




'''simple docstring'''







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

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


A									=logging.get_logger(__name__)


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

# See all LED models at https://huggingface.co/models?filter=LED
A									={
    "vocab_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json",
    },
    "merges_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json",
    },
}

A									={
    "allenai/led-base-16384": 1_63_84,
}





@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def 		snake_case_							():
    UpperCAmelCase     =	(
        list(range(ord('''!'''  )					,     ord('''~'''  ) + 1  )  ) + list(range(ord('''¡'''  )					,     ord('''¬'''  ) + 1  )  ) + list(range(ord('''®'''  )					,     ord('''ÿ'''  ) + 1  )  )
    )
    UpperCAmelCase     =	bs[:]
    UpperCAmelCase     =	0
    for b in range(2**8  ):
        if b not in bs:
            bs.append(_A  )
            cs.append(2**8 + n  )
            n += 1
    UpperCAmelCase     =	[chr(_A  ) for n in cs]
    return dict(zip(_A					,     _A  )  )





def 		snake_case_							(_a			:							Any  ):
    UpperCAmelCase     =	set()
    UpperCAmelCase     =	word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)  )
        UpperCAmelCase     =	char
    return pairs







class     _a						(			lowercase__				):
       __a       :  str            =      VOCAB_FILES_NAMES
       __a       :  List[str]            =      PRETRAINED_VOCAB_FILES_MAP
       __a       :  Tuple            =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __a       :  Tuple            =      ["""input_ids""", """attention_mask"""]
       def __init__(			self		:			str     ,       lowercase		:			Optional[int]     ,       lowercase		:			Dict     ,       lowercase		:			Union[str, Any]="replace"     ,       lowercase		:			Optional[Any]="<s>"     ,       lowercase		:			int="</s>"     ,       lowercase		:			str="</s>"     ,       lowercase		:			List[str]="<s>"     ,       lowercase		:			Optional[int]="<unk>"     ,       lowercase		:			List[str]="<pad>"     ,       lowercase		:			Union[str, Any]="<mask>"     ,       lowercase		:			Tuple=False     ,       **lowercase		:			Optional[Any]     ,       ):



           '''simple docstring'''

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

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

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

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

           # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
           UpperCAmelCase     =	re.compile(R'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'''       )
       @property
       # Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
       def 					A   (			self		:			Union[str, Any]       ):



           '''simple docstring'''

           return len(self.encoder       )
       def 					A   (			self		:			Union[str, Any]       ):



           '''simple docstring'''

           return dict(self.encoder     ,       **self.added_tokens_encoder       )
       def 					A   (			self		:			Tuple     ,       lowercase		:			Dict       ):



           '''simple docstring'''

           if token in self.cache:
               return self.cache[token]
           UpperCAmelCase     =	tuple(__lowerCamelCase       )
           UpperCAmelCase     =	get_pairs(__lowerCamelCase       )

           if not pairs:
               return token

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

                   if word[i] == first and i < len(__lowerCamelCase       ) - 1 and word[i + 1] == second:
                       new_word.append(first + second       )
                       i += 2
                   else:
                       new_word.append(word[i]       )
                       i += 1
               UpperCAmelCase     =	tuple(__lowerCamelCase       )
               UpperCAmelCase     =	new_word
               if len(__lowerCamelCase       ) == 1:
                   break
               else:
                   UpperCAmelCase     =	get_pairs(__lowerCamelCase       )
           UpperCAmelCase     =	" ".join(__lowerCamelCase       )
           UpperCAmelCase     =	word
           return word
       def 					A   (			self		:			Tuple     ,       lowercase		:			List[Any]       ):



           '''simple docstring'''

           UpperCAmelCase     =	[]
           for token in re.findall(self.pat     ,       __lowerCamelCase       ):
               UpperCAmelCase     =	"".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(__lowerCamelCase       ).split(''' '''       )       )
           return bpe_tokens
       def 					A   (			self		:			Any     ,       lowercase		:			int       ):



           '''simple docstring'''

           return self.encoder.get(__lowerCamelCase     ,       self.encoder.get(self.unk_token       )       )
       def 					A   (			self		:			List[Any]     ,       lowercase		:			Union[str, Any]       ):



           '''simple docstring'''

           return self.decoder.get(__lowerCamelCase       )
       def 					A   (			self		:			Union[str, Any]     ,       lowercase		:			Tuple       ):



           '''simple docstring'''

