





'''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


UpperCAmelCase					:		List[str]		=							logging.get_logger(__name__)


UpperCAmelCase					:		List[str]		=							{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all LED models at https://huggingface.co/models?filter=LED
UpperCAmelCase					:		Tuple		=							{
    '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',
    },
}

UpperCAmelCase					:		Any		=							{
    'allenai/led-base-16384': 1_6_3_8_4,
}




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





      """simple docstring"""



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




def    _a    (							lowerCAmelCase_	):





      """simple docstring"""



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





class lowerCamelCase						(a__					):
  _lowercase  :	Optional[Any]       					=				VOCAB_FILES_NAMES
  _lowercase  :	int       					=				PRETRAINED_VOCAB_FILES_MAP
  _lowercase  :	int       					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  _lowercase  :	Optional[int]       					=				["""input_ids""", """attention_mask"""]







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






        """simple docstring"""





        _snake_case		:	Tuple					     =     AddedToken(lowercase__     ,     lstrip=lowercase__     ,     rstrip=lowercase__		) if isinstance(lowercase__     ,     lowercase__		) else bos_token
        _snake_case		:	Dict					     =     AddedToken(lowercase__     ,     lstrip=lowercase__     ,     rstrip=lowercase__		) if isinstance(lowercase__     ,     lowercase__		) else eos_token
        _snake_case		:	Union[str, Any]					     =     AddedToken(lowercase__     ,     lstrip=lowercase__     ,     rstrip=lowercase__		) if isinstance(lowercase__     ,     lowercase__		) else sep_token
        _snake_case		:	Optional[int]					     =     AddedToken(lowercase__     ,     lstrip=lowercase__     ,     rstrip=lowercase__		) if isinstance(lowercase__     ,     lowercase__		) else cls_token
        _snake_case		:	Tuple					     =     AddedToken(lowercase__     ,     lstrip=lowercase__     ,     rstrip=lowercase__		) if isinstance(lowercase__     ,     lowercase__		) else unk_token
        _snake_case		:	Any					     =     AddedToken(lowercase__     ,     lstrip=lowercase__     ,     rstrip=lowercase__		) if isinstance(lowercase__     ,     lowercase__		) else pad_token

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

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

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

        # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
        _snake_case		:	Optional[int]					     =     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 				UpperCAmelCase_				(		self		)		->						Optional[int]:






        """simple docstring"""





        return len(self.encoder		)







  def 				UpperCAmelCase_				(		self		)		->						Any:






        """simple docstring"""





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







  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						List[Any]:






        """simple docstring"""





        if token in self.cache:
              return self.cache[token]
        _snake_case		:	Optional[int]					     =     tuple(lowercase__		)
        _snake_case		:	List[str]					     =     get_pairs(lowercase__		)

        if not pairs:
              return token

        while True:
              _snake_case		:	Dict					     =     min(lowercase__     ,     key=lambda lowercase__		: self.bpe_ranks.get(lowercase__     ,     float('''inf'''		)		)		)
              if bigram not in self.bpe_ranks:
                    break
              _snake_case     ,							_snake_case		:	Any					     =     bigram
              _snake_case		:	Union[str, Any]					     =     []
              _snake_case		:	Tuple					     =     0
              while i < len(lowercase__		):
                    try:
                          _snake_case		:	Union[str, Any]					     =     word.index(lowercase__     ,     lowercase__		)
                    except ValueError:
                          new_word.extend(word[i:]		)
                          break
                    else:
                          new_word.extend(word[i:j]		)
                          _snake_case		:	Union[str, Any]					     =     j

                    if word[i] == first and i < len(lowercase__		) - 1 and word[i + 1] == second:
                          new_word.append(first + second		)
                          i += 2
                    else:
                          new_word.append(word[i]		)
                          i += 1
              _snake_case		:	str					     =     tuple(lowercase__		)
              _snake_case		:	Any					     =     new_word
              if len(lowercase__		) == 1:
                    break
              else:
                    _snake_case		:	str					     =     get_pairs(lowercase__		)
        _snake_case		:	Union[str, Any]					     =     ''' '''.join(lowercase__		)
        _snake_case		:	Optional[int]					     =     word
        return word







  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						Tuple:






        """simple docstring"""





        _snake_case		:	List[str]					     =     []
        for token in re.findall(self.pat     ,     lowercase__		):
              _snake_case		:	Optional[int]					     =     ''''''.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(lowercase__		).split(''' '''		)		)
        return bpe_tokens







  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						List[str]:






        """simple docstring"""





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







  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						Tuple:






        """simple docstring"""





        return self.decoder.get(lowercase__		)







  def 				UpperCAmelCase_				(		self     ,     lowercase__		)		->						Optional[Any]:






        """simple docstring"""





        _snake_case		:	Any					     =     ''''''.join(lowercase__		)
        _snake_case		:	List[Any]					     =     bytearray([self.byte_decoder[c] for c in text]		).decode('''utf-8'''     ,     errors=self.errors		)
        return text







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = None		)		->						Tuple[str]:






        """simple docstring"""





