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


snake_case      =    logging.get_logger(__name__)

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



class __A     (      A__						):

							'''simple docstring'''

							a_     =					'''conditional_detr'''
							a_     =					['''past_key_values''']
							a_     =					{
							    '''hidden_size''': '''d_model''',
							    '''num_attention_heads''': '''encoder_attention_heads''',
							}






							def __init__(				self   ,	_snake_case=True   ,	_snake_case=None   ,	_snake_case=3   ,	_snake_case=300   ,	_snake_case=6   ,	_snake_case=2048   ,	_snake_case=8   ,	_snake_case=6   ,	_snake_case=2048   ,	_snake_case=8   ,	_snake_case=0.0   ,	_snake_case=0.0   ,	_snake_case=True   ,	_snake_case="relu"   ,	_snake_case=256   ,	_snake_case=0.1   ,	_snake_case=0.0   ,	_snake_case=0.0   ,	_snake_case=0.02   ,	_snake_case=1.0   ,	_snake_case=False   ,	_snake_case="sine"   ,	_snake_case="resnet50"   ,	_snake_case=True   ,	_snake_case=False   ,	_snake_case=2   ,	_snake_case=5   ,	_snake_case=2   ,	_snake_case=1   ,	_snake_case=1   ,	_snake_case=2   ,	_snake_case=5   ,	_snake_case=2   ,	_snake_case=0.25   ,	**_snake_case   ,	):


												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(UpperCamelCase_   ,	UpperCamelCase_ ):
																						_lowerCAmelCase			:		Tuple          = backbone_config.get("model_type" )
																						_lowerCAmelCase			:		Dict          = CONFIG_MAPPING[backbone_model_type]
																						_lowerCAmelCase			:		Optional[int]          = config_class.from_dict(UpperCamelCase_ )

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






							@property
							def 	SCREAMING_SNAKE_CASE__			(				self ):
												return self.encoder_attention_heads






							@property
							def 	SCREAMING_SNAKE_CASE__			(				self ):
												return self.d_model






							def 	SCREAMING_SNAKE_CASE__			(				self ):
												_lowerCAmelCase			:		str          = copy.deepcopy(self.__dict__ )
												if self.backbone_config is not None:
																	_lowerCAmelCase			:		List[str]          = self.backbone_config.to_dict()
												_lowerCAmelCase			:		str          = self.__class__.model_type
												return output



class __A     (      A__						):

							'''simple docstring'''

							a_     =					version.parse('''1.11'''						)






							@property
							def 	SCREAMING_SNAKE_CASE__			(				self ):
												return OrderedDict(
												    [
												        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
												        ("pixel_mask", {0: "batch"}),
												    ] )






							@property
							def 	SCREAMING_SNAKE_CASE__			(				self ):
												return 1E-5






							@property
							def 	SCREAMING_SNAKE_CASE__			(				self ):
												return 12










'''simple docstring'''
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   lowercase      (				A__      ,						unittest.TestCase   ):

		"""simple docstring"""

		_a       					=							LxmertTokenizer
		_a       					=							LxmertTokenizerFast
		_a       					=							True
		_a       					=							True




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							super().setUp()

							UpperCamelCase__  :Any				   =					[
							    '''[UNK]''',
							    '''[CLS]''',
							    '''[SEP]''',
							    '''want''',
							    '''##want''',
							    '''##ed''',
							    '''wa''',
							    '''un''',
							    '''runn''',
							    '''##ing''',
							    ''',''',
							    '''low''',
							    '''lowest''',
							]
							UpperCamelCase__  :str				   =					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        lowerCAmelCase__							(						self       ,  UpperCamelCase_				):

							'''simple docstring'''


							UpperCamelCase__  :Optional[Any]				   =					'''UNwant\u00E9d,running'''
							UpperCamelCase__  :Union[str, Any]				   =					'''unwanted, running'''
							return input_text, output_text




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							UpperCamelCase__  :List[Any]				   =					self.tokenizer_class(self.vocab_file				)

							UpperCamelCase__  :List[Any]				   =					tokenizer.tokenize('''UNwant\u00E9d,running'''				)
							self.assertListEqual(UpperCamelCase_       ,  ['''un''', '''##want''', '''##ed''', ''',''', '''runn''', '''##ing''']				)
							self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase_				)       ,  [7, 4, 5, 10, 8, 9]				)




		def        lowerCAmelCase__							(						self				):

							'''simple docstring'''


							if not self.test_rust_tokenizer:
												return

							UpperCamelCase__  :str				   =					self.get_tokenizer()
							UpperCamelCase__  :Union[str, Any]				   =					self.get_rust_tokenizer()

							UpperCamelCase__  :int				   =					'''I was born in 92000, and this is falsé.'''

							UpperCamelCase__  :Optional[Any]				   =					tokenizer.tokenize(UpperCamelCase_				)
							UpperCamelCase__  :str				   =					rust_tokenizer.tokenize(UpperCamelCase_				)
							self.assertListEqual(UpperCamelCase_       ,  UpperCamelCase_				)

							UpperCamelCase__  :Optional[Any]				   =					tokenizer.encode(UpperCamelCase_       ,  add_special_tokens=UpperCamelCase_				)
							UpperCamelCase__  :int				   =					rust_tokenizer.encode(UpperCamelCase_       ,  add_special_tokens=UpperCamelCase_				)
							self.assertListEqual(UpperCamelCase_       ,  UpperCamelCase_				)

							UpperCamelCase__  :Optional[int]				   =					self.get_rust_tokenizer()
							UpperCamelCase__  :Any				   =					tokenizer.encode(UpperCamelCase_				)
							UpperCamelCase__  :Optional[int]				   =					rust_tokenizer.encode(UpperCamelCase_				)
							self.assertListEqual(UpperCamelCase_       ,  UpperCamelCase_				)