




"""simple docstring"""


import copy
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


_A													=      logging.get_logger(__name__)

_A													=      {
    """microsoft/conditional-detr-resnet-50""": (
        """https://huggingface.co/microsoft/conditional-detr-resnet-50/resolve/main/config.json"""
    ),
}


class _lowerCamelCase    (					__lowerCAmelCase						):
   _lowerCamelCase    :Dict     				=     '''conditional_detr'''
   _lowerCamelCase    :str     				=     ['''past_key_values''']
   _lowerCamelCase    :List[str]     				=     {
       '''hidden_size''': '''d_model''',
       '''num_attention_heads''': '''encoder_attention_heads''',
   }






   def __init__(		self       :		Dict   ,     UpperCamelCase       :		Union[str, Any]=True   ,     UpperCamelCase       :		Optional[int]=None   ,     UpperCamelCase       :		int=3   ,     UpperCamelCase       :		Tuple=3_00   ,     UpperCamelCase       :		List[str]=6   ,     UpperCamelCase       :		str=20_48   ,     UpperCamelCase       :		int=8   ,     UpperCamelCase       :		List[str]=6   ,     UpperCamelCase       :		List[Any]=20_48   ,     UpperCamelCase       :		Dict=8   ,     UpperCamelCase       :		Union[str, Any]=0.0   ,     UpperCamelCase       :		Any=0.0   ,     UpperCamelCase       :		Tuple=True   ,     UpperCamelCase       :		List[str]="relu"   ,     UpperCamelCase       :		Dict=2_56   ,     UpperCamelCase       :		Tuple=0.1   ,     UpperCamelCase       :		Any=0.0   ,     UpperCamelCase       :		Dict=0.0   ,     UpperCamelCase       :		Optional[Any]=0.02   ,     UpperCamelCase       :		str=1.0   ,     UpperCamelCase       :		Optional[Any]=False   ,     UpperCamelCase       :		Union[str, Any]="sine"   ,     UpperCamelCase       :		Any="resnet50"   ,     UpperCamelCase       :		Tuple=True   ,     UpperCamelCase       :		Optional[int]=False   ,     UpperCamelCase       :		List[str]=2   ,     UpperCamelCase       :		List[str]=5   ,     UpperCamelCase       :		Optional[Any]=2   ,     UpperCamelCase       :		Tuple=1   ,     UpperCamelCase       :		str=1   ,     UpperCamelCase       :		Optional[Any]=2   ,     UpperCamelCase       :		str=5   ,     UpperCamelCase       :		int=2   ,     UpperCamelCase       :		Union[str, Any]=0.25   ,     **UpperCamelCase       :		Union[str, Any]   ,     )			->						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."""   )
                     lowerCAmelCase__      :			int   =	CONFIG_MAPPING["""resnet"""](out_features=["""stage4"""]   )
               elif isinstance(lowerCAmelCase_   ,     lowerCAmelCase_   ):
                     lowerCAmelCase__      :			List[str]   =	backbone_config.get("""model_type"""   )
                     lowerCAmelCase__      :			Tuple   =	CONFIG_MAPPING[backbone_model_type]
                     lowerCAmelCase__      :			Optional[Any]   =	config_class.from_dict(lowerCAmelCase_   )

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






   @property
   def 	_lowerCAmelCase   (		self       :		Optional[int]   )			->						int:

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






   @property
   def 	_lowerCAmelCase   (		self       :		Optional[int]   )			->						int:

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






   def 	_lowerCAmelCase   (		self       :		Dict   )			->						Union[str, Any]:

         """simple docstring"""
         lowerCAmelCase__      :			Dict   =	copy.deepcopy(self.__dict__   )
         if self.backbone_config is not None:
               lowerCAmelCase__      :			int   =	self.backbone_config.to_dict()
         lowerCAmelCase__      :			Any   =	self.__class__.model_type
         return output






class _lowerCamelCase    (					__lowerCAmelCase						):
   _lowerCamelCase    :Union[str, Any]     				=     version.parse("1.11"						)