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

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

        _snake_case		:	Dict					     =     0
        with open(lowercase__     ,     '''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!'''		)
                          _snake_case		:	Optional[Any]					     =     token_index
                    writer.write(''' '''.join(lowercase__		) + '''\n'''		)
                    index += 1

        return vocab_file, merge_file







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = None		)		->						List[int]:






        """simple docstring"""





        if token_ids_a is None:
              return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        _snake_case		:	str					     =     [self.cls_token_id]
        _snake_case		:	Tuple					     =     [self.sep_token_id]
        return cls + token_ids_a + sep + sep + token_ids_a + sep







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = None     ,     lowercase__ = False		)		->						List[int]:






        """simple docstring"""





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

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







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = None		)		->						List[int]:






        """simple docstring"""





        _snake_case		:	Optional[Any]					     =     [self.sep_token_id]
        _snake_case		:	int					     =     [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 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__=False     ,     **lowercase__		)		->						List[Any]:






        """simple docstring"""





        _snake_case		:	Union[str, Any]					     =     kwargs.pop('''add_prefix_space'''     ,     self.add_prefix_space		)
        if (is_split_into_words or add_prefix_space) and (len(lowercase__		) > 0 and not text[0].isspace()):
              _snake_case		:	Dict					     =     ''' ''' + text
        return (text, kwargs)







  def 				UpperCAmelCase_				(		self     ,     lowercase__     ,     lowercase__ = None     ,     lowercase__ = PaddingStrategy.DO_NOT_PAD     ,     lowercase__ = None     ,     lowercase__ = None     ,     )		->						dict:






        """simple docstring"""





        _snake_case		:	int					     =     super()._pad(
            encoded_inputs=lowercase__     ,     max_length=lowercase__     ,     padding_strategy=lowercase__     ,     pad_to_multiple_of=lowercase__     ,     return_attention_mask=lowercase__     ,     )

        # Load from model defaults
        if return_attention_mask is None:
              _snake_case		:	Optional[Any]					     =     '''attention_mask''' in self.model_input_names

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

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

        return encoded_inputs









'''simple docstring'''

from random import randint
from tempfile import TemporaryFile

import numpy as np




def    _a    (							lowerCAmelCase_			,      lowerCAmelCase_			,      lowerCAmelCase_	):





      """simple docstring"""



      _snake_case		:	List[Any]					     =     0
      if start < end:
            _snake_case		:	List[Any]					     =     randint(lowerCAmelCase_			,      lowerCAmelCase_	)
            _snake_case		:	Any					     =     a[end]
            _snake_case		:	List[str]					     =     a[pivot]
            _snake_case		:	Optional[int]					     =     temp

            _snake_case     ,							_snake_case		:	List[Any]					     =     _in_place_partition(lowerCAmelCase_			,      lowerCAmelCase_			,      lowerCAmelCase_	)
            count += _in_place_quick_sort(lowerCAmelCase_			,      lowerCAmelCase_			,      p - 1	)
            count += _in_place_quick_sort(lowerCAmelCase_			,      p + 1			,      lowerCAmelCase_	)
      return count




def    _a    (							lowerCAmelCase_			,      lowerCAmelCase_			,      lowerCAmelCase_	):





      """simple docstring"""



      _snake_case		:	Optional[Any]					     =     0
      _snake_case		:	Optional[int]					     =     randint(lowerCAmelCase_			,      lowerCAmelCase_	)
      _snake_case		:	Tuple					     =     a[end]
      _snake_case		:	Optional[Any]					     =     a[pivot]
      _snake_case		:	Union[str, Any]					     =     temp
      _snake_case		:	Union[str, Any]					     =     start - 1
      for index in range(lowerCAmelCase_			,      lowerCAmelCase_	):
            count += 1
            if a[index] < a[end]:  # check if current val is less than pivot value
                  _snake_case		:	Optional[int]					     =     new_pivot_index + 1
                  _snake_case		:	Optional[Any]					     =     a[new_pivot_index]
                  _snake_case		:	Tuple					     =     a[index]
                  _snake_case		:	str					     =     temp

      _snake_case		:	Any					     =     a[new_pivot_index + 1]
      _snake_case		:	str					     =     a[end]
      _snake_case		:	Optional[int]					     =     temp
      return new_pivot_index + 1, count


UpperCAmelCase					:		Dict		=							TemporaryFile()
UpperCAmelCase					:		Dict		=							1_0_0  # 1000 elements are to be sorted


UpperCAmelCase,       UpperCAmelCase					:		str		=							0, 1  # mean and standard deviation
UpperCAmelCase					:		Optional[Any]		=							np.random.normal(mu, sigma, p)
np.save(outfile, X)
print('The array is')
print(X)


outfile.seek(0)  # using the same array
UpperCAmelCase					:		int		=							np.load(outfile)
UpperCAmelCase					:		Optional[int]		=							len(M) - 1
UpperCAmelCase					:		str		=							_in_place_quick_sort(M, 0, r)

print(
    'No of Comparisons for 100 elements selected from a standard normal distribution'
    'is :'
)
print(z)