           UpperCAmelCase     =	"".join(__lowerCamelCase       )
           UpperCAmelCase     =	bytearray([self.byte_decoder[c] for c in text]       ).decode('''utf-8'''     ,       errors=self.errors       )
           return text
       def 					A   (			self		:			Optional[int]     ,       lowercase		:			str     ,       lowercase		:			Optional[str] = None       ):



           '''simple docstring'''

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

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

           UpperCAmelCase     =	0
           with open(__lowerCamelCase     ,       '''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 lowercase       : 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!'''       )
                       UpperCAmelCase     =	token_index
                   writer.write(''' '''.join(__lowerCamelCase       ) + '''\n'''       )
                   index += 1

           return vocab_file, merge_file
       def 					A   (			self		:			int     ,       lowercase		:			List[int]     ,       lowercase		:			Optional[List[int]] = None       ):



           '''simple docstring'''

           if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
           UpperCAmelCase     =	[self.cls_token_id]
           UpperCAmelCase     =	[self.sep_token_id]
           return cls + token_ids_a + sep + sep + token_ids_a + sep
       def 					A   (			self		:			Tuple     ,       lowercase		:			List[int]     ,       lowercase		:			Optional[List[int]] = None     ,       lowercase		:			bool = False       ):



           '''simple docstring'''

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

           if token_ids_a is None:
               return [1] + ([0] * len(__lowerCamelCase       )) + [1]
           return [1] + ([0] * len(__lowerCamelCase       )) + [1, 1] + ([0] * len(__lowerCamelCase       )) + [1]
       def 					A   (			self		:			List[Any]     ,       lowercase		:			List[int]     ,       lowercase		:			Optional[List[int]] = None       ):



           '''simple docstring'''

           UpperCAmelCase     =	[self.sep_token_id]
           UpperCAmelCase     =	[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 					A   (			self		:			List[str]     ,       lowercase		:			int     ,       lowercase		:			Dict=False     ,       **lowercase		:			List[str]       ):



           '''simple docstring'''

           UpperCAmelCase     =	kwargs.pop('''add_prefix_space'''     ,       self.add_prefix_space       )
           if (is_split_into_words or add_prefix_space) and (len(__lowerCamelCase       ) > 0 and not text[0].isspace()):
               UpperCAmelCase     =	" " + text
           return (text, kwargs)







       def 					A   (			self		:			Dict     ,       lowercase		:			Union[Dict[str, EncodedInput], BatchEncoding]     ,       lowercase		:			Optional[int] = None     ,       lowercase		:			PaddingStrategy = PaddingStrategy.DO_NOT_PAD     ,       lowercase		:			Optional[int] = None     ,       lowercase		:			Optional[bool] = None     ,       ):



           '''simple docstring'''

           UpperCAmelCase     =	super()._pad(
               encoded_inputs=__lowerCamelCase     ,       max_length=__lowerCamelCase     ,       padding_strategy=__lowerCamelCase     ,       pad_to_multiple_of=__lowerCamelCase     ,       return_attention_mask=__lowerCamelCase     ,       )

           # Load from model defaults
           if return_attention_mask is None:
               UpperCAmelCase     =	"attention_mask" in self.model_input_names

           if return_attention_mask and "global_attention_mask" in encoded_inputs:
               UpperCAmelCase     =	encoded_inputs[self.model_input_names[0]]
               # `global_attention_mask` need to have the same length as other (sequential) inputs.
               UpperCAmelCase     =	len(encoded_inputs['''global_attention_mask''']       ) != len(__lowerCamelCase       )

               if needs_to_be_padded:
                   UpperCAmelCase     =	len(__lowerCamelCase       ) - len(encoded_inputs['''global_attention_mask''']       )

                   if self.padding_side == "right":
                       # Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
                       UpperCAmelCase     =	(
                           encoded_inputs["global_attention_mask"] + [-1] * difference
                       )
                   elif self.padding_side == "left":
                       UpperCAmelCase     =	[-1] * difference + encoded_inputs[
                           "global_attention_mask"
                       ]
                   else:
                       raise ValueError('''Invalid padding strategy:''' + str(self.padding_side       )       )

           return encoded_inputs










'''simple docstring'''







import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


A									=logging.get_logger(__name__)


class     _a						(			__a				):
       def __init__(			self		:			List[str]     ,       *lowercase		:			List[str]     ,       **lowercase		:			Optional[int]       ):



           '''simple docstring'''

           warnings.warn(
               '''The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
               ''' use CLIPImageProcessor instead.'''     ,       lowercase     ,       )
           super().__init__(*lowercase     ,       **lowercase       )




