



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__   :					Tuple 						=      logging.get_logger(__name__)

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



class    UpperCAmelCase__(				lowerCamelCase						):

   '''simple docstring'''




   A     :	int												=     "table-transformer"
   A     :	List[str]												=     ["past_key_values"]
   A     :	Any												=     {
       "hidden_size": "d_model",
       "num_attention_heads": "encoder_attention_heads",
   }


   def __init__(    self	:      Union[str, Any]      ,					lowerCAmelCase	:      Optional[int]=True      ,					lowerCAmelCase	:      Any=None      ,					lowerCAmelCase	:      Optional[Any]=3      ,					lowerCAmelCase	:      List[str]=1_00      ,					lowerCAmelCase	:      Optional[int]=6      ,					lowerCAmelCase	:      List[Any]=20_48      ,					lowerCAmelCase	:      Any=8      ,					lowerCAmelCase	:      Optional[int]=6      ,					lowerCAmelCase	:      Optional[Any]=20_48      ,					lowerCAmelCase	:      Union[str, Any]=8      ,					lowerCAmelCase	:      List[str]=0.0      ,					lowerCAmelCase	:      Optional[int]=0.0      ,					lowerCAmelCase	:      Dict=True      ,					lowerCAmelCase	:      Tuple="relu"      ,					lowerCAmelCase	:      Optional[int]=2_56      ,					lowerCAmelCase	:      int=0.1      ,					lowerCAmelCase	:      Any=0.0      ,					lowerCAmelCase	:      Tuple=0.0      ,					lowerCAmelCase	:      List[str]=0.02      ,					lowerCAmelCase	:      List[str]=1.0      ,					lowerCAmelCase	:      Any=False      ,					lowerCAmelCase	:      Tuple="sine"      ,					lowerCAmelCase	:      Optional[Any]="resnet50"      ,					lowerCAmelCase	:      Any=True      ,					lowerCAmelCase	:      int=False      ,					lowerCAmelCase	:      List[Any]=1      ,					lowerCAmelCase	:      List[str]=5      ,					lowerCAmelCase	:      List[str]=2      ,					lowerCAmelCase	:      Union[str, Any]=1      ,					lowerCAmelCase	:      int=1      ,					lowerCAmelCase	:      Optional[int]=5      ,					lowerCAmelCase	:      Optional[int]=2      ,					lowerCAmelCase	:      Dict=0.1      ,					**lowerCAmelCase	:      List[Any]      ,					)						->					Optional[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(lowerCAmelCase      ,					lowerCAmelCase):
                     lowercase__  =	backbone_config.get('model_type')
                     lowercase__  =	CONFIG_MAPPING[backbone_model_type]
                     lowercase__  =	config_class.from_dict(lowerCAmelCase)
               # set timm attributes to None
               lowercase__,						lowercase__,						lowercase__  =	None, None, None

         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__  =	bbox_loss_coefficient
         lowercase__  =	giou_loss_coefficient
         lowercase__  =	eos_coefficient
         super().__init__(is_encoder_decoder=lowerCAmelCase      ,					**lowerCAmelCase)


   @property
   def       UpperCAmelCase		(    self	:      int)						->					int:




         """simple docstring"""

         return self.encoder_attention_heads



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




         """simple docstring"""

         return self.d_model



class    UpperCAmelCase__(				lowerCamelCase						):

   '''simple docstring'''




   A     :	Tuple												=     version.parse("1.11"						)


   @property
   def       UpperCAmelCase		(    self	:      List[Any])						->					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       UpperCAmelCase		(    self	:      int)						->					float:




         """simple docstring"""

         return 1E-5



   @property
   def       UpperCAmelCase		(    self	:      Union[str, Any])						->					int:




         """simple docstring"""

         return 12





import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin



@require_jieba
class    UpperCAmelCase__(				lowerCamelCase  ,				unittest.TestCase						):

   '''simple docstring'''




   A     :	Optional[int]												=     CpmAntTokenizer
   A     :	Optional[int]												=     False


   def       UpperCAmelCase		(    self	:      List[str])						->					str:




         """simple docstring"""

         super().setUp()

         lowercase__  =	[
             '<d>',
             '</d>',
             '<s>',
             '</s>',
             '</_>',
             '<unk>',
             '<pad>',
             '</n>',
             '我',
             '是',
             'C',
             'P',
             'M',
             'A',
             'n',
             't',
         ]
         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]))



   @tooslow
   def       UpperCAmelCase		(    self	:      str)						->					Optional[Any]:




         """simple docstring"""

         lowercase__  =	CpmAntTokenizer.from_pretrained('openbmb/cpm-ant-10b')
         lowercase__  =	'今天天气真好！'
         lowercase__  =	['今天', '天气', '真', '好', '！']
         lowercase__  =	tokenizer.tokenize(lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase      ,					lowerCAmelCase)
         lowercase__  =	'今天天气真好！'
         lowercase__  =	[tokenizer.bos_token] + tokens

         lowercase__  =	[6, 98_02, 1_49_62, 20_82, 8_31, 2_44]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase)      ,					lowerCAmelCase)

         lowercase__  =	tokenizer.decode(lowerCAmelCase)
         self.assertEqual(lowerCAmelCase      ,					lowerCAmelCase)