   @property
   def 	_lowerCAmelCase   (		self       :		Dict   )			->						Mapping[str, Mapping[int, str]]:

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






   @property
   def 	_lowerCAmelCase   (		self       :		Any   )			->						float:

         """simple docstring"""
         return 1E-5






   @property
   def 	_lowerCAmelCase   (		self       :		str   )			->						int:

         """simple docstring"""
         return 12











"""simple docstring"""


import json
import os
from typing import Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_A													=      logging.get_logger(__name__)

_A													=      {"""vocab_file""": """vocab.json"""}

_A													=      {
    """vocab_file""": {
        """mgp-str""": """https://huggingface.co/alibaba-damo/mgp-str-base/blob/main/vocab.json""",
    }
}

_A													=      {"""mgp-str""": 2_7}


class _lowerCamelCase    (					a_						):
   _lowerCamelCase    :Dict     				=     VOCAB_FILES_NAMES
   _lowerCamelCase    :Union[str, Any]     				=     PRETRAINED_VOCAB_FILES_MAP
   _lowerCamelCase    :Optional[int]     				=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES






   def __init__(		self       :		Optional[int]   ,     UpperCamelCase       :		int   ,     UpperCamelCase       :		Union[str, Any]="[GO]"   ,     UpperCamelCase       :		Any="[GO]"   ,     UpperCamelCase       :		Tuple="[s]"   ,     UpperCamelCase       :		List[Any]="[GO]"   ,     **UpperCamelCase       :		Dict   )			->						Union[str, Any]:

         """simple docstring"""
         super().__init__(
             unk_token=UpperCamelCase   ,     bos_token=UpperCamelCase   ,     eos_token=UpperCamelCase   ,     pad_token=UpperCamelCase   ,     **UpperCamelCase   ,     )

         with open(UpperCamelCase   ,     encoding="""utf-8"""   ) as vocab_handle:
               lowerCAmelCase__      :			Optional[Any]   =	json.load(UpperCamelCase   )
         lowerCAmelCase__      :			Union[str, Any]   =	{v: k for k, v in self.vocab.items()}






   @property
   def 	_lowerCAmelCase   (		self       :		int   )			->						Dict:

         """simple docstring"""
         return len(self.vocab   )






   def 	_lowerCAmelCase   (		self       :		Dict   )			->						Any:

         """simple docstring"""
         return dict(self.vocab   ,     **self.added_tokens_encoder   )






   def 	_lowerCAmelCase   (		self       :		List[Any]   ,     UpperCamelCase       :		Tuple   )			->						Optional[Any]:

         """simple docstring"""
         lowerCAmelCase__      :			Optional[Any]   =	[]
         for s in text:
               char_tokens.extend(UpperCamelCase   )
         return char_tokens






   def 	_lowerCAmelCase   (		self       :		List[Any]   ,     UpperCamelCase       :		str   )			->						Tuple:

         """simple docstring"""
         return self.vocab.get(UpperCamelCase   ,     self.vocab.get(self.unk_token   )   )






   def 	_lowerCAmelCase   (		self       :		List[str]   ,     UpperCamelCase       :		int   )			->						Any:

         """simple docstring"""
         return self.decoder.get(UpperCamelCase   )






   def 	_lowerCAmelCase   (		self       :		Dict   ,     UpperCamelCase       :		str   ,     UpperCamelCase       :		Optional[str] = None   )			->						Tuple[str]:

         """simple docstring"""
         if not os.path.isdir(UpperCamelCase   ):
               logger.error("""Vocabulary path ({}) should be a directory""".format(UpperCamelCase   )   )
               return
         lowerCAmelCase__      :			Union[str, Any]   =	os.path.join(
             UpperCamelCase   ,     (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]   )

         with open(UpperCamelCase   ,     """w"""   ,     encoding="""utf-8"""   ) as f:
               f.write(json.dumps(self.vocab   ,     indent=2   ,     sort_keys=UpperCamelCase   ,     ensure_ascii=UpperCamelCase   ) + """\n"""   )

         return (vocab_file,)





