



from queue import Queue
from typing import TYPE_CHECKING, Optional


if TYPE_CHECKING:
				from ..models.auto import AutoTokenizer

class 		UpperCAmelCase__			:




			'''simple docstring'''






			def  snake_case__     (   self							: str       ,       a_							: int ):
					'''simple docstring'''





					raise NotImplementedError()




			def  snake_case__     (   self							: Union[str, Any] ):
					'''simple docstring'''





					raise NotImplementedError()

class 		UpperCAmelCase__			(			__UpperCamelCase   ):




			'''simple docstring'''






			def __init__(   self							: Union[str, Any]       ,       a_							: "AutoTokenizer"       ,       a_							: bool = False       ,       **a_							: int ):
					'''simple docstring'''





					__UpperCAmelCase    :     Tuple													=	tokenizer
					__UpperCAmelCase    :     Union[str, Any]													=	skip_prompt
					__UpperCAmelCase    :     Optional[int]													=	decode_kwargs

					# variables used in the streaming process
					__UpperCAmelCase    :     List[Any]													=	[]
					__UpperCAmelCase    :     str													=	0
					__UpperCAmelCase    :     int													=	True




			def  snake_case__     (   self							: int       ,       a_							: Dict ):
					'''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:
							__UpperCAmelCase    :     Union[str, Any]													=	value[0]

					if self.skip_prompt and self.next_tokens_are_prompt:
							__UpperCAmelCase    :     Dict													=	False
							return

					# Add the new token to the cache and decodes the entire thing.
					self.token_cache.extend(value.tolist() )
					__UpperCAmelCase    :     Optional[int]													=	self.tokenizer.decode(self.token_cache       ,       **self.decode_kwargs )

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

					self.on_finalized_text(a_ )




			def  snake_case__     (   self							: Any ):
					'''simple docstring'''





					if len(self.token_cache ) > 0:
							__UpperCAmelCase    :     Optional[int]													=	self.tokenizer.decode(self.token_cache       ,       **self.decode_kwargs )
							__UpperCAmelCase    :     str													=	text[self.print_len :]
							__UpperCAmelCase    :     int													=	[]
							__UpperCAmelCase    :     Any													=	0
					else:
							__UpperCAmelCase    :     int													=	''''''

					__UpperCAmelCase    :     List[Any]													=	True
					self.on_finalized_text(a_       ,       stream_end=a_ )




			def  snake_case__     (   self							: Dict       ,       a_							: str       ,       a_							: bool = False ):
					'''simple docstring'''





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




			def  snake_case__     (   self							: str       ,       a_							: Any ):
					'''simple docstring'''





					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 		UpperCAmelCase__			(			__UpperCamelCase   ):




			'''simple docstring'''






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





					super().__init__(a_       ,       a_       ,       **a_ )
					__UpperCAmelCase    :     Dict													=	Queue()
					__UpperCAmelCase    :     str													=	None
					__UpperCAmelCase    :     str													=	timeout




			def  snake_case__     (   self							: int       ,       a_							: str       ,       a_							: bool = False ):
					'''simple docstring'''





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




			def __iter__(   self							: Union[str, Any] ):
					'''simple docstring'''





					return self




			def  snake_case__     (   self							: Union[str, Any] ):
					'''simple docstring'''





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










from itertools import product

from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros

def        a						(      _UpperCAmelCase							:					Tuple ,   _UpperCAmelCase							:					Optional[int]						):







		'''simple docstring'''





		__UpperCAmelCase    :     Union[str, Any]													=	k_size // 2
		__UpperCAmelCase							,					__UpperCAmelCase    :     Optional[Any]													=	mgrid[0 - center : k_size - center, 0 - center : k_size - center]
		__UpperCAmelCase    :     Any													=	1 / (2 * pi * sigma) * exp(-(square(_UpperCAmelCase						) + square(_UpperCAmelCase						)) / (2 * square(_UpperCAmelCase						))						)
		return g

def        a						(      _UpperCAmelCase							:					Optional[int] ,   _UpperCAmelCase							:					Any ,   _UpperCAmelCase							:					List[Any]						):







		'''simple docstring'''





		__UpperCAmelCase							,					__UpperCAmelCase    :     Union[str, Any]													=	image.shape[0], image.shape[1]
		# dst image height and width
		__UpperCAmelCase    :     str													=	height - k_size + 1
		__UpperCAmelCase    :     Optional[int]													=	width - k_size + 1

		# im2col, turn the k_size*k_size pixels into a row and np.vstack all rows
		__UpperCAmelCase    :     str													=	zeros((dst_height * dst_width, k_size * k_size)						)
		__UpperCAmelCase    :     Optional[Any]													=	0
		for i, j in product(range(_UpperCAmelCase						) ,   range(_UpperCAmelCase						)						):
				__UpperCAmelCase    :     int													=	ravel(image[i : i + k_size, j : j + k_size]						)
				__UpperCAmelCase    :     Union[str, Any]													=	window
				row += 1

		#  turn the kernel into shape(k*k, 1)
		__UpperCAmelCase    :     Tuple													=	gen_gaussian_kernel(_UpperCAmelCase ,   _UpperCAmelCase						)
		__UpperCAmelCase    :     List[Any]													=	ravel(_UpperCAmelCase						)

		# reshape and get the dst image
		__UpperCAmelCase    :     Optional[Any]													=	dot(_UpperCAmelCase ,   _UpperCAmelCase						).reshape(_UpperCAmelCase ,   _UpperCAmelCase						).astype(_UpperCAmelCase						)

		return dst


if __name__ == "__main__":
				# read original image
				__A   			=imread(R"../image_data/lena.jpg")
				# turn image in gray scale value
				__A   			=cvtColor(img, COLOR_BGR2GRAY)

				# get values with two different mask size
				__A   			=gaussian_filter(gray, 3, sigma=1)
				__A   			=gaussian_filter(gray, 5, sigma=0.8)

				# show result images
				imshow("gaussian filter with 3x3 mask", gaussianaxa)
				imshow("gaussian filter with 5x5 mask", gaussianaxa)
				waitKey()





