



'''simple docstring'''



import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


lowerCAmelCase_     :       Dict								=						logging.get_logger(__name__)

lowerCAmelCase_     :       List[Any]								=						{
    'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
class 	lowerCamelCase_							(					snake_case_			):
						_lowerCAmelCase     :   Optional[Any]	     =				'deta'
						_lowerCAmelCase     :   List[Any]	     =				{
						    'hidden_size': 'd_model',
						    'num_attention_heads': 'encoder_attention_heads',
						}







						def __init__(  self   :      Optional[Any]				,    lowerCAmelCase__   :      List[str]=None				,    lowerCAmelCase__   :      Optional[Any]=9_00				,    lowerCAmelCase__   :      Dict=20_48				,    lowerCAmelCase__   :      Union[str, Any]=6				,    lowerCAmelCase__   :      int=20_48				,    lowerCAmelCase__   :      Union[str, Any]=8				,    lowerCAmelCase__   :      int=6				,    lowerCAmelCase__   :      Optional[Any]=10_24				,    lowerCAmelCase__   :      Optional[Any]=8				,    lowerCAmelCase__   :      Union[str, Any]=0.0				,    lowerCAmelCase__   :      int=True				,    lowerCAmelCase__   :      Dict="relu"				,    lowerCAmelCase__   :      int=2_56				,    lowerCAmelCase__   :      Optional[int]=0.1				,    lowerCAmelCase__   :      Dict=0.0				,    lowerCAmelCase__   :      Tuple=0.0				,    lowerCAmelCase__   :      int=0.02				,    lowerCAmelCase__   :      List[Any]=1.0				,    lowerCAmelCase__   :      Dict=True				,    lowerCAmelCase__   :      Tuple=False				,    lowerCAmelCase__   :      Union[str, Any]="sine"				,    lowerCAmelCase__   :      Any=5				,    lowerCAmelCase__   :      Union[str, Any]=4				,    lowerCAmelCase__   :      Optional[Any]=4				,    lowerCAmelCase__   :      Union[str, Any]=True				,    lowerCAmelCase__   :      Optional[int]=3_00				,    lowerCAmelCase__   :      str=True				,    lowerCAmelCase__   :      Tuple=True				,    lowerCAmelCase__   :      List[Any]=1				,    lowerCAmelCase__   :      List[Any]=5				,    lowerCAmelCase__   :      List[str]=2				,    lowerCAmelCase__   :      Dict=1				,    lowerCAmelCase__   :      Tuple=1				,    lowerCAmelCase__   :      str=5				,    lowerCAmelCase__   :      List[Any]=2				,    lowerCAmelCase__   :      str=0.1				,    lowerCAmelCase__   :      int=0.25				,    **lowerCAmelCase__   :      str				,    ):

