





'''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


_SCREAMING_SNAKE_CASE									=				logging.get_logger(__name__)


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

# See all LED models at https://huggingface.co/models?filter=LED
_SCREAMING_SNAKE_CASE									=				{
    "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",
    },
}

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


@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def 						__a():



    '''simple docstring'''





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


def 						__a(SCREAMING_SNAKE_CASE_	:       Optional[Any]     ):



    '''simple docstring'''





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





class  lowerCAmelCase_		(		__magic_name__		):
 __lowerCamelCase    :				Optional[int]								=       VOCAB_FILES_NAMES
 __lowerCamelCase    :				str								=       PRETRAINED_VOCAB_FILES_MAP
 __lowerCamelCase    :				List[Any]								=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCamelCase    :				str								=       ["input_ids", "attention_mask"]




 def __init__(						self      ,  _lowerCAmelCase      ,  _lowerCAmelCase      ,  _lowerCAmelCase="replace"      ,  _lowerCAmelCase="<s>"      ,  _lowerCAmelCase="</s>"      ,  _lowerCAmelCase="</s>"      ,  _lowerCAmelCase="<s>"      ,  _lowerCAmelCase="<unk>"      ,  _lowerCAmelCase="<pad>"      ,  _lowerCAmelCase="<mask>"      ,  _lowerCAmelCase=False      ,  **_lowerCAmelCase      ,  )     ->				str:
     _lowerCAmelCase						      =   AddedToken(_lowerCAmelCase      ,  lstrip=_lowerCAmelCase      ,  rstrip=_lowerCAmelCase		) if isinstance(_lowerCAmelCase      ,  _lowerCAmelCase		) else bos_token
     _lowerCAmelCase						      =   AddedToken(_lowerCAmelCase      ,  lstrip=_lowerCAmelCase      ,  rstrip=_lowerCAmelCase		) if isinstance(_lowerCAmelCase      ,  _lowerCAmelCase		) else eos_token
     _lowerCAmelCase						      =   AddedToken(_lowerCAmelCase      ,  lstrip=_lowerCAmelCase      ,  rstrip=_lowerCAmelCase		) if isinstance(_lowerCAmelCase      ,  _lowerCAmelCase		) else sep_token
     _lowerCAmelCase						      =   AddedToken(_lowerCAmelCase      ,  lstrip=_lowerCAmelCase      ,  rstrip=_lowerCAmelCase		) if isinstance(_lowerCAmelCase      ,  _lowerCAmelCase		) else cls_token
     _lowerCAmelCase						      =   AddedToken(_lowerCAmelCase      ,  lstrip=_lowerCAmelCase      ,  rstrip=_lowerCAmelCase		) if isinstance(_lowerCAmelCase      ,  _lowerCAmelCase		) else unk_token
     _lowerCAmelCase						      =   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
     _lowerCAmelCase						      =   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:
         _lowerCAmelCase						      =   json.load(_lowerCAmelCase		)
     _lowerCAmelCase						      =   {v: k for k, v in self.encoder.items()}
     _lowerCAmelCase						      =   errors  # how to handle errors in decoding
     _lowerCAmelCase						      =   bytes_to_unicode()
     _lowerCAmelCase						      =   {v: k for k, v in self.byte_encoder.items()}
     with open(_lowerCAmelCase      ,  encoding="utf-8"		) as merges_handle:
         _lowerCAmelCase						      =   merges_handle.read().split("\n"		)[1:-1]
     _lowerCAmelCase						      =   [tuple(merge.split()		) for merge in bpe_merges]
     _lowerCAmelCase						      =   dict(zip(_lowerCAmelCase      ,  range(len(_lowerCAmelCase		)		)		)		)
     _lowerCAmelCase						      =   {}
     _lowerCAmelCase						      =   add_prefix_space

     # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
     _lowerCAmelCase						      =   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 				_snake_case (						self		)     ->				Union[str, Any]:
     return len(self.encoder		)




 def 				_snake_case (						self		)     ->				Dict:
     return dict(self.encoder      ,  **self.added_tokens_encoder		)




 def 				_snake_case (						self      ,  _lowerCAmelCase		)     ->				Union[str, Any]:
     if token in self.cache:
         return self.cache[token]
     _lowerCAmelCase						      =   tuple(_lowerCAmelCase		)
     _lowerCAmelCase						      =   get_pairs(_lowerCAmelCase		)

     if not pairs:
         return token

     while True:
         _lowerCAmelCase						      =   min(_lowerCAmelCase      ,  key=lambda _lowerCAmelCase		: self.bpe_ranks.get(_lowerCAmelCase      ,  float("inf"		)		)		)
         if bigram not in self.bpe_ranks:
             break
         _lowerCAmelCase      ,      _lowerCAmelCase						      =   bigram
         _lowerCAmelCase						      =   []
         _lowerCAmelCase						      =   0
         while i < len(_lowerCAmelCase		):
             try:
                 _lowerCAmelCase						      =   word.index(_lowerCAmelCase      ,  _lowerCAmelCase		)
             except ValueError:
                 new_word.extend(word[i:]		)
                 break
             else:
                 new_word.extend(word[i:j]		)
                 _lowerCAmelCase						      =   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
         _lowerCAmelCase						      =   tuple(_lowerCAmelCase		)
         _lowerCAmelCase						      =   new_word
         if len(_lowerCAmelCase		) == 1:
             break
         else:
             _lowerCAmelCase						      =   get_pairs(_lowerCAmelCase		)
     _lowerCAmelCase						      =   " ".join(_lowerCAmelCase		)
     _lowerCAmelCase						      =   word
     return word




