




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__			:       str         =							logging.get_logger(__name__)

lowerCamelCase__			:       Optional[Any]         =							{
    '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 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 lowercase_       =   "detr"
 lowercase_       =   ["past_key_values"]
 lowercase_       =   {
     "hidden_size": "d_model",
     "num_attention_heads": "encoder_attention_heads",
 }



 def __init__(							self  :		Optional[Any]    ,    _lowerCAmelCase  :		Optional[Any]=True    ,    _lowerCAmelCase  :		List[Any]=None    ,    _lowerCAmelCase  :		str=3    ,    _lowerCAmelCase  :		Optional[Any]=100    ,    _lowerCAmelCase  :		Dict=6    ,    _lowerCAmelCase  :		str=2_048    ,    _lowerCAmelCase  :		Any=8    ,    _lowerCAmelCase  :		Optional[int]=6    ,    _lowerCAmelCase  :		Union[str, Any]=2_048    ,    _lowerCAmelCase  :		Union[str, Any]=8    ,    _lowerCAmelCase  :		List[Any]=0.0    ,    _lowerCAmelCase  :		Tuple=0.0    ,    _lowerCAmelCase  :		List[Any]=True    ,    _lowerCAmelCase  :		Tuple="relu"    ,    _lowerCAmelCase  :		Any=256    ,    _lowerCAmelCase  :		Optional[Any]=0.1    ,    _lowerCAmelCase  :		Dict=0.0    ,    _lowerCAmelCase  :		Dict=0.0    ,    _lowerCAmelCase  :		Tuple=0.02    ,    _lowerCAmelCase  :		Optional[Any]=1.0    ,    _lowerCAmelCase  :		Optional[Any]=False    ,    _lowerCAmelCase  :		Optional[int]="sine"    ,    _lowerCAmelCase  :		Optional[int]="resnet50"    ,    _lowerCAmelCase  :		Any=True    ,    _lowerCAmelCase  :		Any=False    ,    _lowerCAmelCase  :		Optional[int]=1    ,    _lowerCAmelCase  :		List[str]=5    ,    _lowerCAmelCase  :		Dict=2    ,    _lowerCAmelCase  :		Optional[Any]=1    ,    _lowerCAmelCase  :		Tuple=1    ,    _lowerCAmelCase  :		Dict=5    ,    _lowerCAmelCase  :		List[Any]=2    ,    _lowerCAmelCase  :		Any=0.1    ,    **_lowerCAmelCase  :		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.'						)
                   SCREAMING_SNAKE_CASE_     						=      CONFIG_MAPPING['resnet'](out_features=['stage4']						)
             elif isinstance(_lowerCAmelCase    ,    _lowerCAmelCase						):
                   SCREAMING_SNAKE_CASE_     						=      backbone_config.get('model_type'						)
                   SCREAMING_SNAKE_CASE_     						=      CONFIG_MAPPING[backbone_model_type]
                   SCREAMING_SNAKE_CASE_     						=      config_class.from_dict(_lowerCAmelCase						)
             # set timm attributes to None
             SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_     						=      None, None, None

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



 @property
 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       return self.encoder_attention_heads



 @property
 def 				lowerCAmelCase_  (							self  :		int						):
       return self.d_model



 @classmethod
 def 				lowerCAmelCase_  (							cls  :		Tuple    ,    _lowerCAmelCase  :		PretrainedConfig    ,    **_lowerCAmelCase  :		Tuple						):
       return cls(backbone_config=_lowerCAmelCase    ,    **_lowerCAmelCase						)




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





class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 lowercase_       =   version.parse("1.11" )



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



 @property
 def 				lowerCAmelCase_  (							self  :		Dict						):
       return 1E-5




 @property
 def 				lowerCAmelCase_  (							self  :		Optional[int]						):
       return 12





from pathlib import PurePosixPath
from typing import Optional

import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo

from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url





class 	lowerCamelCase_							(				_SCREAMING_SNAKE_CASE ):


 '''simple docstring'''







 lowercase_       =   ""
 lowercase_       =   "hf-legacy"  # "hf://"" is reserved for hffs



 def __init__(							self  :		Optional[int]    ,    _lowerCAmelCase  :		Optional[DatasetInfo] = None    ,    _lowerCAmelCase  :		Optional[str] = None    ,    **_lowerCAmelCase  :		int    ,    ):
       super().__init__(self    ,    **_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      repo_info
       SCREAMING_SNAKE_CASE_     						=      token
       SCREAMING_SNAKE_CASE_     						=      None



 def 				lowerCAmelCase_  (							self  :		Tuple						):
       if self.dir_cache is None:
             SCREAMING_SNAKE_CASE_     						=      {}
             for hf_file in self.repo_info.siblings:
                   # TODO(QL): add sizes
                   SCREAMING_SNAKE_CASE_     						=      {
                       'name': hf_file.rfilename,
                       'size': None,
                       'type': 'file',
                   }
                   self.dir_cache.update(
                       {
                           str(_lowerCAmelCase						): {'name': str(_lowerCAmelCase						), 'size': None, 'type': 'directory'}
                           for d in list(PurePosixPath(hf_file.rfilename						).parents						)[:-1]
                       }						)



 def 				lowerCAmelCase_  (							self  :		Optional[int]    ,    _lowerCAmelCase  :		str    ,    _lowerCAmelCase  :		str = "rb"    ,    **_lowerCAmelCase  :		Optional[Any]    ,    ):
       if not isinstance(self.repo_info    ,    _lowerCAmelCase						):
             raise NotImplementedError(F"Open is only implemented for dataset repositories, but got {self.repo_info}"						)
       SCREAMING_SNAKE_CASE_     						=      hf_hub_url(self.repo_info.id    ,    _lowerCAmelCase    ,    revision=self.repo_info.sha						)
       return fsspec.open(
           _lowerCAmelCase    ,    mode=_lowerCAmelCase    ,    headers=get_authentication_headers_for_url(_lowerCAmelCase    ,    use_auth_token=self.token						)    ,    client_kwargs={'trust_env': True}    ,    ).open()



 def 				lowerCAmelCase_  (							self  :		List[Any]    ,    _lowerCAmelCase  :		Any    ,    **_lowerCAmelCase  :		Dict						):
       self._get_dirs()
       SCREAMING_SNAKE_CASE_     						=      self._strip_protocol(_lowerCAmelCase						)
       if path in self.dir_cache:
             return self.dir_cache[path]
       else:
             raise FileNotFoundError(_lowerCAmelCase						)




 def 				lowerCAmelCase_  (							self  :		Optional[Any]    ,    _lowerCAmelCase  :		Any    ,    _lowerCAmelCase  :		Any=False    ,    **_lowerCAmelCase  :		str						):
       self._get_dirs()
       SCREAMING_SNAKE_CASE_     						=      PurePosixPath(path.strip('/'						)						)
       SCREAMING_SNAKE_CASE_     						=      {}
       for p, f in self.dir_cache.items():
             SCREAMING_SNAKE_CASE_     						=      PurePosixPath(p.strip('/'						)						)
             SCREAMING_SNAKE_CASE_     						=      p.parent
             if root == path:
                   SCREAMING_SNAKE_CASE_     						=      f
       SCREAMING_SNAKE_CASE_     						=      list(paths.values()						)
       if detail:
             return out
       else:
             return sorted(f['name'] for f in out						)