'''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


a=  logging.get_logger(__name__)

a=  {
    '''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		(						_lowerCamelCase						):







     """simple docstring"""






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







     def __init__(		self     ,			_lowerCamelCase=True     ,			_lowerCamelCase=None     ,			_lowerCamelCase=3     ,			_lowerCamelCase=1_0_0     ,			_lowerCamelCase=6     ,			_lowerCamelCase=2_0_4_8     ,			_lowerCamelCase=8     ,			_lowerCamelCase=6     ,			_lowerCamelCase=2_0_4_8     ,			_lowerCamelCase=8     ,			_lowerCamelCase=0.0     ,			_lowerCamelCase=0.0     ,			_lowerCamelCase=True     ,			_lowerCamelCase="relu"     ,			_lowerCamelCase=2_5_6     ,			_lowerCamelCase=0.1     ,			_lowerCamelCase=0.0     ,			_lowerCamelCase=0.0     ,			_lowerCamelCase=0.0_2     ,			_lowerCamelCase=1.0     ,			_lowerCamelCase=False     ,			_lowerCamelCase="sine"     ,			_lowerCamelCase="resnet50"     ,			_lowerCamelCase=True     ,			_lowerCamelCase=False     ,			_lowerCamelCase=1     ,			_lowerCamelCase=5     ,			_lowerCamelCase=2     ,			_lowerCamelCase=1     ,			_lowerCamelCase=1     ,			_lowerCamelCase=5     ,			_lowerCamelCase=2     ,			_lowerCamelCase=0.1     ,			**_lowerCamelCase     ,			):
         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	:	Dict		    =  CONFIG_MAPPING['resnet'](out_features=['stage4']    )
             elif isinstance(_lowerCamelCase     ,			_lowerCamelCase    ):
                 __UpperCamelCase	:	Optional[int]		    =  backbone_config.get('model_type'    )
                 __UpperCamelCase	:	Any		    =  CONFIG_MAPPING[backbone_model_type]
                 __UpperCamelCase	:	int		    =  config_class.from_dict(_lowerCamelCase    )
             # set timm attributes to None
             __UpperCamelCase    ,					__UpperCamelCase    ,					__UpperCamelCase	:	Dict		    =  None, None, None

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







     @property
     def lowerCAmelCase     (		self    ):
         return self.encoder_attention_heads







     @property
     def lowerCAmelCase     (		self    ):
         return self.d_model







     @classmethod
     def lowerCAmelCase     (		cls     ,			_lowerCamelCase     ,			**_lowerCamelCase    ):
         return cls(backbone_config=_lowerCamelCase     ,			**_lowerCamelCase    )







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	List[str]		    =  copy.deepcopy(self.__dict__    )
         if output["backbone_config"] is not None:
             __UpperCamelCase	:	Optional[int]		    =  self.backbone_config.to_dict()
         __UpperCamelCase	:	List[Any]		    =  self.__class__.model_type
         return output






class 			__lowercase		(						_lowerCamelCase						):







     """simple docstring"""






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







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







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







     @property
     def lowerCAmelCase     (		self    ):
         return 1_2




'''simple docstring'''
from urllib.parse import quote

import pytest

from datasets.utils.hub import hf_hub_url







@pytest.mark.parametrize('repo_id'				,     ['canonical_dataset_name', 'org-name/dataset-name']			)
@pytest.mark.parametrize('path'				,     ['filename.csv', 'filename with blanks.csv']			)
@pytest.mark.parametrize('revision'				,     [None, 'v2']			)
def  _UpperCamelCase (     _a	:	Any				,     _a	:	int				,     _a	:	Dict			):




    """simple docstring"""



    __UpperCamelCase	:	List[Any]		    =  hf_hub_url(repo_id=_a				,     path=_a				,     revision=_a			)
    assert url == f"""https://huggingface.co/datasets/{repo_id}/resolve/{revision or 'main'}/{quote(_a			)}"""