 def 				_snake_case (						self      ,  _lowerCAmelCase		)     ->				str:
     _lowerCAmelCase						      =   []
     for token in re.findall(self.pat      ,  _lowerCAmelCase		):
         _lowerCAmelCase						      =   "".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 				_snake_case (						self      ,  _lowerCAmelCase		)     ->				Dict:
     return self.encoder.get(_lowerCAmelCase      ,  self.encoder.get(self.unk_token		)		)




 def 				_snake_case (						self      ,  _lowerCAmelCase		)     ->				List[Any]:
     return self.decoder.get(_lowerCAmelCase		)




 def 				_snake_case (						self      ,  _lowerCAmelCase		)     ->				Optional[int]:
     _lowerCAmelCase						      =   "".join(_lowerCAmelCase		)
     _lowerCAmelCase						      =   bytearray([self.byte_decoder[c] for c in text]		).decode("utf-8"      ,  errors=self.errors		)
     return text




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

     _lowerCAmelCase						      =   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 _lowerCAmelCase		: 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!"		)
                 _lowerCAmelCase						      =   token_index
             writer.write(" ".join(_lowerCAmelCase		) + "\n"		)
             index += 1

     return vocab_file, merge_file




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




 def 				_snake_case (						self      ,  _lowerCAmelCase      ,  _lowerCAmelCase = None      ,  _lowerCAmelCase = False		)     ->				List[int]:
     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 				_snake_case (						self      ,  _lowerCAmelCase      ,  _lowerCAmelCase = None		)     ->				List[int]:
     _lowerCAmelCase						      =   [self.sep_token_id]
     _lowerCAmelCase						      =   [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 				_snake_case (						self      ,  _lowerCAmelCase      ,  _lowerCAmelCase=False      ,  **_lowerCAmelCase		)     ->				Union[str, Any]:
     _lowerCAmelCase						      =   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()):
         _lowerCAmelCase						      =   " " + text
     return (text, kwargs)





 def 				_snake_case (						self      ,  _lowerCAmelCase      ,  _lowerCAmelCase = None      ,  _lowerCAmelCase = PaddingStrategy.DO_NOT_PAD      ,  _lowerCAmelCase = None      ,  _lowerCAmelCase = None      ,  )     ->				dict:
     _lowerCAmelCase						      =   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:
         _lowerCAmelCase						      =   "attention_mask" in self.model_input_names

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

         if needs_to_be_padded:
             _lowerCAmelCase						      =   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`
                 _lowerCAmelCase						      =   (
                     encoded_inputs["global_attention_mask"] + [-1] * difference
                 )
             elif self.padding_side == "left":
                 _lowerCAmelCase						      =   [-1] * difference + encoded_inputs[
                     "global_attention_mask"
                 ]
             else:
                 raise ValueError("Invalid padding strategy:" + str(self.padding_side		)		)

     return encoded_inputs









'''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


_SCREAMING_SNAKE_CASE									=				logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE									=				{
    "facebook/deit-base-distilled-patch16-224": (
        "https://huggingface.co/facebook/deit-base-patch16-224/resolve/main/config.json"
    ),
    # See all DeiT models at https://huggingface.co/models?filter=deit
}

class  lowerCAmelCase_		(		__magic_name__		):
 __lowerCamelCase    :				Optional[int]								=       "deit"




 def __init__(						self      ,  _lowerCAmelCase=768      ,  _lowerCAmelCase=12      ,  _lowerCAmelCase=12      ,  _lowerCAmelCase=3072      ,  _lowerCAmelCase="gelu"      ,  _lowerCAmelCase=0.0      ,  _lowerCAmelCase=0.0      ,  _lowerCAmelCase=0.02      ,  _lowerCAmelCase=1E-12      ,  _lowerCAmelCase=224      ,  _lowerCAmelCase=16      ,  _lowerCAmelCase=3      ,  _lowerCAmelCase=True      ,  _lowerCAmelCase=16      ,  **_lowerCAmelCase      ,  )     ->				Dict:
     super().__init__(**_lowerCAmelCase		)

     _lowerCAmelCase						      =   hidden_size
     _lowerCAmelCase						      =   num_hidden_layers
     _lowerCAmelCase						      =   num_attention_heads
     _lowerCAmelCase						      =   intermediate_size
     _lowerCAmelCase						      =   hidden_act
     _lowerCAmelCase						      =   hidden_dropout_prob
     _lowerCAmelCase						      =   attention_probs_dropout_prob
     _lowerCAmelCase						      =   initializer_range
     _lowerCAmelCase						      =   layer_norm_eps
     _lowerCAmelCase						      =   image_size
     _lowerCAmelCase						      =   patch_size
     _lowerCAmelCase						      =   num_channels
     _lowerCAmelCase						      =   qkv_bias
     _lowerCAmelCase						      =   encoder_stride







class  lowerCAmelCase_		(		__magic_name__		):
 __lowerCamelCase    :				List[str]								=       version.parse("1.11"		)




 @property
 def 				_snake_case (						self		)     ->				Mapping[str, Mapping[int, str]]:
     return OrderedDict(
         [
             ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
         ]		)





 @property
 def 				_snake_case (						self		)     ->				float:
     return 1E-4


