





'''simple docstring'''






import json
import os
from typing import Optional, Tuple

import regex as re

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


A__    :       List[Any]              =logging.get_logger(__name__)

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

A__    :       Dict              ={
    '''vocab_file''': {'''ctrl''': '''https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-vocab.json'''},
    '''merges_file''': {'''ctrl''': '''https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-merges.txt'''},
}

A__    :       int              ={
    '''ctrl''': 2_56,
}

A__    :       Optional[Any]              ={
    '''Pregnancy''': 16_86_29,
    '''Christianity''': 76_75,
    '''Explain''': 10_64_23,
    '''Fitness''': 6_34_40,
    '''Saving''': 6_31_63,
    '''Ask''': 2_71_71,
    '''Ass''': 9_59_85,
    '''Joke''': 16_35_09,
    '''Questions''': 4_56_22,
    '''Thoughts''': 4_96_05,
    '''Retail''': 5_23_42,
    '''Feminism''': 16_43_38,
    '''Writing''': 1_19_92,
    '''Atheism''': 19_22_63,
    '''Netflix''': 4_86_16,
    '''Computing''': 3_96_39,
    '''Opinion''': 4_32_13,
    '''Alone''': 4_49_67,
    '''Funny''': 5_89_17,
    '''Gaming''': 4_03_58,
    '''Human''': 40_88,
    '''India''': 13_31,
    '''Joker''': 7_71_38,
    '''Diet''': 3_62_06,
    '''Legal''': 1_18_59,
    '''Norman''': 49_39,
    '''Tip''': 7_26_89,
    '''Weight''': 5_23_43,
    '''Movies''': 4_62_73,
    '''Running''': 2_34_25,
    '''Science''': 20_90,
    '''Horror''': 3_77_93,
    '''Confession''': 6_05_72,
    '''Finance''': 1_22_50,
    '''Politics''': 1_63_60,
    '''Scary''': 19_19_85,
    '''Support''': 1_26_54,
    '''Technologies''': 3_25_16,
    '''Teenage''': 6_61_60,
    '''Event''': 3_27_69,
    '''Learned''': 6_74_60,
    '''Notion''': 18_27_70,
    '''Wikipedia''': 3_75_83,
    '''Books''': 66_65,
    '''Extract''': 7_60_50,
    '''Confessions''': 10_27_01,
    '''Conspiracy''': 7_59_32,
    '''Links''': 6_36_74,
    '''Narcissus''': 15_04_25,
    '''Relationship''': 5_47_66,
    '''Relationships''': 13_47_96,
    '''Reviews''': 4_16_71,
    '''News''': 42_56,
    '''Translation''': 2_68_20,
    '''multilingual''': 12_84_06,
}
def        UpperCamelCase__				(		lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase												=							set()
      _lowerCAmelCase												=							word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)  )
            _lowerCAmelCase												=							char

      _lowerCAmelCase												=							set(lowerCAmelCase  )
      return pairs





class 			UpperCAmelCase					(      snake_case_       ):
      _lowercase:      int											=       VOCAB_FILES_NAMES
      _lowercase:      str											=       PRETRAINED_VOCAB_FILES_MAP
      _lowercase:      Tuple											=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _lowercase:      Optional[Any]											=       CONTROL_CODES




      def __init__(      self      :			Optional[Any]      ,      __snake_case      :			Tuple      ,      __snake_case      :			int      ,      __snake_case      :			Dict="<unk>"      ,      **__snake_case      :			Tuple  )    ->				Optional[int]:
            super().__init__(unk_token=__snake_case      ,      **__snake_case  )

            with open(__snake_case      ,      encoding="""utf-8"""  ) as vocab_handle:
                  _lowerCAmelCase												=							json.load(__snake_case  )
            _lowerCAmelCase												=							{v: k for k, v in self.encoder.items()}
            with open(__snake_case      ,      encoding="""utf-8"""  ) as merges_handle:
                  _lowerCAmelCase												=							merges_handle.read().split("""\n"""  )[1:-1]
            _lowerCAmelCase												=							[tuple(merge.split()  ) for merge in merges]
            _lowerCAmelCase												=							dict(zip(__snake_case      ,      range(len(__snake_case  )  )  )  )
            _lowerCAmelCase												=							{}




