



import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


__snake_case     :Tuple			       =logging.get_logger(__name__)


__snake_case     :Dict			       ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all BART models at https://huggingface.co/models?filter=bart
__snake_case     :Dict			       ={
    'vocab_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/vocab.json',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/vocab.json',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json',
    },
    'merges_file': {
        'facebook/bart-base': 'https://huggingface.co/facebook/bart-base/resolve/main/merges.txt',
        'facebook/bart-large': 'https://huggingface.co/facebook/bart-large/resolve/main/merges.txt',
        'facebook/bart-large-mnli': 'https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt',
        'facebook/bart-large-cnn': 'https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt',
        'facebook/bart-large-xsum': 'https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt',
        'yjernite/bart_eli5': 'https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt',
    },
}

__snake_case     :Optional[int]			       ={
    'facebook/bart-base': 1024,
    'facebook/bart-large': 1024,
    'facebook/bart-large-mnli': 1024,
    'facebook/bart-large-cnn': 1024,
    'facebook/bart-large-xsum': 1024,
    'yjernite/bart_eli5': 1024,
}






@lru_cache()
def  lowerCamelCase_	(      )       ->							Optional[int]:

							'''simple docstring'''






							A      						=    (
							    list(range(ord('!'				)			,	ord('~'				) + 1				)				) + list(range(ord('¡'				)			,	ord('¬'				) + 1				)				) + list(range(ord('®'				)			,	ord('ÿ'				) + 1				)				)
							)
							A      						=    bs[:]
							A      						=    0
							for b in range(2**8				):
														if b not in bs:
																					bs.append(lowerCAmelCase__				)
																					cs.append(2**8 + n				)
																					n += 1
							A      						=    [chr(lowerCAmelCase__				) for n in cs]
							return dict(zip(lowerCAmelCase__			,	lowerCAmelCase__				)				)






def  lowerCamelCase_	(      lowerCAmelCase__	:	Optional[Any]				)       ->							Dict:

							'''simple docstring'''






							A      						=    set()
							A      						=    word[0]
							for char in word[1:]:
														pairs.add((prev_char, char)				)
														A      						=    char
							return pairs



class        lowerCAmelCase__					(  _lowerCamelCase       ):
				A_   :     Optional[Any]								=     VOCAB_FILES_NAMES
				A_   :     List[str]								=     PRETRAINED_VOCAB_FILES_MAP
				A_   :     Optional[Any]								=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				A_   :     str								=     ['input_ids', 'attention_mask']


				def __init__(							self      :  Optional[int]						, __UpperCamelCase      :  Any						, __UpperCamelCase      :  Optional[Any]						, __UpperCamelCase      :  Tuple="replace"						, __UpperCamelCase      :  Any="<s>"						, __UpperCamelCase      :  Dict="</s>"						, __UpperCamelCase      :  List[Any]="</s>"						, __UpperCamelCase      :  List[Any]="<s>"						, __UpperCamelCase      :  str="<unk>"						, __UpperCamelCase      :  Optional[Any]="<pad>"						, __UpperCamelCase      :  Union[str, Any]="<mask>"						, __UpperCamelCase      :  Any=False						, **__UpperCamelCase      :  Any						, )		->     Optional[Any]:
											A      						=    AddedToken(__UpperCamelCase						, lstrip=__UpperCamelCase						, rstrip=__UpperCamelCase       ) if isinstance(__UpperCamelCase						, __UpperCamelCase       ) else bos_token
											A      						=    AddedToken(__UpperCamelCase						, lstrip=__UpperCamelCase						, rstrip=__UpperCamelCase       ) if isinstance(__UpperCamelCase						, __UpperCamelCase       ) else eos_token
											A      						=    AddedToken(__UpperCamelCase						, lstrip=__UpperCamelCase						, rstrip=__UpperCamelCase       ) if isinstance(__UpperCamelCase						, __UpperCamelCase       ) else sep_token
											A      						=    AddedToken(__UpperCamelCase						, lstrip=__UpperCamelCase						, rstrip=__UpperCamelCase       ) if isinstance(__UpperCamelCase						, __UpperCamelCase       ) else cls_token
											A      						=    AddedToken(__UpperCamelCase						, lstrip=__UpperCamelCase						, rstrip=__UpperCamelCase       ) if isinstance(__UpperCamelCase						, __UpperCamelCase       ) else unk_token
											A      						=    AddedToken(__UpperCamelCase						, lstrip=__UpperCamelCase						, rstrip=__UpperCamelCase       ) if isinstance(__UpperCamelCase						, __UpperCamelCase       ) else pad_token

