



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


UpperCamelCase__ =						logging.get_logger(__name__)

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






   """simple docstring"""





   lowercase__      :  List[str]      =			'conditional_detr'
   lowercase__      :  Union[str, Any]      =			['past_key_values']
   lowercase__      :  List[str]      =			{
       'hidden_size': 'd_model',
       'num_attention_heads': 'encoder_attention_heads',
   }





   def __init__(				self	:       List[str]			,     lowercase	:       Tuple=True			,     lowercase	:       List[Any]=None			,     lowercase	:       Tuple=3			,     lowercase	:       Optional[Any]=300			,     lowercase	:       Dict=6			,     lowercase	:       str=2_048			,     lowercase	:       Optional[Any]=8			,     lowercase	:       Any=6			,     lowercase	:       Optional[Any]=2_048			,     lowercase	:       Tuple=8			,     lowercase	:       int=0.0			,     lowercase	:       List[Any]=0.0			,     lowercase	:       Optional[Any]=True			,     lowercase	:       Optional[int]="relu"			,     lowercase	:       List[str]=256			,     lowercase	:       int=0.1			,     lowercase	:       List[Any]=0.0			,     lowercase	:       str=0.0			,     lowercase	:       Optional[int]=0.02			,     lowercase	:       Dict=1.0			,     lowercase	:       Union[str, Any]=False			,     lowercase	:       List[Any]="sine"			,     lowercase	:       Any="resnet50"			,     lowercase	:       Dict=True			,     lowercase	:       List[Any]=False			,     lowercase	:       Optional[Any]=2			,     lowercase	:       int=5			,     lowercase	:       Tuple=2			,     lowercase	:       Optional[int]=1			,     lowercase	:       int=1			,     lowercase	:       Dict=2			,     lowercase	:       List[Any]=5			,     lowercase	:       Optional[Any]=2			,     lowercase	:       List[str]=0.25			,     **lowercase	:       Union[str, Any]			,     )						->					Union[str, 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(lowercase			,     lowercase   ):
                     __lowercase					=				backbone_config.get("""model_type"""   )
                     __lowercase					=				CONFIG_MAPPING[backbone_model_type]
                     __lowercase					=				config_class.from_dict(lowercase   )

         __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					=				cls_loss_coefficient
         __lowercase					=				bbox_loss_coefficient
         __lowercase					=				giou_loss_coefficient
         __lowercase					=				focal_alpha
         super().__init__(is_encoder_decoder=lowercase			,     **lowercase   )





   @property
   def 		snake_case__			(				self	:       Optional[int]   )						->					int:
         """simple docstring"""







         return self.encoder_attention_heads





   @property
   def 		snake_case__			(				self	:       Tuple   )						->					int:
         """simple docstring"""







         return self.d_model







   def 		snake_case__			(				self	:       Tuple   )						->					Optional[Any]:
         """simple docstring"""







         __lowercase					=				copy.deepcopy(self.__dict__   )
         if self.backbone_config is not None:
               __lowercase					=				self.backbone_config.to_dict()
         __lowercase					=				self.__class__.model_type
         return output





class 			_lowerCAmelCase   ( _UpperCAmelCase			):






   """simple docstring"""





   lowercase__      :  Optional[int]      =			version.parse("""1.11"""			)





   @property
   def 		snake_case__			(				self	:       List[str]   )						->					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 		snake_case__			(				self	:       Any   )						->					float:
         """simple docstring"""







         return 1E-5







   @property
   def 		snake_case__			(				self	:       List[Any]   )						->					int:
         """simple docstring"""







         return 12










import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class 			_lowerCAmelCase   ( _UpperCAmelCase    ,					unittest.TestCase			):






			"""simple docstring"""





			lowercase__      :  Tuple      =			LxmertTokenizer
			lowercase__      :  List[str]      =			LxmertTokenizerFast
			lowercase__      :  Optional[Any]      =			True
			lowercase__      :  List[Any]      =			True





			def 		snake_case__			(				self	:       Tuple   )						->					Tuple:
									"""simple docstring"""







									super().setUp()

									__lowercase					=				[
									    """[UNK]""",
									    """[CLS]""",
									    """[SEP]""",
									    """want""",
									    """##want""",
									    """##ed""",
									    """wa""",
									    """un""",
									    """runn""",
									    """##ing""",
									    """,""",
									    """low""",
									    """lowest""",
									]
									__lowercase					=				os.path.join(self.tmpdirname			,     VOCAB_FILES_NAMES["""vocab_file"""]   )
									with open(self.vocab_file			,     """w"""			,     encoding="""utf-8"""   ) as vocab_writer:
															vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]   )   )





			def 		snake_case__			(				self	:       Optional[int]			,     lowercase	:       int   )						->					List[Any]:
									"""simple docstring"""







									__lowercase					=				"""UNwant\u00E9d,running"""
									__lowercase					=				"""unwanted, running"""
									return input_text, output_text





			def 		snake_case__			(				self	:       str   )						->					Any:
									"""simple docstring"""







									__lowercase					=				self.tokenizer_class(self.vocab_file   )

									__lowercase					=				tokenizer.tokenize("""UNwant\u00E9d,running"""   )
									self.assertListEqual(lowercase			,     ["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]   )
									self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase   )			,     [7, 4, 5, 10, 8, 9]   )







			def 		snake_case__			(				self	:       Union[str, Any]   )						->					int:
									"""simple docstring"""







									if not self.test_rust_tokenizer:
															return

									__lowercase					=				self.get_tokenizer()
									__lowercase					=				self.get_rust_tokenizer()

									__lowercase					=				"""I was born in 92000, and this is falsé."""

									__lowercase					=				tokenizer.tokenize(lowercase   )
									__lowercase					=				rust_tokenizer.tokenize(lowercase   )
									self.assertListEqual(lowercase			,     lowercase   )

									__lowercase					=				tokenizer.encode(lowercase			,     add_special_tokens=lowercase   )
									__lowercase					=				rust_tokenizer.encode(lowercase			,     add_special_tokens=lowercase   )
									self.assertListEqual(lowercase			,     lowercase   )

									__lowercase					=				self.get_rust_tokenizer()
									__lowercase					=				tokenizer.encode(lowercase   )
									__lowercase					=				rust_tokenizer.encode(lowercase   )
									self.assertListEqual(lowercase			,     lowercase   )





