



from queue import Queue
from typing import TYPE_CHECKING, Optional


if TYPE_CHECKING:
							from ..models.auto import AutoTokenizer


class   __lowerCAmelCase  :
					"""simple docstring"""






					def      _a				(  self       :							Dict					,       _snake_case       :							List[str]       ):






								"""simple docstring"""


								raise NotImplementedError()



					def      _a				(  self       :							Union[str, Any]       ):






								"""simple docstring"""


								raise NotImplementedError()







class   __lowerCAmelCase  (		UpperCAmelCase_   ):
					"""simple docstring"""






					def __init__(  self       :							List[str]					,       _snake_case       :							"AutoTokenizer"					,       _snake_case       :							bool = False					,       **_snake_case       :							Tuple       ):






								"""simple docstring"""


								A__	  =     tokenizer
								A__	  =     skip_prompt
								A__	  =     decode_kwargs

								# variables used in the streaming process
								A__	  =     []
								A__	  =     0
								A__	  =     True



					def      _a				(  self       :							Optional[int]					,       _snake_case       :							str       ):






								"""simple docstring"""


								if len(value.shape       ) > 1 and value.shape[0] > 1:
											raise ValueError('TextStreamer only supports batch size 1'       )
								elif len(value.shape       ) > 1:
											A__	  =     value[0]

								if self.skip_prompt and self.next_tokens_are_prompt:
											A__	  =     False
											return

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

								# After the symbol for a new line, we flush the cache.
								if text.endswith('\n'       ):
											A__	  =     text[self.print_len :]
											A__	  =     []
											A__	  =     0
								# If the last token is a CJK character, we print the characters.
								elif len(_snake_case       ) > 0 and self._is_chinese_char(ord(text[-1]       )       ):
											A__	  =     text[self.print_len :]
											self.print_len += len(_snake_case       )
								# 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:
											A__	  =     text[self.print_len : text.rfind(' '       ) + 1]
											self.print_len += len(_snake_case       )

								self.on_finalized_text(_snake_case       )



					def      _a				(  self       :							Optional[int]       ):






								"""simple docstring"""


								if len(self.token_cache       ) > 0:
											A__	  =     self.tokenizer.decode(self.token_cache					,       **self.decode_kwargs       )
											A__	  =     text[self.print_len :]
											A__	  =     []
											A__	  =     0
								else:
											A__	  =     ''

								A__	  =     True
								self.on_finalized_text(_snake_case					,       stream_end=_snake_case       )



					def      _a				(  self       :							Optional[int]					,       _snake_case       :							str					,       _snake_case       :							bool = False       ):






								"""simple docstring"""


								print(_snake_case					,       flush=_snake_case					,       end='' if not stream_end else None       )



					def      _a				(  self       :							Any					,       _snake_case       :							str       ):






								"""simple docstring"""


								if (
								    (cp >= 0x4E00 and cp <= 0x9FFF)
								    or (cp >= 0x3400 and cp <= 0x4DBF)  #
								    or (cp >= 0x20000 and cp <= 0x2A6DF)  #
								    or (cp >= 0x2A700 and cp <= 0x2B73F)  #
								    or (cp >= 0x2B740 and cp <= 0x2B81F)  #
								    or (cp >= 0x2B820 and cp <= 0x2CEAF)  #
								    or (cp >= 0xF900 and cp <= 0xFAFF)
								    or (cp >= 0x2F800 and cp <= 0x2FA1F)  #
								):  #
											return True

								return False







class   __lowerCAmelCase  (		UpperCAmelCase_   ):
					"""simple docstring"""






					def __init__(  self       :							Dict					,       _snake_case       :							"AutoTokenizer"					,       _snake_case       :							bool = False					,       _snake_case       :							Optional[float] = None					,       **_snake_case       :							str       ):






								"""simple docstring"""


								super().__init__(_snake_case					,       _snake_case					,       **_snake_case       )
								A__	  =     Queue()
								A__	  =     None
								A__	  =     timeout



					def      _a				(  self       :							Optional[int]					,       _snake_case       :							str					,       _snake_case       :							bool = False       ):






								"""simple docstring"""


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



					def __iter__(  self       :							Optional[int]       ):






								"""simple docstring"""


								return self



					def      _a				(  self       :							Dict       ):






