


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


A   :					str	=      {
    """configuration_poolformer""": [
        """POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """PoolFormerConfig""",
        """PoolFormerOnnxConfig""",
    ]
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A   :					str	=      ["""PoolFormerFeatureExtractor"""]
    A   :					List[str]	=      ["""PoolFormerImageProcessor"""]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A   :					List[Any]	=      [
        """POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """PoolFormerForImageClassification""",
        """PoolFormerModel""",
        """PoolFormerPreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_poolformer import (
        POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
        PoolFormerConfig,
        PoolFormerOnnxConfig,
    )

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_poolformer import PoolFormerFeatureExtractor
        from .image_processing_poolformer import PoolFormerImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_poolformer import (
            POOLFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            PoolFormerForImageClassification,
            PoolFormerModel,
            PoolFormerPreTrainedModel,
        )


else:
    import sys

    A   :					Tuple	=      _LazyModule(__name__, globals()["__file__"], _import_structure)





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   :					Tuple	=      logging.get_logger(__name__)


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

# See all LED models at https://huggingface.co/models?filter=LED
A   :					int	=      {
    "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   :					Union[str, Any]	=      {
    "allenai/led-base-16384": 16384,
}

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

      """simple docstring"""




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

def    lowercase_	(	_A    :					Any		):

      """simple docstring"""




      lowerCamelCase__	:       Union[str, Any]					=						set()
      lowerCamelCase__	:       Optional[int]					=						word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)		)
            lowerCamelCase__	:       Any					=						char
      return pairs







class     _lowercase				(							lowercase__):


       """simple docstring"""




       A__      		=    VOCAB_FILES_NAMES
       A__      		=    PRETRAINED_VOCAB_FILES_MAP
       A__      		=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       A__      		=    ["input_ids", "attention_mask"]





       def __init__(     self							:    str      ,   __lowerCamelCase							:    Optional[int]      ,   __lowerCamelCase							:    Dict      ,   __lowerCamelCase							:    Union[str, Any]="replace"      ,   __lowerCamelCase							:    Optional[Any]="<s>"      ,   __lowerCamelCase							:    int="</s>"      ,   __lowerCamelCase							:    str="</s>"      ,   __lowerCamelCase							:    List[str]="<s>"      ,   __lowerCamelCase							:    Optional[int]="<unk>"      ,   __lowerCamelCase							:    List[str]="<pad>"      ,   __lowerCamelCase							:    Union[str, Any]="<mask>"      ,   __lowerCamelCase							:    Tuple=False      ,   **__lowerCamelCase							:    Optional[Any]      ,   ):


             '''simple docstring'''



             lowerCamelCase__	:       Union[str, Any]					=						AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase      ,   __lowerCamelCase ) else bos_token
             lowerCamelCase__	:       Optional[int]					=						AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase      ,   __lowerCamelCase ) else eos_token
             lowerCamelCase__	:       str					=						AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase      ,   __lowerCamelCase ) else sep_token
             lowerCamelCase__	:       int					=						AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase      ,   __lowerCamelCase ) else cls_token
             lowerCamelCase__	:       Optional[Any]					=						AddedToken(__lowerCamelCase      ,   lstrip=__lowerCamelCase      ,   rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase      ,   __lowerCamelCase ) else unk_token
             lowerCamelCase__	:       Tuple					=						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__	:       int					=						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__	:       Union[str, Any]					=						json.load(__lowerCamelCase )
             lowerCamelCase__	:       List[str]					=						{v: k for k, v in self.encoder.items()}
             lowerCamelCase__	:       Union[str, Any]					=						errors  # how to handle errors in decoding
             lowerCamelCase__	:       List[Any]					=						bytes_to_unicode()
             lowerCamelCase__	:       Optional[Any]					=						{v: k for k, v in self.byte_encoder.items()}
             with open(__lowerCamelCase      ,   encoding="utf-8" ) as merges_handle:
                   lowerCamelCase__	:       List[Any]					=						merges_handle.read().split("\n" )[1:-1]
             lowerCamelCase__	:       str					=						[tuple(merge.split() ) for merge in bpe_merges]
             lowerCamelCase__	:       Optional[Any]					=						dict(zip(__lowerCamelCase      ,   range(len(__lowerCamelCase ) ) ) )
             lowerCamelCase__	:       List[Any]					=						{}
             lowerCamelCase__	:       Dict					=						add_prefix_space

             # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
             lowerCamelCase__	:       List[str]					=						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 		lowerCAmelCase  (     self							:    Union[str, Any] ):


             '''simple docstring'''



             return len(self.encoder )





       def 		lowerCAmelCase  (     self							:    Union[str, Any] ):


             '''simple docstring'''



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





       def 		lowerCAmelCase  (     self							:    Tuple      ,   __lowerCamelCase							:    Dict ):


