



'''simple docstring'''
import json
import os
from typing import List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_UpperCamelCase											=			logging.get_logger(__name__)

_UpperCamelCase											=			{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
}

_UpperCamelCase											=			{
    '''vocab_file''': {
        '''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/vocab.json''',
    },
    '''merges_file''': {'''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/merges.txt'''},
}

_UpperCamelCase											=			{
    '''microsoft/biogpt''': 1024,
}


def   lowercase_	(   lowerCAmelCase__	:  Tuple ):

			"""simple docstring"""





			__UpperCAmelCase   :      int										=     set()
			__UpperCAmelCase   :      int										=     word[0]
			for char in word[1:]:
						pairs.add((prev_char, char) )
						__UpperCAmelCase   :      Union[str, Any]										=     char
			return pairs






class _A  (    __SCREAMING_SNAKE_CASE    ):
		_SCREAMING_SNAKE_CASE					:    Tuple						      =			VOCAB_FILES_NAMES
		_SCREAMING_SNAKE_CASE					:    Optional[int]						      =			PRETRAINED_VOCAB_FILES_MAP
		_SCREAMING_SNAKE_CASE					:    Optional[int]						      =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		_SCREAMING_SNAKE_CASE					:    str						      =			["input_ids", "attention_mask"]





		def __init__(     self ,       __UpperCAmelCase ,       __UpperCAmelCase ,       __UpperCAmelCase="<unk>" ,       __UpperCAmelCase="<s>" ,       __UpperCAmelCase="</s>" ,       __UpperCAmelCase="</s>" ,       __UpperCAmelCase="<pad>" ,       **__UpperCAmelCase ,       )       ->     Optional[int]:

					'''simple docstring'''
					super().__init__(
					    bos_token=__UpperCAmelCase ,       eos_token=__UpperCAmelCase ,       sep_token=__UpperCAmelCase ,       unk_token=__UpperCAmelCase ,       pad_token=__UpperCAmelCase ,       **__UpperCAmelCase ,       )

					try:
								import sacremoses
					except ImportError:
								raise ImportError(
								    """You need to install sacremoses to use BioGptTokenizer. """
								    """See https://pypi.org/project/sacremoses/ for installation."""				)

					__UpperCAmelCase   :      List[str]										=     """en"""
					__UpperCAmelCase   :      List[Any]										=     sacremoses
					# cache of sm.MosesTokenizer instance
					__UpperCAmelCase   :      Tuple										=     {}
					__UpperCAmelCase   :      Union[str, Any]										=     {}
					with open(__UpperCAmelCase ,       encoding="""utf-8"""				) as vocab_handle:
								__UpperCAmelCase   :      Dict										=     json.load(__UpperCAmelCase				)
					__UpperCAmelCase   :      str										=     {v: k for k, v in self.encoder.items()}
					with open(__UpperCAmelCase ,       encoding="""utf-8"""				) as merges_handle:
								__UpperCAmelCase   :      Dict										=     merges_handle.read().split("""\n"""				)[:-1]
					__UpperCAmelCase   :      Tuple										=     [tuple(merge.split()[:2]				) for merge in merges]
					__UpperCAmelCase   :      Optional[Any]										=     dict(zip(__UpperCAmelCase ,       range(len(__UpperCAmelCase				)				)				)				)
					__UpperCAmelCase   :      Tuple										=     {}





		@property
		def 							__A       (     self				)       ->     Union[str, Any]:

					'''simple docstring'''
					return len(self.encoder				)





		def 							__A       (     self				)       ->     Optional[Any]:

					'''simple docstring'''
					return dict(self.encoder ,       **self.added_tokens_encoder				)





		def 							__A       (     self ,       __UpperCAmelCase ,       __UpperCAmelCase				)       ->     Union[str, Any]:

					'''simple docstring'''
					if lang not in self.cache_moses_tokenizer:
								__UpperCAmelCase   :      Any										=     self.sm.MosesTokenizer(lang=__UpperCAmelCase				)
								__UpperCAmelCase   :      Any										=     moses_tokenizer
					return self.cache_moses_tokenizer[lang].tokenize(
					    __UpperCAmelCase ,       aggressive_dash_splits=__UpperCAmelCase ,       return_str=__UpperCAmelCase ,       escape=__UpperCAmelCase				)





		def 							__A       (     self ,       __UpperCAmelCase ,       __UpperCAmelCase				)       ->     Dict:

					'''simple docstring'''
					if lang not in self.cache_moses_detokenizer:
								__UpperCAmelCase   :      List[Any]										=     self.sm.MosesDetokenizer(lang=__UpperCAmelCase				)
								__UpperCAmelCase   :      int										=     moses_detokenizer
					return self.cache_moses_detokenizer[lang].detokenize(__UpperCAmelCase				)





		def 							__A       (     self ,       __UpperCAmelCase				)       ->     Optional[int]:

					'''simple docstring'''
					__UpperCAmelCase   :      List[str]										=     tuple(token[:-1]				) + (token[-1] + """</w>""",)
					if token in self.cache:
								return self.cache[token]
					__UpperCAmelCase   :      int										=     get_pairs(__UpperCAmelCase				)

					if not pairs:
								return token + "</w>"

					while True:
								__UpperCAmelCase   :      Optional[int]										=     min(__UpperCAmelCase ,       key=lambda __UpperCAmelCase				: self.bpe_ranks.get(__UpperCAmelCase ,       float("""inf"""				)				)				)
								if bigram not in self.bpe_ranks:
											break
								__UpperCAmelCase				,  __UpperCAmelCase   :      Optional[int]										=     bigram
								__UpperCAmelCase   :      str										=     []
								__UpperCAmelCase   :      List[str]										=     0
								while i < len(__UpperCAmelCase				):
											try:
														__UpperCAmelCase   :      Optional[int]										=     word.index(__UpperCAmelCase ,       __UpperCAmelCase				)
											except ValueError:
														new_word.extend(word[i:]				)
														break
											else:
														new_word.extend(word[i:j]				)
														__UpperCAmelCase   :      Any										=     j

											if word[i] == first and i < len(__UpperCAmelCase				) - 1 and word[i + 1] == second:
														new_word.append(first + second				)
														i += 2
											else:
														new_word.append(word[i]				)
														i += 1
								__UpperCAmelCase   :      Any										=     tuple(__UpperCAmelCase				)
								__UpperCAmelCase   :      int										=     new_word
								if len(__UpperCAmelCase				) == 1:
											break
								else:
											__UpperCAmelCase   :      str										=     get_pairs(__UpperCAmelCase				)
					__UpperCAmelCase   :      Tuple										=     """ """.join(__UpperCAmelCase				)
					if word == "\n  </w>":
								__UpperCAmelCase   :      Union[str, Any]										=     """\n</w>"""
					__UpperCAmelCase   :      Union[str, Any]										=     word
					return word





		def 							__A       (     self ,       __UpperCAmelCase ,       __UpperCAmelCase=False				)       ->     List[str]:

					'''simple docstring'''
					if bypass_tokenizer:
								__UpperCAmelCase   :      List[str]										=     text.split()
					else:
								__UpperCAmelCase   :      Any										=     self.moses_tokenize(__UpperCAmelCase ,       self.lang				)

					__UpperCAmelCase   :      Optional[int]										=     []
					for token in text:
								if token:
											split_tokens.extend(list(self.bpe(__UpperCAmelCase				).split(""" """				)				)				)

					return split_tokens





		def 							__A       (     self ,       __UpperCAmelCase				)       ->     List[Any]:

					'''simple docstring'''
					return self.encoder.get(__UpperCAmelCase ,       self.encoder.get(self.unk_token				)				)





		def 							__A       (     self ,       __UpperCAmelCase				)       ->     Union[str, Any]:

					'''simple docstring'''
					return self.decoder.get(__UpperCAmelCase ,       self.unk_token				)





		def 							__A       (     self ,       __UpperCAmelCase				)       ->     int:

					'''simple docstring'''
					__UpperCAmelCase   :      Union[str, Any]										=     [t.replace(""" """ ,       """"""				).replace("""</w>""" ,       """ """				) for t in tokens]
					__UpperCAmelCase   :      Tuple										=     """""".join(__UpperCAmelCase				).split()
					# detokenize
					__UpperCAmelCase   :      str										=     self.moses_detokenize(__UpperCAmelCase ,       self.lang				)
					return text





		def 							__A       (     self ,       __UpperCAmelCase ,       __UpperCAmelCase = None				)       ->     List[int]:

					'''simple docstring'''
					if token_ids_a is None:
								return [self.sep_token_id] + token_ids_a
					__UpperCAmelCase   :      Tuple										=     [self.sep_token_id]
					return sep + token_ids_a + sep + token_ids_a





		def 							__A       (     self ,       __UpperCAmelCase ,       __UpperCAmelCase = None ,       __UpperCAmelCase = False				)       ->     List[int]:

					'''simple docstring'''
					if already_has_special_tokens:
								return super().get_special_tokens_mask(
								    token_ids_a=__UpperCAmelCase ,       token_ids_a=__UpperCAmelCase ,       already_has_special_tokens=__UpperCAmelCase				)
					# no bos used in fairseq
					if token_ids_a is not None:
								return [1] + ([0] * len(__UpperCAmelCase				)) + [1] + ([0] * len(__UpperCAmelCase				))
					return [1] + ([0] * len(__UpperCAmelCase				))





		def 							__A       (     self ,       __UpperCAmelCase ,       __UpperCAmelCase = None				)       ->     List[int]:

					'''simple docstring'''
					__UpperCAmelCase   :      str										=     [self.sep_token_id]

					# no bos used in fairseq
					if token_ids_a is None:
								return len(token_ids_a + sep				) * [0]
					return len(token_ids_a + sep				) * [0] + len(token_ids_a + sep				) * [1]





		def 							__A       (     self ,       __UpperCAmelCase ,       __UpperCAmelCase = None				)       ->     Tuple[str]:

					'''simple docstring'''
					if not os.path.isdir(__UpperCAmelCase				):
								logger.error(f'Vocabulary path ({save_directory}) should be a directory'				)
								return
					__UpperCAmelCase   :      Dict										=     os.path.join(
					    __UpperCAmelCase ,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)
					__UpperCAmelCase   :      Optional[Any]										=     os.path.join(
					    __UpperCAmelCase ,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]				)

					with open(__UpperCAmelCase ,       """w""" ,       encoding="""utf-8"""				) as f:
								f.write(json.dumps(self.encoder ,       indent=2 ,       sort_keys=__UpperCAmelCase ,       ensure_ascii=__UpperCAmelCase				) + """\n"""				)

					__UpperCAmelCase   :      Optional[int]										=     0
					with open(__UpperCAmelCase ,       """w""" ,       encoding="""utf-8"""				) as writer:
								for bpe_tokens, token_index in sorted(self.bpe_ranks.items() ,       key=lambda __UpperCAmelCase				: kv[1]				):
											if index != token_index:
														logger.warning(
														    f'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
														    """ Please check that the tokenizer is not corrupted!"""				)
														__UpperCAmelCase   :      Optional[Any]										=     token_index
											writer.write(""" """.join(__UpperCAmelCase				) + """\n"""				)
											index += 1

					return vocab_file, merge_file





		def __getstate__(     self				)       ->     Tuple:

					'''simple docstring'''
					__UpperCAmelCase   :      List[str]										=     self.__dict__.copy()
					__UpperCAmelCase   :      Dict										=     None
					return state





		def __setstate__(     self ,       __UpperCAmelCase				)       ->     Optional[Any]:

					'''simple docstring'''
					__UpperCAmelCase   :      List[str]										=     d

					try:
								import sacremoses
					except ImportError:
								raise ImportError(
								    """You need to install sacremoses to use XLMTokenizer. """
								    """See https://pypi.org/project/sacremoses/ for installation."""				)

					__UpperCAmelCase   :      Any										=     sacremoses









'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey



class _A  :





		def __init__(     self ,       __UpperCAmelCase ,       __UpperCAmelCase				)       ->     Union[str, Any]:

					'''simple docstring'''
					__UpperCAmelCase   :      Optional[int]										=     0
					# max greyscale value for #FFFFFF
					__UpperCAmelCase   :      List[Any]										=     int(self.get_greyscale(255 ,       255 ,       255				)				)

					if not self.min_threshold < threshold < self.max_threshold:
								__UpperCAmelCase   :      str										=     f'Factor value should be from 0 to {self.max_threshold}'
								raise ValueError(__UpperCAmelCase				)

					__UpperCAmelCase   :      Tuple										=     input_img
					__UpperCAmelCase   :      Optional[Any]										=     threshold
					__UpperCAmelCase				,  __UpperCAmelCase   :      List[Any]										=     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
					__UpperCAmelCase   :      Optional[Any]										=     [
					    [0 for _ in range(self.height + 4				)] for __ in range(self.width + 1				)
					]
					__UpperCAmelCase   :      Any										=     np.ones((self.width, self.height, 3) ,       np.uinta				) * 255





		@classmethod
		def 							__A       (     cls ,       __UpperCAmelCase ,       __UpperCAmelCase ,       __UpperCAmelCase				)       ->     float:

					'''simple docstring'''
					return 0.114 * blue + 0.587 * green + 0.2126 * red





		def 							__A       (     self				)       ->     None:

					'''simple docstring'''
					for y in range(self.height				):
								for x in range(self.width				):
											__UpperCAmelCase   :      Optional[Any]										=     int(self.get_greyscale(*self.input_img[y][x]				)				)
											if self.threshold > greyscale + self.error_table[y][x]:
														__UpperCAmelCase   :      List[Any]										=     (0, 0, 0)
														__UpperCAmelCase   :      Union[str, Any]										=     greyscale + self.error_table[x][y]
											else:
														__UpperCAmelCase   :      Optional[Any]										=     (255, 255, 255)
														__UpperCAmelCase   :      Dict										=     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
					_UpperCamelCase											=			[
					    Burkes(imread('''image_data/lena.jpg''', 1), threshold)
					    for threshold in (1, 126, 130, 140)
					]

					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()




