





import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class SCREAMING_SNAKE_CASE_    :






						def __init__(   self   :   int		, _A   :   Union[str, Any]		, _A   :   int						)				->     Tuple:







							"""simple docstring"""


							snake_case_		:      List[str]           =						0
							# max greyscale value for #FFFFFF
							snake_case_		:      Dict           =						int(self.get_greyscale(255		, 255		, 255						)						)

							if not self.min_threshold < threshold < self.max_threshold:
								snake_case_		:      Union[str, Any]           =						F"""Factor value should be from 0 to {self.max_threshold}"""
								raise ValueError(_A						)

							snake_case_		:      int           =						input_img
							snake_case_		:      Union[str, Any]           =						threshold
							snake_case_    ,snake_case_		:      str           =						self.input_img.shape[1], self.input_img.shape[0]

							# error table size (+4 columns and +1 row) greater than input image because of
							# lack of if statements
							snake_case_		:      Any           =						[
							    [0 for _ in range(self.height + 4						)] for __ in range(self.width + 1						)
							]
							snake_case_		:      List[Any]           =						np.ones((self.width, self.height, 3)		, np.uinta						) * 255






						@classmethod
						def UpperCAmelCase_					(   cls   :   List[str]		, _A   :   int		, _A   :   int		, _A   :   int						)				->     float:







							"""simple docstring"""


							return 0.1_1_4 * blue + 0.5_8_7 * green + 0.2_1_2_6 * red






						def UpperCAmelCase_					(   self   :   List[str]						)				->     None:







							"""simple docstring"""


							for y in range(self.height						):
								for x in range(self.width						):
									snake_case_		:      Union[str, Any]           =						int(self.get_greyscale(*self.input_img[y][x]						)						)
									if self.threshold > greyscale + self.error_table[y][x]:
										snake_case_		:      Dict           =						(0, 0, 0)
										snake_case_		:      List[Any]           =						greyscale + self.error_table[x][y]
									else:
										snake_case_		:      Union[str, Any]           =						(255, 255, 255)
										snake_case_		:      Optional[Any]           =						greyscale + self.error_table[x][y] - 255
									self.error_table[y][x + 1] += int(8 / 32 * current_error						)
									self.error_table[y][x + 2] += int(4 / 32 * current_error						)
									self.error_table[y + 1][x] += int(8 / 32 * current_error						)
									self.error_table[y + 1][x + 1] += int(4 / 32 * current_error						)
									self.error_table[y + 1][x + 2] += int(2 / 32 * current_error						)
									self.error_table[y + 1][x - 1] += int(4 / 32 * current_error						)
									self.error_table[y + 1][x - 2] += int(2 / 32 * current_error						)


if __name__ == "__main__":
						# create Burke's instances with original images in greyscale
						_SCREAMING_SNAKE_CASE   						=		[
						    Burkes(imread("""image_data/lena.jpg""", 1), threshold)
						    for threshold in (1, 1_26, 1_30, 1_40)
						]

						for burkes in burkes_instances:
												burkes.process()

						for burkes in burkes_instances:
												imshow(
												    F'''Original image with dithering threshold: {burkes.threshold}''',
												    burkes.output_img,
												)

						waitKey(0)
						destroyAllWindows()



"""simple docstring"""






import json
import os
import unittest

from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import (
    VOCAB_FILES_NAMES,
    GPTNeoXJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class      _SCREAMING_SNAKE_CASE   (     A__      ,					unittest.TestCase				):
			UpperCAmelCase_    :List[str]												=		GPTNeoXJapaneseTokenizer
			UpperCAmelCase_    :List[str]												=		False
			UpperCAmelCase_    :int												=		{"do_clean_text": False, "add_prefix_space": False}






			def 					__lowerCAmelCase					(   self			)     ->	Optional[Any]:
						super().setUp()

						lowerCAmelCase_       :int     	=    [
						    """こん""",
						    """こんに""",
						    """にちは""",
						    """ばんは""",
						    """世界,㔺界""",
						    """、""",
						    """。""",
						    """<BR>""",
						    """<SP>""",
						    """<TAB>""",
						    """<URL>""",
						    """<EMAIL>""",
						    """<TEL>""",
						    """<DATE>""",
						    """<PRICE>""",
						    """<BLOCK>""",
						    """<KIGOU>""",
						    """<U2000U2BFF>""",
						    """<|emoji1|>""",
						    """<unk>""",
						    """<|startoftext|>""",
						    """<|endoftext|>""",
						]
						lowerCAmelCase_       :str     	=    {"""emoji""": {"""\ud83d\ude00""": """<|emoji1|>"""}, """emoji_inv""": {"""<|emoji1|>""": """\ud83d\ude00"""}}  # 😀
						lowerCAmelCase_       :Dict     	=    {"""unk_token""": """<unk>"""}