								"""simple docstring"""


								A__	  =     self.text_queue.get(timeout=self.timeout       )
								if value == self.stop_signal:
											raise StopIteration()
								else:
											return value









import numpy as np
import skfuzzy as fuzz

if __name__ == "__main__":
							# Create universe of discourse in Python using linspace ()
							SCREAMING_SNAKE_CASE__   			=   np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False)

							# Create two fuzzy sets by defining any membership function
							# (trapmf(), gbellmf(), gaussmf(), etc).
							SCREAMING_SNAKE_CASE__   			=   [0, 2_5, 5_0]
							SCREAMING_SNAKE_CASE__   			=   [2_5, 5_0, 7_5]
							SCREAMING_SNAKE_CASE__   			=   fuzz.membership.trimf(X, abca)
							SCREAMING_SNAKE_CASE__   			=   fuzz.membership.trimf(X, abca)

							# Compute the different operations using inbuilt functions.
							SCREAMING_SNAKE_CASE__   			=   np.ones(7_5)
							SCREAMING_SNAKE_CASE__   			=   np.zeros((7_5,))
							# 1. Union = max(µA(x), µB(x))
							SCREAMING_SNAKE_CASE__   			=   fuzz.fuzzy_or(X, young, X, middle_aged)[1]
							# 2. Intersection = min(µA(x), µB(x))
							SCREAMING_SNAKE_CASE__   			=   fuzz.fuzzy_and(X, young, X, middle_aged)[1]
							# 3. Complement (A) = (1- min(µA(x))
							SCREAMING_SNAKE_CASE__   			=   fuzz.fuzzy_not(young)
							# 4. Difference (A/B) = min(µA(x),(1- µB(x)))
							SCREAMING_SNAKE_CASE__   			=   fuzz.fuzzy_and(X, young, X, fuzz.fuzzy_not(middle_aged)[1])[1]
							# 5. Algebraic Sum = [µA(x) + µB(x) – (µA(x) * µB(x))]
							SCREAMING_SNAKE_CASE__   			=   young + middle_aged - (young * middle_aged)
							# 6. Algebraic Product = (µA(x) * µB(x))
							SCREAMING_SNAKE_CASE__   			=   young * middle_aged
							# 7. Bounded Sum = min[1,(µA(x), µB(x))]
							SCREAMING_SNAKE_CASE__   			=   fuzz.fuzzy_and(X, one, X, young + middle_aged)[1]
							# 8. Bounded difference = min[0,(µA(x), µB(x))]
							SCREAMING_SNAKE_CASE__   			=   fuzz.fuzzy_or(X, zero, X, young - middle_aged)[1]

							# max-min composition
							# max-product composition

							# Plot each set A, set B and each operation result using plot() and subplot().
							from matplotlib import pyplot as plt

							plt.figure()

							plt.subplot(4, 3, 1)
							plt.plot(X, young)
							plt.title('''Young''')
							plt.grid(True)

							plt.subplot(4, 3, 2)
							plt.plot(X, middle_aged)
							plt.title('''Middle aged''')
							plt.grid(True)

							plt.subplot(4, 3, 3)
							plt.plot(X, union)
							plt.title('''union''')
							plt.grid(True)

							plt.subplot(4, 3, 4)
							plt.plot(X, intersection)
							plt.title('''intersection''')
							plt.grid(True)

							plt.subplot(4, 3, 5)
							plt.plot(X, complement_a)
							plt.title('''complement_a''')
							plt.grid(True)

							plt.subplot(4, 3, 6)
							plt.plot(X, difference)
							plt.title('''difference a/b''')
							plt.grid(True)

							plt.subplot(4, 3, 7)
							plt.plot(X, alg_sum)
							plt.title('''alg_sum''')
							plt.grid(True)

							plt.subplot(4, 3, 8)
							plt.plot(X, alg_product)
							plt.title('''alg_product''')
							plt.grid(True)

							plt.subplot(4, 3, 9)
							plt.plot(X, bdd_sum)
							plt.title('''bdd_sum''')
							plt.grid(True)

							plt.subplot(4, 3, 1_0)
							plt.plot(X, bdd_difference)
							plt.title('''bdd_difference''')
							plt.grid(True)

							plt.subplots_adjust(hspace=0.5)
							plt.show()