											# Mask token behave like a normal word, i.e. include the space before it
											A      						=    AddedToken(__UpperCamelCase						, lstrip=__UpperCamelCase						, rstrip=__UpperCamelCase       ) if isinstance(__UpperCamelCase						, __UpperCamelCase       ) else mask_token

											super().__init__(
											    errors=__UpperCamelCase						, bos_token=__UpperCamelCase						, eos_token=__UpperCamelCase						, unk_token=__UpperCamelCase						, sep_token=__UpperCamelCase						, cls_token=__UpperCamelCase						, pad_token=__UpperCamelCase						, mask_token=__UpperCamelCase						, add_prefix_space=__UpperCamelCase						, **__UpperCamelCase						, )

											with open(__UpperCamelCase						, encoding='utf-8'       ) as vocab_handle:
																		A      						=    json.load(__UpperCamelCase       )
											A      						=    {v: k for k, v in self.encoder.items()}
											A      						=    errors  # how to handle errors in decoding
											A      						=    bytes_to_unicode()
											A      						=    {v: k for k, v in self.byte_encoder.items()}
											with open(__UpperCamelCase						, encoding='utf-8'       ) as merges_handle:
																		A      						=    merges_handle.read().split('\n'       )[1:-1]
											A      						=    [tuple(merge.split()       ) for merge in bpe_merges]
											A      						=    dict(zip(__UpperCamelCase						, range(len(__UpperCamelCase       )       )       )       )
											A      						=    {}
											A      						=    add_prefix_space

											# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
											A      						=    re.compile(R'\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'       )


				@property
				def __UpperCamelCase						(							self      :  Any       )		->     Any:
											return len(self.encoder       )


				def __UpperCamelCase						(							self      :  Optional[Any]       )		->     str:
											return dict(self.encoder						, **self.added_tokens_encoder       )


				def __UpperCamelCase						(							self      :  List[Any]						, __UpperCamelCase      :  int       )		->     Any:
											if token in self.cache:
																		return self.cache[token]
											A      						=    tuple(__UpperCamelCase       )
											A      						=    get_pairs(__UpperCamelCase       )

											if not pairs:
																		return token

											while True:
																		A      						=    min(__UpperCamelCase						, key=lambda __UpperCamelCase       : self.bpe_ranks.get(__UpperCamelCase						, float('inf'       )       )       )
																		if bigram not in self.bpe_ranks:
																									break
																		A						,   A      						=    bigram
																		A      						=    []
																		A      						=    0
																		while i < len(__UpperCamelCase       ):
																									try:
																																A      						=    word.index(__UpperCamelCase						, __UpperCamelCase       )
																									except ValueError:
																																new_word.extend(word[i:]       )
																																break
																									else:
																																new_word.extend(word[i:j]       )
																																A      						=    j

																									if word[i] == first and i < len(__UpperCamelCase       ) - 1 and word[i + 1] == second:
																																new_word.append(first + second       )
																																i += 2
																									else:
																																new_word.append(word[i]       )
																																i += 1
																		A      						=    tuple(__UpperCamelCase       )
																		A      						=    new_word
																		if len(__UpperCamelCase       ) == 1:
																									break
																		else:
																									A      						=    get_pairs(__UpperCamelCase       )
											A      						=    ' '.join(__UpperCamelCase       )
											A      						=    word
											return word


				def __UpperCamelCase						(							self      :  Optional[int]						, __UpperCamelCase      :  int       )		->     Optional[int]:
											A      						=    []
											for token in re.findall(self.pat						, __UpperCamelCase       ):
																		A      						=    ''.join(
																		    self.byte_encoder[b] for b in token.encode('utf-8'       )       )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
																		bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__UpperCamelCase       ).split(' '       )       )
											return bpe_tokens