						lowerCAmelCase_       :Union[str, Any]     	=    os.path.join(self.tmpdirname			,  VOCAB_FILES_NAMES["""vocab_file"""]			)
						lowerCAmelCase_       :Union[str, Any]     	=    os.path.join(self.tmpdirname			,  VOCAB_FILES_NAMES["""emoji_file"""]			)
						with open(self.vocab_file			,  """w"""			,  encoding="""utf-8"""			) as vocab_writer:
									vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]			)			)
						with open(self.emoji_file			,  """w"""			) as emoji_writer:
									emoji_writer.write(json.dumps(__A			)			)






			def 					__lowerCAmelCase					(   self			,  **__A			)     ->	str:
						kwargs.update(self.special_tokens_map			)
						return GPTNeoXJapaneseTokenizer.from_pretrained(self.tmpdirname			,  **__A			)






			def 					__lowerCAmelCase					(   self			,  __A			)     ->	List[Any]:
						lowerCAmelCase_       :Optional[Any]     	=    """こんにちは、世界。 \nこんばんは、㔺界。😀"""
						lowerCAmelCase_       :List[Any]     	=    """こんにちは、世界。 \nこんばんは、世界。😀"""
						return input_text, output_text






			def 					__lowerCAmelCase					(   self			,  __A			)     ->	Optional[Any]:
						lowerCAmelCase_	,			lowerCAmelCase_       :Optional[int]     	=    self.get_input_output_texts(__A			)
						lowerCAmelCase_       :List[Any]     	=    tokenizer.encode(__A			,  add_special_tokens=__A			)
						lowerCAmelCase_       :Optional[Any]     	=    tokenizer.decode(__A			,  clean_up_tokenization_spaces=__A			)
						return text, ids






			def 					__lowerCAmelCase					(   self			)     ->	str:
						pass  # TODO add if relevant






			def 					__lowerCAmelCase					(   self			)     ->	Any:
						pass  # TODO add if relevant






			def 					__lowerCAmelCase					(   self			)     ->	Optional[int]:
						pass  # TODO add if relevant






			def 					__lowerCAmelCase					(   self			)     ->	Optional[Any]:
						lowerCAmelCase_       :int     	=    self.get_tokenizer()

						# Testing tokenization
						lowerCAmelCase_       :List[str]     	=    """こんにちは、世界。　こんばんは、㔺界。"""
						lowerCAmelCase_       :int     	=    ["""こん""", """にちは""", """、""", """世界""", """。""", """<SP>""", """こん""", """ばんは""", """、""", """㔺界""", """。"""]
						lowerCAmelCase_       :List[Any]     	=    tokenizer.tokenize(__A			)
						self.assertListEqual(__A			,  __A			)

						# Testing conversion to ids without special tokens
						lowerCAmelCase_       :List[str]     	=    [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
						lowerCAmelCase_       :Dict     	=    tokenizer.convert_tokens_to_ids(__A			)
						self.assertListEqual(__A			,  __A			)

						# Testing conversion to ids with special tokens
						lowerCAmelCase_       :Tuple     	=    tokens + [tokenizer.unk_token]
						lowerCAmelCase_       :str     	=    [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
						lowerCAmelCase_       :Any     	=    tokenizer.convert_tokens_to_ids(__A			)
						self.assertListEqual(__A			,  __A			)






			@slow
			def 					__lowerCAmelCase					(   self			)     ->	Any:
						lowerCAmelCase_       :str     	=    self.tokenizer_class.from_pretrained("""abeja/gpt-neox-japanese-2.7b"""			)

						lowerCAmelCase_       :Union[str, Any]     	=    tokenizer.encode("""ありがとう。"""			,  add_special_tokens=__A			)
						lowerCAmelCase_       :Dict     	=    tokenizer.encode("""どういたしまして。"""			,  add_special_tokens=__A			)

						lowerCAmelCase_       :Union[str, Any]     	=    tokenizer.build_inputs_with_special_tokens(__A			)
						lowerCAmelCase_       :Optional[int]     	=    tokenizer.build_inputs_with_special_tokens(__A			,  __A			)

						assert encoded_sentence == ids_a
						assert encoded_pair == ids_a + ids_a






			def 					__lowerCAmelCase					(   self			)     ->	Dict:
						# Intentionally convert some words to accommodate character fluctuations unique to Japanese
						pass






			def 					__lowerCAmelCase					(   self			)     ->	List[str]:
						# tokenizer has no padding token
						pass