													"""simple docstring"""
													if backbone_config is None:
																				logger.info('''`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'''				)
																				SCREAMING_SNAKE_CASE					:      str     					=			CONFIG_MAPPING['''resnet'''](out_features=['''stage2''', '''stage3''', '''stage4''']				)
													else:
																				if isinstance(lowerCAmelCase__				,    lowerCAmelCase__				):
																											SCREAMING_SNAKE_CASE					:      Any     					=			backbone_config.pop('''model_type'''				)
																											SCREAMING_SNAKE_CASE					:      List[str]     					=			CONFIG_MAPPING[backbone_model_type]
																											SCREAMING_SNAKE_CASE					:      Any     					=			config_class.from_dict(lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Tuple     					=			backbone_config
													SCREAMING_SNAKE_CASE					:      List[str]     					=			num_queries
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			max_position_embeddings
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			d_model
													SCREAMING_SNAKE_CASE					:      Tuple     					=			encoder_ffn_dim
													SCREAMING_SNAKE_CASE					:      Any     					=			encoder_layers
													SCREAMING_SNAKE_CASE					:      Any     					=			encoder_attention_heads
													SCREAMING_SNAKE_CASE					:      List[str]     					=			decoder_ffn_dim
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			decoder_layers
													SCREAMING_SNAKE_CASE					:      List[str]     					=			decoder_attention_heads
													SCREAMING_SNAKE_CASE					:      Any     					=			dropout
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			attention_dropout
													SCREAMING_SNAKE_CASE					:      Dict     					=			activation_dropout
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			activation_function
													SCREAMING_SNAKE_CASE					:      Tuple     					=			init_std
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			init_xavier_std
													SCREAMING_SNAKE_CASE					:      List[str]     					=			encoder_layerdrop
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			auxiliary_loss
													SCREAMING_SNAKE_CASE					:      str     					=			position_embedding_type
													# deformable attributes
													SCREAMING_SNAKE_CASE					:      Dict     					=			num_feature_levels
													SCREAMING_SNAKE_CASE					:      Dict     					=			encoder_n_points
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			decoder_n_points
													SCREAMING_SNAKE_CASE					:      Tuple     					=			two_stage
													SCREAMING_SNAKE_CASE					:      Tuple     					=			two_stage_num_proposals
													SCREAMING_SNAKE_CASE					:      int     					=			with_box_refine
													SCREAMING_SNAKE_CASE					:      Tuple     					=			assign_first_stage
													if two_stage is True and with_box_refine is False:
																				raise ValueError('''If two_stage is True, with_box_refine must be True.'''				)
													# Hungarian matcher
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			class_cost
													SCREAMING_SNAKE_CASE					:      List[str]     					=			bbox_cost
													SCREAMING_SNAKE_CASE					:      Tuple     					=			giou_cost
													# Loss coefficients
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			mask_loss_coefficient
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			dice_loss_coefficient
													SCREAMING_SNAKE_CASE					:      List[str]     					=			bbox_loss_coefficient
													SCREAMING_SNAKE_CASE					:      List[str]     					=			giou_loss_coefficient
													SCREAMING_SNAKE_CASE					:      Any     					=			eos_coefficient
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			focal_alpha
													super().__init__(is_encoder_decoder=lowerCAmelCase__				,    **lowerCAmelCase__				)







						@property
						def 					__lowercase    (  self   :      Any				):

													"""simple docstring"""
													return self.encoder_attention_heads







						@property
						def 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													return self.d_model







						def 					__lowercase    (  self   :      Optional[int]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			copy.deepcopy(self.__dict__				)
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			self.backbone_config.to_dict()
													SCREAMING_SNAKE_CASE					:      str     					=			self.__class__.model_type
													return output









'''simple docstring'''



import string
from math import logaa
def 					UpperCAmelCase   (						A  :				str					,		A  :				str				):
							SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			document.translate(
							    str.maketrans(''''''					,		''''''					,		string.punctuation				)				).replace('''\n'''					,		''''''				)
							SCREAMING_SNAKE_CASE					:      Tuple     					=			document_without_punctuation.split(''' '''				)  # word tokenization
							return len([word for word in tokenize_document if word.lower() == term.lower()]				)
def 					UpperCAmelCase   (						A  :				str					,		A  :				str				):
							SCREAMING_SNAKE_CASE					:      int     					=			corpus.lower().translate(
							    str.maketrans(''''''					,		''''''					,		string.punctuation				)				)  # strip all punctuation and replace it with ''
							SCREAMING_SNAKE_CASE					:      Any     					=			corpus_without_punctuation.split('''\n'''				)
							SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			term.lower()
							return (len([doc for doc in docs if term in doc]				), len(A				))
def 					UpperCAmelCase   (						A  :				int					,		A  :				int					,		A  :				str=False				):
							if smoothing:
														if n == 0:
																					raise ValueError('''log10(0) is undefined.'''				)
														return round(1 + logaa(n / (1 + df)				)					,		3				)

							if df == 0:
														raise ZeroDivisionError('''df must be > 0'''				)
							elif n == 0:
														raise ValueError('''log10(0) is undefined.'''				)
							return round(logaa(n / df				)					,		3				)






def 					UpperCAmelCase   (						A  :				int					,		A  :				int				):
							return round(tf * idf					,		3				)




