



from __future__ import annotations

import math
from collections import Counter
from string import ascii_lowercase
def 						UpperCamelCase      (  snake_case__			:       str      )      ->	None:
   UpperCamelCase      ,	UpperCamelCase       :    Tuple		      =      analyze_text(snake_case__      )
   UpperCamelCase       :    Optional[Any]		      =      list(' ' + ascii_lowercase      )
   # what is our total sum of probabilities.
   UpperCamelCase       :    List[str]		      =      sum(single_char_strings.values()      )

   # one length string
   UpperCamelCase       :    Optional[Any]		      =      0
   # for each alpha we go in our dict and if it is in it we calculate entropy
   for ch in my_alphas:
      if ch in single_char_strings:
         UpperCamelCase       :    Tuple		      =      single_char_strings[ch]
         UpperCamelCase       :    Any		      =      my_str / all_sum
         my_fir_sum += prob * math.loga(snake_case__      )  # entropy formula.

    # print entropy
   print(F"""{round(-1 * my_fir_sum      ):.1f}"""      )

   # two len string
   UpperCamelCase       :    List[str]		      =      sum(two_char_strings.values()      )
   UpperCamelCase       :    Union[str, Any]		      =      0
   # for each alpha (two in size) calculate entropy.
   for cha in my_alphas:
      for cha in my_alphas:
         UpperCamelCase       :    List[Any]		      =      cha + cha
         if sequence in two_char_strings:
            UpperCamelCase       :    List[str]		      =      two_char_strings[sequence]
            UpperCamelCase       :    Dict		      =      int(snake_case__      ) / all_sum
            my_sec_sum += prob * math.loga(snake_case__      )

    # print second entropy
   print(F"""{round(-1 * my_sec_sum      ):.1f}"""      )

   # print the difference between them
   print(F"""{round((-1 * my_sec_sum) - (-1 * my_fir_sum)      ):.1f}"""      )
def 						UpperCamelCase      (  snake_case__			:       str      )      ->	tuple[dict, dict]:
   UpperCamelCase       :    List[str]		      =      Counter()  # type: ignore
   UpperCamelCase       :    Any		      =      Counter()  # type: ignore
   single_char_strings[text[-1]] += 1

   # first case when we have space at start.
   two_char_strings[" " + text[0]] += 1
   for i in range(0			,	len(snake_case__      ) - 1      ):
      single_char_strings[text[i]] += 1
      two_char_strings[text[i : i + 2]] += 1
   return single_char_strings, two_char_strings
def 						UpperCamelCase      (  )      ->	Optional[int]:
   import doctest

   doctest.testmod()
   # text = (
   #     "Had repulsive dashwoods suspicion sincerity but advantage now him. Remark "
   #     "easily garret nor nay. Civil those mrs enjoy shy fat merry. You greatest "
   #     "jointure saw horrible. He private he on be imagine suppose. Fertile "
   #     "beloved evident through no service elderly is. Blind there if every no so "
   #     "at. Own neglected you preferred way sincerity delivered his attempted. To "
   #     "of message cottage windows do besides against uncivil.  Delightful "
   #     "unreserved impossible few estimating men favourable see entreaties. She "
   #     "propriety immediate was improving. He or entrance humoured likewise "
   #     "moderate. Much nor game son say feel. Fat make met can must form into "
   #     "gate. Me we offending prevailed discovery. "
   # )

   # calculate_prob(text)


if __name__ == "__main__":
    main()









import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
   from .tokenization_fnet import FNetTokenizer
else:
   lowerCamelCase__					:  Optional[Any]      							=				None

lowerCamelCase__					:  List[str]      							=				logging.get_logger(__name__)
lowerCamelCase__					:  List[str]      							=				{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

lowerCamelCase__					:  List[str]      							=				{
    'vocab_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/spiece.model',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/spiece.model',
    },
    'tokenizer_file': {
        'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/tokenizer.json',
        'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/tokenizer.json',
    },
}

lowerCamelCase__					:  Optional[Any]      							=				{
    'google/fnet-base': 512,
    'google/fnet-large': 512,
}

lowerCamelCase__					:  List[Any]      							=				'▁'





class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE   ):


 '''simple docstring'''







 lowercase_							       =       VOCAB_FILES_NAMES
 lowercase_							       =       PRETRAINED_VOCAB_FILES_MAP
 lowercase_							       =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_							       =       ["input_ids", "token_type_ids"]
 lowercase_							       =       FNetTokenizer



 def __init__(				self    :						List[Any]							,							_lowerCAmelCase    :						Dict=None							,							_lowerCAmelCase    :						Dict=None							,							_lowerCAmelCase    :						List[str]=False							,							_lowerCAmelCase    :						Optional[Any]=True							,							_lowerCAmelCase    :						Tuple=True							,							_lowerCAmelCase    :						List[Any]="<unk>"							,							_lowerCAmelCase    :						Optional[Any]="[SEP]"							,							_lowerCAmelCase    :						Optional[Any]="<pad>"							,							_lowerCAmelCase    :						Optional[int]="[CLS]"							,							_lowerCAmelCase    :						Optional[Any]="[MASK]"							,							**_lowerCAmelCase    :						Any							,							):
       # Mask token behave like a normal word, i.e. include the space before it and
       # is included in the raw text, there should be a match in a non-normalized sentence.
       SCREAMING_SNAKE_CASE_      		=     (
           AddedToken(_lowerCAmelCase							,							lstrip=_lowerCAmelCase							,							rstrip=_lowerCAmelCase							,							normalized=_lowerCAmelCase		)
           if isinstance(_lowerCAmelCase							,							_lowerCAmelCase		)
           else mask_token
       )

       super().__init__(
           _lowerCAmelCase							,							tokenizer_file=_lowerCAmelCase							,							do_lower_case=_lowerCAmelCase							,							remove_space=_lowerCAmelCase							,							keep_accents=_lowerCAmelCase							,							unk_token=_lowerCAmelCase							,							sep_token=_lowerCAmelCase							,							pad_token=_lowerCAmelCase							,							cls_token=_lowerCAmelCase							,							mask_token=_lowerCAmelCase							,							**_lowerCAmelCase							,							)

       SCREAMING_SNAKE_CASE_      		=     do_lower_case
       SCREAMING_SNAKE_CASE_      		=     remove_space
       SCREAMING_SNAKE_CASE_      		=     keep_accents
       SCREAMING_SNAKE_CASE_      		=     vocab_file
       SCREAMING_SNAKE_CASE_      		=     False if not self.vocab_file else True



 def  lowerCAmelCase_    (				self    :						Any							,							_lowerCAmelCase    :						List[int]							,							_lowerCAmelCase    :						Optional[List[int]] = None		):
       SCREAMING_SNAKE_CASE_      		=     [self.sep_token_id]
       SCREAMING_SNAKE_CASE_      		=     [self.cls_token_id]
       if token_ids_a is None:
             return cls + token_ids_a + sep
       return cls + token_ids_a + sep + token_ids_a + sep



 def  lowerCAmelCase_    (				self    :						Optional[int]							,							_lowerCAmelCase    :						List[int]							,							_lowerCAmelCase    :						Optional[List[int]] = None		):
       SCREAMING_SNAKE_CASE_      		=     [self.sep_token_id]
       SCREAMING_SNAKE_CASE_      		=     [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		) * [0] + len(token_ids_a + sep		) * [1]




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

       if os.path.abspath(self.vocab_file		) != os.path.abspath(_lowerCAmelCase		):
             copyfile(self.vocab_file							,							_lowerCAmelCase		)

       return (out_vocab_file,)