
'''simple docstring'''




from queue import Queue
from typing import TYPE_CHECKING, Optional


if TYPE_CHECKING:
      from ..models.auto import AutoTokenizer





class 					A							:





     def 							__lowerCAmelCase				(				self		,     SCREAMING_SNAKE_CASE      )					->							str:






         """simple docstring"""






         raise NotImplementedError()





     def 							__lowerCAmelCase				(				self      )					->							Dict:






         """simple docstring"""






         raise NotImplementedError()





class 					A							(				__snake_case		):





     def __init__(				self		,     SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE = False		,     **SCREAMING_SNAKE_CASE      )					->							Any:






         """simple docstring"""






         A			:  int   =		tokenizer
         A			:  Any   =		skip_prompt
         A			:  Any   =		decode_kwargs

         # variables used in the streaming process
         A			:  List[Any]   =		[]
         A			:  Tuple   =		0
         A			:  Tuple   =		True





     def 							__lowerCAmelCase				(				self		,     SCREAMING_SNAKE_CASE      )					->							Dict:






         """simple docstring"""






         if len(value.shape      ) > 1 and value.shape[0] > 1:
             raise ValueError('''TextStreamer only supports batch size 1'''      )
         elif len(value.shape      ) > 1:
             A			:  Union[str, Any]   =		value[0]

         if self.skip_prompt and self.next_tokens_are_prompt:
             A			:  Optional[int]   =		False
             return

         # Add the new token to the cache and decodes the entire thing.
         self.token_cache.extend(value.tolist()      )
         A			:  Optional[Any]   =		self.tokenizer.decode(self.token_cache		,     **self.decode_kwargs      )

         # After the symbol for a new line, we flush the cache.
         if text.endswith('''\n'''      ):
             A			:  Optional[Any]   =		text[self.print_len :]
             A			:  Any   =		[]
             A			:  Optional[Any]   =		0
         # If the last token is a CJK character, we print the characters.
         elif len(SCREAMING_SNAKE_CASE      ) > 0 and self._is_chinese_char(ord(text[-1]      )      ):
             A			:  Optional[Any]   =		text[self.print_len :]
             self.print_len += len(SCREAMING_SNAKE_CASE      )
         # Otherwise, prints until the last space char (simple heuristic to avoid printing incomplete words,
         # which may change with the subsequent token -- there are probably smarter ways to do this!)
         else:
             A			:  str   =		text[self.print_len : text.rfind(''' '''      ) + 1]
             self.print_len += len(SCREAMING_SNAKE_CASE      )

         self.on_finalized_text(SCREAMING_SNAKE_CASE      )





     def 							__lowerCAmelCase				(				self      )					->							List[Any]:






         """simple docstring"""






         if len(self.token_cache      ) > 0:
             A			:  Any   =		self.tokenizer.decode(self.token_cache		,     **self.decode_kwargs      )
             A			:  Dict   =		text[self.print_len :]
             A			:  str   =		[]
             A			:  int   =		0
         else:
             A			:  Union[str, Any]   =		''''''

         A			:  Tuple   =		True
         self.on_finalized_text(SCREAMING_SNAKE_CASE		,     stream_end=SCREAMING_SNAKE_CASE      )





     def 							__lowerCAmelCase				(				self		,     SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE = False      )					->							Dict:






         """simple docstring"""






         print(SCREAMING_SNAKE_CASE		,     flush=SCREAMING_SNAKE_CASE		,     end='''''' if not stream_end else None      )





     def 							__lowerCAmelCase				(				self		,     SCREAMING_SNAKE_CASE      )					->							Optional[Any]:






         """simple docstring"""






         if (
             (cp >= 0X4_E00 and cp <= 0X9_FFF)
             or (cp >= 0X3_400 and cp <= 0X4_DBF)  #
             or (cp >= 0X20_000 and cp <= 0X2A_6DF)  #
             or (cp >= 0X2A_700 and cp <= 0X2B_73F)  #
             or (cp >= 0X2B_740 and cp <= 0X2B_81F)  #
             or (cp >= 0X2B_820 and cp <= 0X2C_EAF)  #
             or (cp >= 0XF_900 and cp <= 0XF_AFF)
             or (cp >= 0X2F_800 and cp <= 0X2F_A1F)  #
         ):  #
             return True

         return False





class 					A							(				__snake_case		):





     def __init__(				self		,     SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE = False		,     SCREAMING_SNAKE_CASE = None		,     **SCREAMING_SNAKE_CASE      )					->							Tuple:






         """simple docstring"""






         super().__init__(SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE		,     **SCREAMING_SNAKE_CASE      )
         A			:  Tuple   =		Queue()
         A			:  Optional[Any]   =		None
         A			:  Any   =		timeout





     def 							__lowerCAmelCase				(				self		,     SCREAMING_SNAKE_CASE		,     SCREAMING_SNAKE_CASE = False      )					->							Union[str, Any]:






