





"""simple docstring"""


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


lowerCamelCase__						= logging.get_logger(__name__)


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

lowerCamelCase__						= {
    "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"
        ),
    },
}

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




@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def        lowercase__     (       )       ->		Optional[Any]:




      """simple docstring"""

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




def        lowercase__     (       lowercase_      )       ->		Union[str, Any]:




      """simple docstring"""

      _UpperCamelCase   :						Tuple    =							set()
      _UpperCamelCase   :						str    =							word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)      )
            _UpperCamelCase   :						Dict    =							char
      return pairs



class   __SCREAMING_SNAKE_CASE     (    _UpperCamelCase ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__				:Optional[Any]						  =       VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__				:int						  =       PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__				:List[Any]						  =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__				:Optional[Any]						  =       ["input_ids", "attention_mask"]

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

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

  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							Optional[int]						)		->					Optional[Any]:
        return len(self.encoder						)

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

  def  __SCREAMING_SNAKE_CASE					(		self :							int       , __a :							List[Any]						)		->					Dict:
        if token in self.cache:
              return self.cache[token]
        _UpperCamelCase   :						List[str]    =							tuple(__a						)
        _UpperCamelCase   :						str    =							get_pairs(__a						)

        if not pairs:
              return token

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

  def  __SCREAMING_SNAKE_CASE					(		self :							int       , __a :							Any						)		->					Any:
        _UpperCamelCase   :						Dict    =							[]
        for token in re.findall(self.pat       , __a						):
              _UpperCamelCase   :						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(__a						).split(" "						)						)
        return bpe_tokens

  def  __SCREAMING_SNAKE_CASE					(		self :							int       , __a :							Optional[Any]						)		->					Union[str, Any]:
        return self.encoder.get(__a       , self.encoder.get(self.unk_token						)						)

  def  __SCREAMING_SNAKE_CASE					(		self :							Dict       , __a :							Union[str, Any]						)		->					Optional[Any]:
        return self.decoder.get(__a						)

  def  __SCREAMING_SNAKE_CASE					(		self :							Optional[int]       , __a :							List[Any]						)		->					int:
        _UpperCamelCase   :						List[str]    =							"".join(__a						)
        _UpperCamelCase   :						Any    =							bytearray([self.byte_decoder[c] for c in text]						).decode("utf-8"       , errors=self.errors						)
        return text

  def  __SCREAMING_SNAKE_CASE					(		self :							Tuple       , __a :							str       , __a :							Optional[str] = None						)		->					Tuple[str]:
        if not os.path.isdir(__a						):
              logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''						)
              return
        _UpperCamelCase   :						List[Any]    =							os.path.join(
            __a       , (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)
        _UpperCamelCase   :						Any    =							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"						)

        _UpperCamelCase   :						Dict    =							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!"						)
                          _UpperCamelCase   :						Tuple    =							token_index
                    writer.write(" ".join(__a						) + "\n"						)
                    index += 1

        return vocab_file, merge_file

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

  def  __SCREAMING_SNAKE_CASE					(		self :							int       , __a :							List[int]       , __a :							Optional[List[int]] = None       , __a :							bool = False						)		->					List[int]:
        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  __SCREAMING_SNAKE_CASE					(		self :							int       , __a :							List[int]       , __a :							Optional[List[int]] = None						)		->					List[int]:
        _UpperCamelCase   :						int    =							[self.sep_token_id]
        _UpperCamelCase   :						str    =							[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  __SCREAMING_SNAKE_CASE					(		self :							List[Any]       , __a :							List[str]       , __a :							Any=False       , **__a :							str						)		->					Optional[Any]:
        _UpperCamelCase   :						Dict    =							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()):
              _UpperCamelCase   :						List[str]    =							" " + text
        return (text, kwargs)







"""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


lowerCamelCase__						= logging.get_logger(__name__)

lowerCamelCase__						= {
    "google/mobilenet_v1_1.0_224": "https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json",
    "google/mobilenet_v1_0.75_192": "https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json",
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}



class   __SCREAMING_SNAKE_CASE     (    _UpperCamelCase ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__				:int						  =       "mobilenet_v1"

  def __init__(		self :							Optional[int]       , __a :							List[str]=3       , __a :							Union[str, Any]=224       , __a :							Tuple=1.0       , __a :							List[Any]=8       , __a :							Union[str, Any]="relu6"       , __a :							Dict=True       , __a :							Tuple=0.9_99       , __a :							Dict=0.02       , __a :							Any=0.0_01       , **__a :							Any       , )		->					int:
        super().__init__(**__a						)

        if depth_multiplier <= 0:
              raise ValueError("depth_multiplier must be greater than zero."						)

        _UpperCamelCase   :						Any    =							num_channels
        _UpperCamelCase   :						Optional[Any]    =							image_size
        _UpperCamelCase   :						Optional[Any]    =							depth_multiplier
        _UpperCamelCase   :						int    =							min_depth
        _UpperCamelCase   :						List[str]    =							hidden_act
        _UpperCamelCase   :						Union[str, Any]    =							tf_padding
        _UpperCamelCase   :						int    =							classifier_dropout_prob
        _UpperCamelCase   :						Optional[int]    =							initializer_range
        _UpperCamelCase   :						Union[str, Any]    =							layer_norm_eps





class   __SCREAMING_SNAKE_CASE     (    _UpperCamelCase ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__				:List[Any]						  =       version.parse("1.11" )

  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							List[str]						)		->					Mapping[str, Mapping[int, str]]:
        return OrderedDict([("pixel_values", {0: "batch"})]						)

  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							Optional[int]						)		->					Mapping[str, Mapping[int, str]]:
        if self.task == "image-classification":
              return OrderedDict([("logits", {0: "batch"})]						)
        else:
              return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]						)


  @property
  def  __SCREAMING_SNAKE_CASE					(		self :							Tuple						)		->					float:
        return 1e-4
