
from __future__ import annotations

import math
from collections import Counter
from string import ascii_lowercase







def     A__   (  lowerCamelCase  )					->		None:
				UpperCamelCase_,				UpperCamelCase_:							Optional[int]		=  analyze_text(lowerCamelCase  )
				UpperCamelCase_:							Dict		=  list(""" """ + ascii_lowercase  )
				# what is our total sum of probabilities.
				UpperCamelCase_:							Dict		=  sum(single_char_strings.values()  )

				# one length string
				UpperCamelCase_:							Dict		=  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_:							Optional[Any]		=  single_char_strings[ch]
												UpperCamelCase_:							Tuple		=  my_str / all_sum
												my_fir_sum += prob * math.loga(lowerCamelCase  )  # entropy formula.

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

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

    # 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     A__   (  lowerCamelCase  )					->		tuple[dict, dict]:
				UpperCamelCase_:							Union[str, Any]		=  Counter()  # type: ignore
				UpperCamelCase_:							int		=  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(lowerCamelCase  ) - 1  ):
								single_char_strings[text[i]] += 1
								two_char_strings[text[i : i + 2]] += 1
				return single_char_strings, two_char_strings







def     A__   (  )					->		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()








from typing import TYPE_CHECKING

from ...utils import _LazyModule


lowerCamelCase_  :	Dict 				=					{"""tokenization_byt5""": ["""ByT5Tokenizer"""]}


if TYPE_CHECKING:
							from .tokenization_byta import ByTaTokenizer
else:
							import sys

							lowerCamelCase_  :	Any 				=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






