



'''simple docstring'''



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/table-transformer-detection""": (
        """https://huggingface.co/microsoft/table-transformer-detection/resolve/main/config.json"""
    ),
}





class _UpperCamelCase		(     A		):





				'''simple docstring'''





				lowerCAmelCase__					    =    """table-transformer"""
				lowerCAmelCase__					    =    ["""past_key_values"""]
				lowerCAmelCase__					    =    {
				    """hidden_size""": """d_model""",
				    """num_attention_heads""": """encoder_attention_heads""",
				}

				def __init__(							self  :  List[str]  ,       _lowerCAmelCase  :  Dict=True  ,       _lowerCAmelCase  :  Dict=None  ,       _lowerCAmelCase  :  Union[str, Any]=3  ,       _lowerCAmelCase  :  Any=1_0_0  ,       _lowerCAmelCase  :  Optional[Any]=6  ,       _lowerCAmelCase  :  Any=2_0_4_8  ,       _lowerCAmelCase  :  Dict=8  ,       _lowerCAmelCase  :  Optional[Any]=6  ,       _lowerCAmelCase  :  str=2_0_4_8  ,       _lowerCAmelCase  :  Any=8  ,       _lowerCAmelCase  :  List[Any]=0.0  ,       _lowerCAmelCase  :  Union[str, Any]=0.0  ,       _lowerCAmelCase  :  List[str]=True  ,       _lowerCAmelCase  :  List[str]="relu"  ,       _lowerCAmelCase  :  Union[str, Any]=2_5_6  ,       _lowerCAmelCase  :  Optional[int]=0.1  ,       _lowerCAmelCase  :  List[str]=0.0  ,       _lowerCAmelCase  :  str=0.0  ,       _lowerCAmelCase  :  Dict=0.02  ,       _lowerCAmelCase  :  Union[str, Any]=1.0  ,       _lowerCAmelCase  :  Dict=False  ,       _lowerCAmelCase  :  Optional[int]="sine"  ,       _lowerCAmelCase  :  Any="resnet50"  ,       _lowerCAmelCase  :  str=True  ,       _lowerCAmelCase  :  Any=False  ,       _lowerCAmelCase  :  str=1  ,       _lowerCAmelCase  :  Optional[int]=5  ,       _lowerCAmelCase  :  Any=2  ,       _lowerCAmelCase  :  str=1  ,       _lowerCAmelCase  :  Tuple=1  ,       _lowerCAmelCase  :  Tuple=5  ,       _lowerCAmelCase  :  List[Any]=2  ,       _lowerCAmelCase  :  Optional[Any]=0.1  ,       **_lowerCAmelCase  :  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.')
																									__lowercase       	=CONFIG_MAPPING['resnet'](out_features=['stage4'])
																		elif isinstance(_lowerCAmelCase  ,       _lowerCAmelCase):
																									__lowercase       	=backbone_config.get('model_type')
																									__lowercase       	=CONFIG_MAPPING[backbone_model_type]
																									__lowercase       	=config_class.from_dict(_lowerCAmelCase)
																		# set timm attributes to None
																		__lowercase	,				__lowercase	,				__lowercase       	=None, None, None

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

				@property
				def 				__lowerCamelCase     (							self  :  Tuple):







											'''simple docstring'''

											return self.encoder_attention_heads

				@property
				def 				__lowerCamelCase     (							self  :  Dict):







											'''simple docstring'''

											return self.d_model





class _UpperCamelCase		(     A		):





				'''simple docstring'''





				lowerCAmelCase__					    =    version.parse("""1.11"""		)

				@property
				def 				__lowerCamelCase     (							self  :  Tuple):







											'''simple docstring'''

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

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







											'''simple docstring'''

											return 1e-5

				@property
				def 				__lowerCamelCase     (							self  :  int):







											'''simple docstring'''

											return 1_2








'''simple docstring'''



import numpy as np





class _UpperCamelCase		:





				'''simple docstring'''





				def __init__(							self  :  Dict):







											'''simple docstring'''

											__lowercase       	=(0, 0)
											__lowercase       	=None
											__lowercase       	=0
											__lowercase       	=0
											__lowercase       	=0

				def __eq__(							self  :  List[str]  ,       _lowerCAmelCase  :  Optional[Any]):







											'''simple docstring'''

											return self.position == cell.position

				def 				__lowerCamelCase     (							self  :  Dict):







											'''simple docstring'''

											print(self.position)





class _UpperCamelCase		:





				'''simple docstring'''





				def __init__(							self  :  Any  ,       _lowerCAmelCase  :  List[str]=(5, 5)):







											'''simple docstring'''

											__lowercase       	=np.zeros(_lowerCAmelCase)
											__lowercase       	=world_size[0]
											__lowercase       	=world_size[1]

				def 				__lowerCamelCase     (							self  :  Optional[int]):







											'''simple docstring'''

											print(self.w)

				def 				__lowerCamelCase     (							self  :  int  ,       _lowerCAmelCase  :  List[str]):







											'''simple docstring'''

											__lowercase       	=[
											    (-1, -1),
											    (-1, 0),
											    (-1, 1),
											    (0, -1),
											    (0, 1),
											    (1, -1),
											    (1, 0),
											    (1, 1),
											]
											__lowercase       	=cell.position[0]
											__lowercase       	=cell.position[1]
											__lowercase       	=[]
											for n in neughbour_cord:
																		__lowercase       	=current_x + n[0]
																		__lowercase       	=current_y + n[1]
																		if 0 <= x < self.world_x_limit and 0 <= y < self.world_y_limit:
																									__lowercase       	=Cell()
																									__lowercase       	=(x, y)
																									__lowercase       	=cell
																									neighbours.append(_lowerCAmelCase)
											return neighbours



def   _A       (   _lowerCAmelCase  ,   _lowerCAmelCase  ,   _lowerCAmelCase					):



							"""simple docstring"""



							__lowercase       	=[]
							__lowercase       	=[]
							_open.append(_lowerCAmelCase					)

							while _open:
														__lowercase       	=np.argmin([n.f for n in _open]					)
														__lowercase       	=_open[min_f]
														_closed.append(_open.pop(_lowerCAmelCase					)					)
														if current == goal:
																					break
														for n in world.get_neigbours(_lowerCAmelCase					):
																					for c in _closed:
																												if c == n:
																																			continue
																					__lowercase       	=current.g + 1
																					__lowercase	,				__lowercase       	=n.position
																					__lowercase	,				__lowercase       	=goal.position
																					__lowercase       	=(ya - ya) ** 2 + (xa - xa) ** 2
																					__lowercase       	=n.h + n.g

																					for c in _open:
																												if c == n and c.f < n.f:
																																			continue
																					_open.append(_lowerCAmelCase					)
							__lowercase       	=[]
							while current.parent is not None:
														path.append(current.position					)
														__lowercase       	=current.parent
							path.append(current.position					)
							return path[::-1]


if __name__ == "__main__":
		lowerCamelCase	 =       Gridworld()
		# Start position and goal
		lowerCamelCase	 =       Cell()
		lowerCamelCase	 =       (0, 0)
		lowerCamelCase	 =       Cell()
		lowerCamelCase	 =       (4, 4)
		print(f"path from {start.position} to {goal.position}")
		lowerCamelCase	 =       astar(world, start, goal)
		#   Just for visual reasons.
		for i in s:
				lowerCamelCase	 =       1
		print(world.w)



