components[-1]
			if not test_fn.endswith("py"     ):
						raise ValueError(f'''`test_file` should be a python file. Got {test_fn} instead.'''     )
			if not test_fn.startswith("test_modeling_"     ):
						raise ValueError(
						    f'''`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead.'''     )

			a__     = components[:-1] + [test_fn.replace(".py"					,  ""     )]
			a__     = ".".join(__lowerCamelCase     )

			return test_module_path







def    _lowerCamelCase  (__lowerCamelCase  :     Union[str, Any]     )   ->    Optional[Any]:
			a__     = get_module_path(__lowerCamelCase     )
			a__     = importlib.import_module(__lowerCamelCase     )

			return test_module







def    _lowerCamelCase  (__lowerCamelCase  :     Optional[int]     )   ->    Union[str, Any]:
			a__     = []
			a__     = get_test_module(__lowerCamelCase     )
			for attr in dir(__lowerCamelCase     ):
						if attr.endswith("ModelTester"     ):
									tester_classes.append(getattr(__lowerCamelCase					,  __lowerCamelCase     )     )

    # sort with class names
			return sorted(__lowerCamelCase					,  key=lambda __lowerCamelCase     : x.__name__     )







def    _lowerCamelCase  (__lowerCamelCase  :     Tuple     )   ->    Tuple:
			a__     = []
			a__     = get_test_module(__lowerCamelCase     )
			for attr in dir(__lowerCamelCase     ):
						a__     = getattr(__lowerCamelCase					,  __lowerCamelCase     )
						# (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
						# `all_model_classes` is not empty (which also excludes other special classes).
						a__     = getattr(__lowerCamelCase					,  "all_model_classes"					,  []     )
						if len(__lowerCamelCase     ) > 0:
									test_classes.append(__lowerCamelCase     )

    # sort with class names
			return sorted(__lowerCamelCase					,  key=lambda __lowerCamelCase     : x.__name__     )







def    _lowerCamelCase  (__lowerCamelCase  :     List[Any]     )   ->    List[Any]:
			a__     = get_test_classes(__lowerCamelCase     )
			a__     = set()
			for test_class in test_classes:
						model_classes.update(test_class.all_model_classes     )

			# sort with class names
			return sorted(__lowerCamelCase					,  key=lambda __lowerCamelCase     : x.__name__     )







def    _lowerCamelCase  (__lowerCamelCase  :     str     )   ->    Dict:
			a__     = test_class()
			if hasattr(__lowerCamelCase					,  "setUp"     ):
						test.setUp()

			a__     = None
			if hasattr(__lowerCamelCase					,  "model_tester"     ):
						# `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
						if test.model_tester is not None:
									a__     = test.model_tester.__class__

			return model_tester







def    _lowerCamelCase  (__lowerCamelCase  :     Dict					,  __lowerCamelCase  :     Optional[int]     )   ->    List[Any]:
			a__     = get_test_classes(__lowerCamelCase     )

			a__     = []
			for test_class in test_classes:
						if model_class in test_class.all_model_classes:
									target_test_classes.append(__lowerCamelCase     )

    # sort with class names
			return sorted(__lowerCamelCase					,  key=lambda __lowerCamelCase     : x.__name__     )







def    _lowerCamelCase  (__lowerCamelCase  :     Any					,  __lowerCamelCase  :     Tuple     )   ->    Dict:
			a__     = get_test_classes_for_model(__lowerCamelCase					,  __lowerCamelCase     )

			a__     = []
			for test_class in test_classes:
						a__     = get_model_tester_from_test_class(__lowerCamelCase     )
						if tester_class is not None:
									tester_classes.append(__lowerCamelCase     )

    # sort with class names
			return sorted(__lowerCamelCase					,  key=lambda __lowerCamelCase     : x.__name__     )







def    _lowerCamelCase  (__lowerCamelCase  :     List[str]     )   ->    int:
			a__     = get_test_classes(__lowerCamelCase     )
			a__     = {test_class: get_model_tester_from_test_class(__lowerCamelCase     ) for test_class in test_classes}
			return test_tester_mapping







def    _lowerCamelCase  (__lowerCamelCase  :     Any     )   ->    List[Any]:
			a__     = get_model_classes(__lowerCamelCase     )
			a__     = {
			    model_class: get_test_classes_for_model(__lowerCamelCase					,  __lowerCamelCase     ) for model_class in model_classes
			}
			return model_test_mapping







def    _lowerCamelCase  (__lowerCamelCase  :     Tuple     )   ->    Tuple:
			a__     = get_model_classes(__lowerCamelCase     )
			a__     = {
			    model_class: get_tester_classes_for_model(__lowerCamelCase					,  __lowerCamelCase     ) for model_class in model_classes
			}
			return model_to_tester_mapping







def    _lowerCamelCase  (__lowerCamelCase  :     str     )   ->    Dict:
			if isinstance(__lowerCamelCase					,  __lowerCamelCase     ):
						return o
			elif isinstance(__lowerCamelCase					,  __lowerCamelCase     ):
						return o.__name__
			elif isinstance(__lowerCamelCase					,  (list, tuple)     ):
						return [to_json(__lowerCamelCase     ) for x in o]
			elif isinstance(__lowerCamelCase					,  __lowerCamelCase     ):
						return {to_json(__lowerCamelCase     ): to_json(__lowerCamelCase     ) for k, v in o.items()}
			else:
						return o