         """simple docstring"""






         self.text_queue.put(SCREAMING_SNAKE_CASE		,     timeout=self.timeout      )
         if stream_end:
             self.text_queue.put(self.stop_signal		,     timeout=self.timeout      )





     def __iter__(				self      )					->							Optional[int]:






         """simple docstring"""






         return self





     def 							__lowerCAmelCase				(				self      )					->							Dict:






         """simple docstring"""






         A			:  Optional[Any]   =		self.text_queue.get(timeout=self.timeout      )
         if value == self.stop_signal:
             raise StopIteration()
         else:
             return value






'''simple docstring'''




import copy

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


lowercase     :							Optional[Any]       						=     logging.get_logger(__name__)

lowercase     :							int       						=     {
    'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}





class 					A							(				__snake_case		):
     __magic_name__          =						'''deta'''
     __magic_name__          =						{
         '''hidden_size''': '''d_model''',
         '''num_attention_heads''': '''encoder_attention_heads''',
     }





     def __init__(				self		,     SCREAMING_SNAKE_CASE=None		,     SCREAMING_SNAKE_CASE=900		,     SCREAMING_SNAKE_CASE=2048		,     SCREAMING_SNAKE_CASE=6		,     SCREAMING_SNAKE_CASE=2048		,     SCREAMING_SNAKE_CASE=8		,     SCREAMING_SNAKE_CASE=6		,     SCREAMING_SNAKE_CASE=1024		,     SCREAMING_SNAKE_CASE=8		,     SCREAMING_SNAKE_CASE=0.0		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE="relu"		,     SCREAMING_SNAKE_CASE=256		,     SCREAMING_SNAKE_CASE=0.1		,     SCREAMING_SNAKE_CASE=0.0		,     SCREAMING_SNAKE_CASE=0.0		,     SCREAMING_SNAKE_CASE=0.02		,     SCREAMING_SNAKE_CASE=1.0		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE=False		,     SCREAMING_SNAKE_CASE="sine"		,     SCREAMING_SNAKE_CASE=5		,     SCREAMING_SNAKE_CASE=4		,     SCREAMING_SNAKE_CASE=4		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE=300		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE=1		,     SCREAMING_SNAKE_CASE=5		,     SCREAMING_SNAKE_CASE=2		,     SCREAMING_SNAKE_CASE=1		,     SCREAMING_SNAKE_CASE=1		,     SCREAMING_SNAKE_CASE=5		,     SCREAMING_SNAKE_CASE=2		,     SCREAMING_SNAKE_CASE=0.1		,     SCREAMING_SNAKE_CASE=0.25		,     **SCREAMING_SNAKE_CASE		,     )					->							Any:






         """simple docstring"""






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

         A			:  str   =		backbone_config
         A			:  Optional[int]   =		num_queries
         A			:  Dict   =		max_position_embeddings
         A			:  Optional[Any]   =		d_model
         A			:  Optional[Any]   =		encoder_ffn_dim
         A			:  List[str]   =		encoder_layers
         A			:  Tuple   =		encoder_attention_heads
         A			:  Optional[Any]   =		decoder_ffn_dim
         A			:  Optional[int]   =		decoder_layers
         A			:  List[str]   =		decoder_attention_heads
         A			:  Union[str, Any]   =		dropout
         A			:  str   =		attention_dropout
         A			:  Any   =		activation_dropout
         A			:  Optional[int]   =		activation_function
         A			:  Tuple   =		init_std
         A			:  Any   =		init_xavier_std
         A			:  Optional[Any]   =		encoder_layerdrop
         A			:  int   =		auxiliary_loss
         A			:  Dict   =		position_embedding_type
         # deformable attributes
         A			:  str   =		num_feature_levels
         A			:  Optional[int]   =		encoder_n_points
         A			:  Any   =		decoder_n_points
         A			:  Tuple   =		two_stage
         A			:  Dict   =		two_stage_num_proposals
         A			:  List[str]   =		with_box_refine
         A			:  List[str]   =		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
         A			:  Dict   =		class_cost
         A			:  Optional[int]   =		bbox_cost
         A			:  Optional[Any]   =		giou_cost
         # Loss coefficients
         A			:  int   =		mask_loss_coefficient
         A			:  int   =		dice_loss_coefficient
         A			:  Tuple   =		bbox_loss_coefficient
         A			:  int   =		giou_loss_coefficient
         A			:  Dict   =		eos_coefficient
         A			:  Optional[Any]   =		focal_alpha
         super().__init__(is_encoder_decoder=SCREAMING_SNAKE_CASE		,     **SCREAMING_SNAKE_CASE      )





     @property
     def 							__lowerCAmelCase				(				self      )					->							int:






         """simple docstring"""






         return self.encoder_attention_heads





     @property
     def 							__lowerCAmelCase				(				self      )					->							int:






         """simple docstring"""






         return self.d_model





     def 							__lowerCAmelCase				(				self      )					->							Any:






         """simple docstring"""






         A			:  Any   =		copy.deepcopy(self.__dict__      )
         A			:  Dict   =		self.backbone_config.to_dict()
         A			:  List[Any]   =		self.__class__.model_type
         return output