             '''simple docstring'''



             if token in self.cache:
                   return self.cache[token]
             lowerCamelCase__	:       Union[str, Any]					=						tuple(__lowerCamelCase )
             lowerCamelCase__	:       Tuple					=						get_pairs(__lowerCamelCase )

             if not pairs:
                   return token

             while True:
                   lowerCamelCase__	:       str					=						min(__lowerCamelCase      ,   key=lambda __lowerCamelCase : self.bpe_ranks.get(__lowerCamelCase      ,   float("inf" ) ) )
                   if bigram not in self.bpe_ranks:
                         break
                   lowerCamelCase__					,     lowerCamelCase__	:       Union[str, Any]					=						bigram
                   lowerCamelCase__	:       int					=						[]
                   lowerCamelCase__	:       int					=						0
                   while i < len(__lowerCamelCase ):
                         try:
                               lowerCamelCase__	:       Union[str, Any]					=						word.index(__lowerCamelCase      ,   __lowerCamelCase )
                         except ValueError:
                               new_word.extend(word[i:] )
                               break
                         else:
                               new_word.extend(word[i:j] )
                               lowerCamelCase__	:       List[str]					=						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__	:       Dict					=						tuple(__lowerCamelCase )
                   lowerCamelCase__	:       str					=						new_word
                   if len(__lowerCamelCase ) == 1:
                         break
                   else:
                         lowerCamelCase__	:       List[str]					=						get_pairs(__lowerCamelCase )
             lowerCamelCase__	:       Optional[int]					=						" ".join(__lowerCamelCase )
             lowerCamelCase__	:       Dict					=						word
             return word





       def 		lowerCAmelCase  (     self							:    Tuple      ,   __lowerCamelCase							:    List[Any] ):


             '''simple docstring'''



             lowerCamelCase__	:       List[Any]					=						[]
             for token in re.findall(self.pat      ,   __lowerCamelCase ):
                   lowerCamelCase__	:       Union[str, Any]					=						"".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 		lowerCAmelCase  (     self							:    Any      ,   __lowerCamelCase							:    int ):


             '''simple docstring'''



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





       def 		lowerCAmelCase  (     self							:    List[Any]      ,   __lowerCamelCase							:    Union[str, Any] ):


             '''simple docstring'''



             return self.decoder.get(__lowerCamelCase )





       def 		lowerCAmelCase  (     self							:    Union[str, Any]      ,   __lowerCamelCase							:    Tuple ):


             '''simple docstring'''



             lowerCamelCase__	:       Union[str, Any]					=						"".join(__lowerCamelCase )
             lowerCamelCase__	:       Dict					=						bytearray([self.byte_decoder[c] for c in text] ).decode("utf-8"      ,   errors=self.errors )
             return text





       def 		lowerCAmelCase  (     self							:    Optional[int]      ,   __lowerCamelCase							:    str      ,   __lowerCamelCase							:    Optional[str] = None ):


             '''simple docstring'''



             if not os.path.isdir(__lowerCamelCase ):
                   logger.error(f"Vocabulary path ({save_directory}) should be a directory" )
                   return
             lowerCamelCase__	:       List[Any]					=						os.path.join(
                 __lowerCamelCase      ,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )
             lowerCamelCase__	:       Union[str, Any]					=						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__	:       Tuple					=						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__	:       List[Any]					=						token_index
                         writer.write(" ".join(__lowerCamelCase ) + "\n" )
                         index += 1

             return vocab_file, merge_file





       def 		lowerCAmelCase  (     self							:    int      ,   __lowerCamelCase							:    List[int]      ,   __lowerCamelCase							:    Optional[List[int]] = None ):


             '''simple docstring'''



             if token_ids_a is None:
                   return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
             lowerCamelCase__	:       List[str]					=						[self.cls_token_id]
             lowerCamelCase__	:       int					=						[self.sep_token_id]
             return cls + token_ids_a + sep + sep + token_ids_a + sep





       def 		lowerCAmelCase  (     self							:    Tuple      ,   __lowerCamelCase							:    List[int]      ,   __lowerCamelCase							:    Optional[List[int]] = None      ,   __lowerCamelCase							:    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 		lowerCAmelCase  (     self							:    List[Any]      ,   __lowerCamelCase							:    List[int]      ,   __lowerCamelCase							:    Optional[List[int]] = None ):


             '''simple docstring'''



             lowerCamelCase__	:       Any					=						[self.sep_token_id]
             lowerCamelCase__	:       Union[str, Any]					=						[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							:    List[str]      ,   __lowerCamelCase							:    int      ,   __lowerCamelCase							:    Dict=False      ,   **__lowerCamelCase							:    List[str] ):


             '''simple docstring'''



             lowerCamelCase__	:       Union[str, Any]					=						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__	:       Dict					=						" " + text
             return (text, kwargs)





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


             '''simple docstring'''



             lowerCamelCase__	:       str					=						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__	:       str					=						"attention_mask" in self.model_input_names

             if return_attention_mask and "global_attention_mask" in encoded_inputs:
                   lowerCamelCase__	:       Optional[int]					=						encoded_inputs[self.model_input_names[0]]
                   # `global_attention_mask` need to have the same length as other (sequential) inputs.
                   lowerCamelCase__	:       Union[str, Any]					=						len(encoded_inputs["global_attention_mask"] ) != len(__lowerCamelCase )

                   if needs_to_be_padded:
                         lowerCamelCase__	:       Dict					=						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__	:       Optional[int]					=						(
                                   encoded_inputs["global_attention_mask"] + [-1] * difference
                               )
                         elif self.padding_side == "left":
                               lowerCamelCase__	:       Union[str, Any]					=						[-1] * difference + encoded_inputs[
                                   "global_attention_mask"
                               ]
                         else:
                               raise ValueError("Invalid padding strategy:" + str(self.padding_side ) )

             return encoded_inputs


