



from queue import Queue
from typing import TYPE_CHECKING, Optional


if TYPE_CHECKING:
				from ..models.auto import AutoTokenizer
class 				__A					:





			def        _snake_case    (self							,    __magic_name__				):
						raise NotImplementedError()





			def        _snake_case    (self				):
						raise NotImplementedError()







class 				__A					( A_      ):





			def __init__(self							,    __magic_name__							,    __magic_name__ = False							,    **__magic_name__				):
						lowerCamelCase__ :      Dict								=		tokenizer
						lowerCamelCase__ :      Any								=		skip_prompt
						lowerCamelCase__ :      Any								=		decode_kwargs

						# variables used in the streaming process
						lowerCamelCase__ :      Optional[int]								=		[]
						lowerCamelCase__ :      List[Any]								=		0
						lowerCamelCase__ :      Union[str, Any]								=		True





			def        _snake_case    (self							,    __magic_name__				):
						if len(value.shape				) > 1 and value.shape[0] > 1:
									raise ValueError("""TextStreamer only supports batch size 1"""				)
						elif len(value.shape				) > 1:
									lowerCamelCase__ :      Any								=		value[0]

						if self.skip_prompt and self.next_tokens_are_prompt:
									lowerCamelCase__ :      Optional[Any]								=		False
									return

						# Add the new token to the cache and decodes the entire thing.
						self.token_cache.extend(value.tolist()				)
						lowerCamelCase__ :      str								=		self.tokenizer.decode(self.token_cache							,    **self.decode_kwargs				)

						# After the symbol for a new line, we flush the cache.
						if text.endswith("""\n"""				):
									lowerCamelCase__ :      Tuple								=		text[self.print_len :]
									lowerCamelCase__ :      Tuple								=		[]
									lowerCamelCase__ :      int								=		0
						# If the last token is a CJK character, we print the characters.
						elif len(__magic_name__				) > 0 and self._is_chinese_char(ord(text[-1]				)				):
									lowerCamelCase__ :      Optional[int]								=		text[self.print_len :]
									self.print_len += len(__magic_name__				)
						# Otherwise, prints until the last space char (simple heuristic to avoid printing incomplete words,
						# which may change with the subsequent token -- there are probably smarter ways to do this!)
						else:
									lowerCamelCase__ :      Tuple								=		text[self.print_len : text.rfind(""" """				) + 1]
									self.print_len += len(__magic_name__				)

						self.on_finalized_text(__magic_name__				)





			def        _snake_case    (self				):
						# Flush the cache, if it exists
						if len(self.token_cache				) > 0:
									lowerCamelCase__ :      Optional[int]								=		self.tokenizer.decode(self.token_cache							,    **self.decode_kwargs				)
									lowerCamelCase__ :      Dict								=		text[self.print_len :]
									lowerCamelCase__ :      List[str]								=		[]
									lowerCamelCase__ :      Optional[Any]								=		0
						else:
									lowerCamelCase__ :      List[Any]								=		""""""

						lowerCamelCase__ :      Dict								=		True
						self.on_finalized_text(__magic_name__							,    stream_end=__magic_name__				)





			def        _snake_case    (self							,    __magic_name__							,    __magic_name__ = False				):
						print(__magic_name__							,    flush=__magic_name__							,    end="""""" if not stream_end else None				)





			def        _snake_case    (self							,    __magic_name__				):
						# This defines a "chinese character" as anything in the CJK Unicode block:
						#   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
						#
						# Note that the CJK Unicode block is NOT all Japanese and Korean characters,
						# despite its name. The modern Korean Hangul alphabet is a different block,
						# as is Japanese Hiragana and Katakana. Those alphabets are used to write
						# space-separated words, so they are not treated specially and handled
						# like the all of the other languages.
						if (
						    (cp >= 0X4e_00 and cp <= 0X9f_ff)
						    or (cp >= 0X34_00 and cp <= 0X4d_bf)  #
						    or (cp >= 0X2_00_00 and cp <= 0X2_a6_df)  #
						    or (cp >= 0X2_a7_00 and cp <= 0X2_b7_3f)  #
						    or (cp >= 0X2_b7_40 and cp <= 0X2_b8_1f)  #
						    or (cp >= 0X2_b8_20 and cp <= 0X2_ce_af)  #
						    or (cp >= 0Xf9_00 and cp <= 0Xfa_ff)
						    or (cp >= 0X2_f8_00 and cp <= 0X2_fa_1f)  #
						):  #
									return True

						return False







class 				__A					( A_      ):





			def __init__(self							,    __magic_name__							,    __magic_name__ = False							,    __magic_name__ = None							,    **__magic_name__				):
						super().__init__(__magic_name__							,    __magic_name__							,    **__magic_name__				)
						lowerCamelCase__ :      Optional[Any]								=		Queue()
						lowerCamelCase__ :      Optional[int]								=		None
						lowerCamelCase__ :      Union[str, Any]								=		timeout





			def        _snake_case    (self							,    __magic_name__							,    __magic_name__ = False				):
						self.text_queue.put(__magic_name__							,    timeout=self.timeout				)
						if stream_end:
									self.text_queue.put(self.stop_signal							,    timeout=self.timeout				)





			def __iter__(self				):
						return self





			def        _snake_case    (self				):
						lowerCamelCase__ :      Optional[int]								=		self.text_queue.get(timeout=self.timeout				)
						if value == self.stop_signal:
									raise StopIteration()
						else:
									return value








from __future__ import annotations

import math
from collections import Counter
from string import ascii_lowercase






def      _A				(UpperCamelCase		:      str )  ->None:



			'''simple docstring'''







			lowerCamelCase__							,lowerCamelCase__ :      List[str]								=		analyze_text(UpperCamelCase )
			lowerCamelCase__ :      Any								=		list(""" """ + ascii_lowercase )
			# what is our total sum of probabilities.
			lowerCamelCase__ :      str								=		sum(single_char_strings.values() )

			# one length string
			lowerCamelCase__ :      Union[str, 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:
									lowerCamelCase__ :      List[Any]								=		single_char_strings[ch]
									lowerCamelCase__ :      List[str]								=		my_str / all_sum
									my_fir_sum += prob * math.loga(UpperCamelCase )  # entropy formula.

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

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

    # 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				(UpperCamelCase		:      str )  ->tuple[dict, dict]:



			'''simple docstring'''







			lowerCamelCase__ :      Optional[int]								=		Counter()  # type: ignore
			lowerCamelCase__ :      List[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(UpperCamelCase ) - 1 ):
						single_char_strings[text[i]] += 1
						two_char_strings[text[i : i + 2]] += 1
			return single_char_strings, two_char_strings






def      _A				()  ->List[str]:



			'''simple docstring'''







			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()