				def __UpperCamelCase						(							self      :  List[Any]						, __UpperCamelCase      :  List[Any]       )		->     int:
											return self.encoder.get(__UpperCamelCase						, self.encoder.get(self.unk_token       )       )


				def __UpperCamelCase						(							self      :  Optional[Any]						, __UpperCamelCase      :  Optional[Any]       )		->     Optional[Any]:
											return self.decoder.get(__UpperCamelCase       )


				def __UpperCamelCase						(							self      :  Any						, __UpperCamelCase      :  Optional[Any]       )		->     Any:
											A      						=    ''.join(__UpperCamelCase       )
											A      						=    bytearray([self.byte_decoder[c] for c in text]       ).decode('utf-8'						, errors=self.errors       )
											return text


				def __UpperCamelCase						(							self      :  int						, __UpperCamelCase      :  str						, __UpperCamelCase      :  Optional[str] = None       )		->     Tuple[str]:
											if not os.path.isdir(__UpperCamelCase       ):
																		logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''       )
																		return
											A      						=    os.path.join(
											    __UpperCamelCase						, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']       )
											A      						=    os.path.join(
											    __UpperCamelCase						, (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']       )

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

											A      						=    0
											with open(__UpperCamelCase						, 'w'						, encoding='utf-8'       ) as writer:
																		writer.write('#version: 0.2\n'       )
																		for bpe_tokens, token_index in sorted(self.bpe_ranks.items()						, key=lambda __UpperCamelCase       : kv[1]       ):
																									if index != token_index:
																																logger.warning(
																																    f'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
																																    ' Please check that the tokenizer is not corrupted!'       )
																																A      						=    token_index
																									writer.write(' '.join(__UpperCamelCase       ) + '\n'       )
																									index += 1

											return vocab_file, merge_file


				def __UpperCamelCase						(							self      :  Optional[Any]						, __UpperCamelCase      :  List[int]						, __UpperCamelCase      :  Optional[List[int]] = None       )		->     List[int]:
											if token_ids_a is None:
																		return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
											A      						=    [self.cls_token_id]
											A      						=    [self.sep_token_id]
											return cls + token_ids_a + sep + sep + token_ids_a + sep


				def __UpperCamelCase						(							self      :  Optional[int]						, __UpperCamelCase      :  List[int]						, __UpperCamelCase      :  Optional[List[int]] = None						, __UpperCamelCase      :  bool = False       )		->     List[int]:
											if already_has_special_tokens:
																		return super().get_special_tokens_mask(
																		    token_ids_a=__UpperCamelCase						, token_ids_a=__UpperCamelCase						, already_has_special_tokens=__UpperCamelCase       )

											if token_ids_a is None:
																		return [1] + ([0] * len(__UpperCamelCase       )) + [1]
											return [1] + ([0] * len(__UpperCamelCase       )) + [1, 1] + ([0] * len(__UpperCamelCase       )) + [1]


				def __UpperCamelCase						(							self      :  int						, __UpperCamelCase      :  List[int]						, __UpperCamelCase      :  Optional[List[int]] = None       )		->     List[int]:
											A      						=    [self.sep_token_id]
											A      						=    [self.cls_token_id]

											if token_ids_a is None:
																		return len(cls + token_ids_a + sep       ) * [0]
											return len(cls + token_ids_a + sep + sep + token_ids_a + sep       ) * [0]


				def __UpperCamelCase						(							self      :  int						, __UpperCamelCase      :  str						, __UpperCamelCase      :  Optional[Any]=False						, **__UpperCamelCase      :  Tuple       )		->     Any:
											A      						=    kwargs.pop('add_prefix_space'						, self.add_prefix_space       )
											if (is_split_into_words or add_prefix_space) and (len(__UpperCamelCase       ) > 0 and not text[0].isspace()):
																		A      						=    ' ' + text
											return (text, kwargs)


