



"""simple docstring"""





import copy
from collections import OrderedDict
from typing import Dict, 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  			=		{
    """facebook/detr-resnet-50""": """https://huggingface.co/facebook/detr-resnet-50/resolve/main/config.json""",
    # See all DETR models at https://huggingface.co/models?filter=detr
}
class  lowercase__  (       SCREAMING_SNAKE_CASE ):







       '''simple docstring'''


       UpperCamelCase		=	'''detr'''
       UpperCamelCase		=	['''past_key_values''']
       UpperCamelCase		=	{
           '''hidden_size''': '''d_model''',
           '''num_attention_heads''': '''encoder_attention_heads''',
       }



       def __init__(				self     :    int						,							_UpperCAmelCase     :    int=True						,							_UpperCAmelCase     :    Tuple=None						,							_UpperCAmelCase     :    Any=3						,							_UpperCAmelCase     :    Optional[int]=100						,							_UpperCAmelCase     :    Tuple=6						,							_UpperCAmelCase     :    Dict=2048						,							_UpperCAmelCase     :    Optional[int]=8						,							_UpperCAmelCase     :    Optional[Any]=6						,							_UpperCAmelCase     :    int=2048						,							_UpperCAmelCase     :    Union[str, Any]=8						,							_UpperCAmelCase     :    Dict=0.0						,							_UpperCAmelCase     :    Dict=0.0						,							_UpperCAmelCase     :    Optional[Any]=True						,							_UpperCAmelCase     :    Optional[Any]="relu"						,							_UpperCAmelCase     :    List[str]=256						,							_UpperCAmelCase     :    Any=0.1						,							_UpperCAmelCase     :    int=0.0						,							_UpperCAmelCase     :    Optional[int]=0.0						,							_UpperCAmelCase     :    Optional[int]=0.02						,							_UpperCAmelCase     :    Optional[int]=1.0						,							_UpperCAmelCase     :    int=False						,							_UpperCAmelCase     :    Any="sine"						,							_UpperCAmelCase     :    Union[str, Any]="resnet50"						,							_UpperCAmelCase     :    Union[str, Any]=True						,							_UpperCAmelCase     :    int=False						,							_UpperCAmelCase     :    List[str]=1						,							_UpperCAmelCase     :    Optional[Any]=5						,							_UpperCAmelCase     :    Any=2						,							_UpperCAmelCase     :    Any=1						,							_UpperCAmelCase     :    List[str]=1						,							_UpperCAmelCase     :    Optional[Any]=5						,							_UpperCAmelCase     :    Optional[int]=2						,							_UpperCAmelCase     :    List[str]=0.1						,							**_UpperCAmelCase     :    Any						,							)					->		Union[str, Any]:


             '''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."       )
                         UpperCAmelCase_     					=				CONFIG_MAPPING["resnet"](out_features=["stage4"]       )
                   elif isinstance(_UpperCAmelCase						,							_UpperCAmelCase       ):
                         UpperCAmelCase_     					=				backbone_config.get("model_type"       )
                         UpperCAmelCase_     					=				CONFIG_MAPPING[backbone_model_type]
                         UpperCAmelCase_     					=				config_class.from_dict(_UpperCAmelCase       )
                   # set timm attributes to None
                   UpperCAmelCase_					,       UpperCAmelCase_					,       UpperCAmelCase_     					=				None, None, None

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



       @property
       def 	lowercase__							(				self     :    List[Any]       )					->		int:


             '''simple docstring'''




             return self.encoder_attention_heads



       @property
       def 	lowercase__							(				self     :    List[Any]       )					->		int:


             '''simple docstring'''




             return self.d_model



       @classmethod
       def 	lowercase__							(				cls     :    Dict						,							_UpperCAmelCase     :    PretrainedConfig						,							**_UpperCAmelCase     :    Tuple       )					->		Any:


             '''simple docstring'''




             return cls(backbone_config=_UpperCAmelCase						,							**_UpperCAmelCase       )







       def 	lowercase__							(				self     :    Optional[int]       )					->		Dict[str, any]:


             '''simple docstring'''




             UpperCAmelCase_     					=				copy.deepcopy(self.__dict__       )
             if output["backbone_config"] is not None:
                   UpperCAmelCase_     					=				self.backbone_config.to_dict()
             UpperCAmelCase_     					=				self.__class__.model_type
             return output



class  lowercase__  (       SCREAMING_SNAKE_CASE ):







       '''simple docstring'''


       UpperCamelCase		=	version.parse('''1.11''' )



       @property
       def 	lowercase__							(				self     :    str       )					->		Mapping[str, Mapping[int, str]]:


             '''simple docstring'''




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



       @property
       def 	lowercase__							(				self     :    List[Any]       )					->		float:


             '''simple docstring'''




             return 1e-5







       @property
       def 	lowercase__							(				self     :    List[str]       )					->		int:


             '''simple docstring'''




             return 12








"""simple docstring"""



from typing import TYPE_CHECKING

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


__snake_case       =       {
    """configuration_poolformer""": [
        """POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """PoolFormerConfig""",
        """PoolFormerOnnxConfig""",
    ]
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __snake_case       =       ["""PoolFormerFeatureExtractor"""]
  __snake_case       =       ["""PoolFormerImageProcessor"""]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __snake_case       =       [
      """POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """PoolFormerForImageClassification""",
      """PoolFormerModel""",
      """PoolFormerPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_poolformer import (
      POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      PoolFormerConfig,
      PoolFormerOnnxConfig,
  )

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_poolformer import PoolFormerFeatureExtractor
    from .image_processing_poolformer import PoolFormerImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_poolformer import (
        POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        PoolFormerForImageClassification,
        PoolFormerModel,
        PoolFormerPreTrainedModel,
    )


else:
  import sys

  __snake_case       =       _LazyModule(__name__, globals()["""__file__"""], _import_structure)





