





"""simple docstring"""



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/table-transformer-detection""": (
        """https://huggingface.co/microsoft/table-transformer-detection/resolve/main/config.json"""
    ),
}






class 		__snake_case (		SCREAMING_SNAKE_CASE__					):





 """simple docstring"""


 _lowerCamelCase				=					"""table-transformer"""
 _lowerCamelCase				=					["""past_key_values"""]
 _lowerCamelCase				=					{
     """hidden_size""": """d_model""",
     """num_attention_heads""": """encoder_attention_heads""",
 }

 def __init__(   self ,						__lowerCamelCase=True ,						__lowerCamelCase=None ,						__lowerCamelCase=3 ,						__lowerCamelCase=100 ,						__lowerCamelCase=6 ,						__lowerCamelCase=2048 ,						__lowerCamelCase=8 ,						__lowerCamelCase=6 ,						__lowerCamelCase=2048 ,						__lowerCamelCase=8 ,						__lowerCamelCase=0.0 ,						__lowerCamelCase=0.0 ,						__lowerCamelCase=True ,						__lowerCamelCase="relu" ,						__lowerCamelCase=256 ,						__lowerCamelCase=0.1 ,						__lowerCamelCase=0.0 ,						__lowerCamelCase=0.0 ,						__lowerCamelCase=0.0_2 ,						__lowerCamelCase=1.0 ,						__lowerCamelCase=False ,						__lowerCamelCase="sine" ,						__lowerCamelCase="resnet50" ,						__lowerCamelCase=True ,						__lowerCamelCase=False ,						__lowerCamelCase=1 ,						__lowerCamelCase=5 ,						__lowerCamelCase=2 ,						__lowerCamelCase=1 ,						__lowerCamelCase=1 ,						__lowerCamelCase=5 ,						__lowerCamelCase=2 ,						__lowerCamelCase=0.1 ,						**__lowerCamelCase ,						):



     '''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.'''  )
             __A   :						Dict									=					CONFIG_MAPPING['''resnet'''](out_features=['''stage4''']  )
         elif isinstance(__lowerCamelCase ,						__lowerCamelCase  ):
             __A   :						Tuple									=					backbone_config.get('''model_type'''  )
             __A   :						Any									=					CONFIG_MAPPING[backbone_model_type]
             __A   :						Optional[Any]									=					config_class.from_dict(__lowerCamelCase  )
         # set timm attributes to None
         __A			,	__A			,	__A   :						Optional[int]									=					None, None, None

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

 @property
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     return self.encoder_attention_heads







 @property
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     return self.d_model






class 		__snake_case (		SCREAMING_SNAKE_CASE__					):





 """simple docstring"""


 _lowerCamelCase				=					version.parse("""1.11"""					)

 @property
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




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

 @property
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     return 1e-5







 @property
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     return 12











"""simple docstring"""



import json
import os
import unittest

from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow

from ...test_tokenization_common import TokenizerTesterMixin






class 		__snake_case (		SCREAMING_SNAKE_CASE__							,							unittest.TestCase					):





 """simple docstring"""


 _lowerCamelCase				=					XLMTokenizer
 _lowerCamelCase				=					False

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     super().setUp()

     # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
     __A   :						Tuple									=					[
         '''l''',
         '''o''',
         '''w''',
         '''e''',
         '''r''',
         '''s''',
         '''t''',
         '''i''',
         '''d''',
         '''n''',
         '''w</w>''',
         '''r</w>''',
         '''t</w>''',
         '''lo''',
         '''low''',
         '''er</w>''',
         '''low</w>''',
         '''lowest</w>''',
         '''newer</w>''',
         '''wider</w>''',
         '''<unk>''',
     ]
     __A   :						Dict									=					dict(zip(__lowerCamelCase ,						range(len(__lowerCamelCase  )  )  )  )
     __A   :						Union[str, Any]									=					['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

     __A   :						Optional[Any]									=					os.path.join(self.tmpdirname ,						VOCAB_FILES_NAMES['''vocab_file''']  )
     __A   :						Optional[Any]									=					os.path.join(self.tmpdirname ,						VOCAB_FILES_NAMES['''merges_file''']  )
     with open(self.vocab_file ,						'''w'''  ) as fp:
         fp.write(json.dumps(__lowerCamelCase  )  )
     with open(self.merges_file ,						'''w'''  ) as fp:
         fp.write('''\n'''.join(__lowerCamelCase  )  )

 def  UpperCamelCase__(   self ,						__lowerCamelCase  ):



     '''simple docstring'''




     __A   :						Optional[int]									=					'''lower newer'''
     __A   :						int									=					'''lower newer'''
     return input_text, output_text

 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Union[str, Any]									=					XLMTokenizer(self.vocab_file ,						self.merges_file  )

     __A   :						Optional[Any]									=					'''lower'''
     __A   :						Any									=					['''low''', '''er</w>''']
     __A   :						Tuple									=					tokenizer.tokenize(__lowerCamelCase  )
     self.assertListEqual(__lowerCamelCase ,						__lowerCamelCase  )

     __A   :						str									=					tokens + ['''<unk>''']
     __A   :						List[str]									=					[14, 15, 20]
     self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase  ) ,						__lowerCamelCase  )







 @slow
 def  UpperCamelCase__(   self  ):



     '''simple docstring'''




     __A   :						Optional[int]									=					XLMTokenizer.from_pretrained('''xlm-mlm-en-2048'''  )

     __A   :						Union[str, Any]									=					tokenizer.encode('''sequence builders''' ,						add_special_tokens=__lowerCamelCase  )
     __A   :						int									=					tokenizer.encode('''multi-sequence build''' ,						add_special_tokens=__lowerCamelCase  )

     __A   :						int									=					tokenizer.build_inputs_with_special_tokens(__lowerCamelCase  )
     __A   :						List[Any]									=					tokenizer.build_inputs_with_special_tokens(__lowerCamelCase ,						__lowerCamelCase  )

     assert encoded_sentence == [0] + text + [1]
     assert encoded_pair == [0] + text + [1] + text_a + [1]