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


__lowercase				      =						logging.get_logger(__name__)

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

class    _lowercase				(					__lowerCamelCase			):
   _lowercase     :       Any  					=    'table-transformer'
   _lowercase     :       List[Any]  					=    ['past_key_values']
   _lowercase     :       Union[str, Any]  					=    {
       'hidden_size': 'd_model',
       'num_attention_heads': 'encoder_attention_heads',
   }

   def __init__(				self	:    List[Any]			,						lowerCamelCase__	:    Any=True			,						lowerCamelCase__	:    List[Any]=None			,						lowerCamelCase__	:    Any=3			,						lowerCamelCase__	:    Any=1_0_0			,						lowerCamelCase__	:    int=6			,						lowerCamelCase__	:    List[Any]=2_0_4_8			,						lowerCamelCase__	:    List[str]=8			,						lowerCamelCase__	:    int=6			,						lowerCamelCase__	:    List[str]=2_0_4_8			,						lowerCamelCase__	:    Optional[int]=8			,						lowerCamelCase__	:    Union[str, Any]=0.0			,						lowerCamelCase__	:    Any=0.0			,						lowerCamelCase__	:    str=True			,						lowerCamelCase__	:    Optional[Any]="relu"			,						lowerCamelCase__	:    Optional[int]=2_5_6			,						lowerCamelCase__	:    List[str]=0.1			,						lowerCamelCase__	:    str=0.0			,						lowerCamelCase__	:    Optional[int]=0.0			,						lowerCamelCase__	:    Dict=0.02			,						lowerCamelCase__	:    Union[str, Any]=1.0			,						lowerCamelCase__	:    Union[str, Any]=False			,						lowerCamelCase__	:    Optional[int]="sine"			,						lowerCamelCase__	:    str="resnet50"			,						lowerCamelCase__	:    List[str]=True			,						lowerCamelCase__	:    Optional[Any]=False			,						lowerCamelCase__	:    Any=1			,						lowerCamelCase__	:    int=5			,						lowerCamelCase__	:    Union[str, Any]=2			,						lowerCamelCase__	:    List[str]=1			,						lowerCamelCase__	:    Union[str, Any]=1			,						lowerCamelCase__	:    Optional[Any]=5			,						lowerCamelCase__	:    Tuple=2			,						lowerCamelCase__	:    List[str]=0.1			,						**lowerCamelCase__	:    List[str]			,						) ->			Dict:
         """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_							       =		CONFIG_MAPPING['''resnet'''](out_features=['''stage4''']       )
               elif isinstance(lowerCamelCase__			,						lowerCamelCase__       ):
                     A_							       =		backbone_config.get('''model_type'''       )
                     A_							       =		CONFIG_MAPPING[backbone_model_type]
                     A_							       =		config_class.from_dict(lowerCamelCase__       )
               # set timm attributes to None
               A_       ,A_       ,A_							       =		None, None, None

         A_							       =		use_timm_backbone
         A_							       =		backbone_config
         A_							       =		num_channels
         A_							       =		num_queries
         A_							       =		d_model
         A_							       =		encoder_ffn_dim
         A_							       =		encoder_layers
         A_							       =		encoder_attention_heads
         A_							       =		decoder_ffn_dim
         A_							       =		decoder_layers
         A_							       =		decoder_attention_heads
         A_							       =		dropout
         A_							       =		attention_dropout
         A_							       =		activation_dropout
         A_							       =		activation_function
         A_							       =		init_std
         A_							       =		init_xavier_std
         A_							       =		encoder_layerdrop
         A_							       =		decoder_layerdrop
         A_							       =		encoder_layers
         A_							       =		auxiliary_loss
         A_							       =		position_embedding_type
         A_							       =		backbone
         A_							       =		use_pretrained_backbone
         A_							       =		dilation
         # Hungarian matcher
         A_							       =		class_cost
         A_							       =		bbox_cost
         A_							       =		giou_cost
         # Loss coefficients
         A_							       =		mask_loss_coefficient
         A_							       =		dice_loss_coefficient
         A_							       =		bbox_loss_coefficient
         A_							       =		giou_loss_coefficient
         A_							       =		eos_coefficient
         super().__init__(is_encoder_decoder=lowerCamelCase__			,						**lowerCamelCase__       )

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





         return self.encoder_attention_heads





   @property
   def     UpperCamelCase					(				self	:    Any       ) ->			int:
         """simple docstring"""





         return self.d_model



class    _lowercase				(					__lowerCamelCase			):
   _lowercase     :       Tuple  					=    version.parse('1.11'			)

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





         return 1e-5





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





         return 1_2





