




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


lowercase__				:      Optional[Any]	   = logging.get_logger(__name__)


lowercase__				:      str	   = {"vocab_file": "vocab.json", "merges_file": "merges.txt"}

lowercase__				:      Any	   = {
    "vocab_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
    },
}

lowercase__				:      Tuple	   = {
    "allenai/longformer-base-4096": 4_096,
    "allenai/longformer-large-4096": 4_096,
    "allenai/longformer-large-4096-finetuned-triviaqa": 4_096,
    "allenai/longformer-base-4096-extra.pos.embd.only": 4_096,
    "allenai/longformer-large-4096-extra.pos.embd.only": 4_096,
}

@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def  SCREAMING_SNAKE_CASE							(       )      ->					Optional[int]:
     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(__UpperCamelCase)
               cs.append(2**8 + n)
               n += 1
     a     =				[chr(__UpperCamelCase) for n in cs]
     return dict(zip(__UpperCamelCase		, __UpperCamelCase))

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase)      ->					int:
     a     =				set()
     a     =				word[0]
     for char in word[1:]:
          pairs.add((prev_char, char))
          a     =				char
     return pairs





class       a__	( UpperCamelCase__				):
     a		:      Optional[int]		 =     VOCAB_FILES_NAMES
     a		:      int		 =     PRETRAINED_VOCAB_FILES_MAP
     a		:      Optional[int]		 =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     a		:      Union[str, Any]		 =     ["""input_ids""", """attention_mask"""]







     def __init__(     self  ,		A  ,		A  ,		A="replace"  ,		A="<s>"  ,		A="</s>"  ,		A="</s>"  ,		A="<s>"  ,		A="<unk>"  ,		A="<pad>"  ,		A="<mask>"  ,		A=False  ,		**A  ,		)  ->   List[str]:



          '''simple docstring'''



          a     =				AddedToken(A  ,		lstrip=A  ,		rstrip=A			) if isinstance(A  ,		A			) else bos_token
          a     =				AddedToken(A  ,		lstrip=A  ,		rstrip=A			) if isinstance(A  ,		A			) else eos_token
          a     =				AddedToken(A  ,		lstrip=A  ,		rstrip=A			) if isinstance(A  ,		A			) else sep_token
          a     =				AddedToken(A  ,		lstrip=A  ,		rstrip=A			) if isinstance(A  ,		A			) else cls_token
          a     =				AddedToken(A  ,		lstrip=A  ,		rstrip=A			) if isinstance(A  ,		A			) else unk_token
          a     =				AddedToken(A  ,		lstrip=A  ,		rstrip=A			) if isinstance(A  ,		A			) else pad_token

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

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

          with open(A  ,		encoding="utf-8"			) as vocab_handle:
               a     =				json.load(A			)
          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(A  ,		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(A  ,		range(len(A			)			)			)			)
          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       lowerCAmelCase_    (     self			)  ->   Any:



          '''simple docstring'''



          return len(self.encoder			)







     def       lowerCAmelCase_    (     self			)  ->   List[Any]:



          '''simple docstring'''



          return dict(self.encoder  ,		**self.added_tokens_encoder			)







     def       lowerCAmelCase_    (     self  ,		A			)  ->   Union[str, Any]:



          '''simple docstring'''



          if token in self.cache:
               return self.cache[token]
          a     =				tuple(A			)
          a     =				get_pairs(A			)

          if not pairs:
               return token

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

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







     def       lowerCAmelCase_    (     self  ,		A			)  ->   Union[str, Any]:



          '''simple docstring'''



          a     =				[]
          for token in re.findall(self.pat  ,		A			):
               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(A			).split(" "			)			)
          return bpe_tokens







     def       lowerCAmelCase_    (     self  ,		A			)  ->   int:



          '''simple docstring'''



          return self.encoder.get(A  ,		self.encoder.get(self.unk_token			)			)







     def       lowerCAmelCase_    (     self  ,		A			)  ->   Optional[int]:



          '''simple docstring'''



          return self.decoder.get(A			)







     def       lowerCAmelCase_    (     self  ,		A			)  ->   List[str]:



          '''simple docstring'''



          a     =				"".join(A			)
          a     =				bytearray([self.byte_decoder[c] for c in text]			).decode("utf-8"  ,		errors=self.errors			)
          return text







     def       lowerCAmelCase_    (     self  ,		A  ,		A = None			)  ->   Tuple[str]:



          '''simple docstring'''



          if not os.path.isdir(A			):
               logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''			)
               return
          a     =				os.path.join(
              A  ,		(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]			)
          a     =				os.path.join(
              A  ,		(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]			)

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

          a     =				0
          with open(A  ,		"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 A			: 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(A			) + "\n"			)
                    index += 1

          return vocab_file, merge_file







     def       lowerCAmelCase_    (     self  ,		A  ,		A = None			)  ->   List[int]:



          '''simple docstring'''



          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       lowerCAmelCase_    (     self  ,		A  ,		A = None  ,		A = False			)  ->   List[int]:



          '''simple docstring'''



          if already_has_special_tokens:
               return super().get_special_tokens_mask(
                   token_ids_a=A  ,		token_ids_a=A  ,		already_has_special_tokens=A			)

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







     def       lowerCAmelCase_    (     self  ,		A  ,		A = None			)  ->   List[int]:



          '''simple docstring'''



          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       lowerCAmelCase_    (     self  ,		A  ,		A=False  ,		**A			)  ->   Dict:



          '''simple docstring'''



          a     =				kwargs.pop("add_prefix_space"  ,		self.add_prefix_space			)
          if (is_split_into_words or add_prefix_space) and (len(A			) > 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__				:      Optional[Any]	   = logging.get_logger(__name__)

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




class       a__	( UpperCamelCase__				):
     a		:      Optional[int]		 =     """table-transformer"""
     a		:      Tuple		 =     ["""past_key_values"""]
     a		:      int		 =     {
         """hidden_size""": """d_model""",
         """num_attention_heads""": """encoder_attention_heads""",
     }







     def __init__(     self  ,		A=True  ,		A=None  ,		A=3  ,		A=100  ,		A=6  ,		A=2048  ,		A=8  ,		A=6  ,		A=2048  ,		A=8  ,		A=0.0  ,		A=0.0  ,		A=True  ,		A="relu"  ,		A=256  ,		A=0.1  ,		A=0.0  ,		A=0.0  ,		A=0.0_2  ,		A=1.0  ,		A=False  ,		A="sine"  ,		A="resnet50"  ,		A=True  ,		A=False  ,		A=1  ,		A=5  ,		A=2  ,		A=1  ,		A=1  ,		A=5  ,		A=2  ,		A=0.1  ,		**A  ,		)  ->   List[str]:



          '''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(A  ,		A			):
                    a     =				backbone_config.get("model_type"			)
                    a     =				CONFIG_MAPPING[backbone_model_type]
                    a     =				config_class.from_dict(A			)
               # 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=A  ,		**A			)







     @property
     def       lowerCAmelCase_    (     self			)  ->   int:



          '''simple docstring'''



          return self.encoder_attention_heads







     @property
     def       lowerCAmelCase_    (     self			)  ->   int:



          '''simple docstring'''



          return self.d_model







class       a__	( UpperCamelCase__				):
     a		:      Any		 =     version.parse("""1.11"""				)







     @property
     def       lowerCAmelCase_    (     self			)  ->   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       lowerCAmelCase_    (     self			)  ->   float:



          '''simple docstring'''



          return 1e-5







     @property
     def       lowerCAmelCase_    (     self			)  ->   int:



          '''simple docstring'''



          return 12