      @property
      def     lowercase__   (      self      :			Any  )    ->				Tuple:
            return len(self.encoder  )




      def     lowercase__   (      self      :			Union[str, Any]  )    ->				str:
            return dict(self.encoder      ,      **self.added_tokens_encoder  )




      def     lowercase__   (      self      :			List[str]      ,      __snake_case      :			Optional[Any]  )    ->				Optional[int]:
            if token in self.cache:
                  return self.cache[token]
            _lowerCAmelCase												=							tuple(__snake_case  )
            _lowerCAmelCase												=							tuple(list(word[:-1]  ) + [word[-1] + """</w>"""]  )
            _lowerCAmelCase												=							get_pairs(__snake_case  )

            if not pairs:
                  return token

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

                        if word[i] == first and i < len(__snake_case  ) - 1 and word[i + 1] == second:
                              new_word.append(first + second  )
                              i += 2
                        else:
                              new_word.append(word[i]  )
                              i += 1
                  _lowerCAmelCase												=							tuple(__snake_case  )
                  _lowerCAmelCase												=							new_word
                  if len(__snake_case  ) == 1:
                        break
                  else:
                        _lowerCAmelCase												=							get_pairs(__snake_case  )
            _lowerCAmelCase												=							"""@@ """.join(__snake_case  )
            _lowerCAmelCase												=							word[:-4]
            _lowerCAmelCase												=							word
            return word




      def     lowercase__   (      self      :			Tuple      ,      __snake_case      :			Dict  )    ->				Optional[int]:
            _lowerCAmelCase												=							[]

            _lowerCAmelCase												=							re.findall(R"""\S+\n?"""      ,      __snake_case  )

            for token in words:
                  split_tokens.extend(list(self.bpe(__snake_case  ).split(""" """  )  )  )
            return split_tokens




      def     lowercase__   (      self      :			Union[str, Any]      ,      __snake_case      :			Dict  )    ->				Tuple:
            return self.encoder.get(__snake_case      ,      self.encoder.get(self.unk_token  )  )




      def     lowercase__   (      self      :			str      ,      __snake_case      :			List[str]  )    ->				str:
            return self.decoder.get(__snake_case      ,      self.unk_token  )




      def     lowercase__   (      self      :			Dict      ,      __snake_case      :			str  )    ->				str:
            _lowerCAmelCase												=							""" """.join(__snake_case  ).replace("""@@ """      ,      """"""  ).strip()
            return out_string




      def     lowercase__   (      self      :			List[Any]      ,      __snake_case      :			str      ,      __snake_case      :			Optional[str] = None  )    ->				Tuple[str]:
            if not os.path.isdir(__snake_case  ):
                  logger.error(f"Vocabulary path ({save_directory}) should be a directory"  )
                  return
            _lowerCAmelCase												=							os.path.join(
                __snake_case      ,      (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]  )
            _lowerCAmelCase												=							os.path.join(
                __snake_case      ,      (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]  )

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

            _lowerCAmelCase												=							0
            with open(__snake_case      ,      """w"""      ,      encoding="""utf-8"""  ) as writer:
                  writer.write("""#version: 0.2\n"""  )
                  for bpe_tokens, token_index in sorted(self.bpe_ranks.items()      ,      key=lambda __snake_case  : 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!"""  )
                              _lowerCAmelCase												=							token_index
                        writer.write(""" """.join(__snake_case  ) + """\n"""  )
                        index += 1

            return vocab_file, merge_file

      # def decode(self, token_ids, skip_special_tokens=False, clean_up_tokenization_spaces=True):
      #     filtered_tokens = ' '.join(self.convert_ids_to_tokens(token_ids, skip_special_tokens=skip_special_tokens))
      #     tokens_generated_so_far = re.sub('(@@ )', '', string=filtered_tokens)
      #     tokens_generated_so_far = re.sub('(@@ ?$)', '', string=tokens_generated_so_far)
      #     return ''.join(tokens_generated_so_far)













'''simple docstring'''






from pathlib import Path

import cva
import numpy as np
from matplotlib import pyplot as plt
def        UpperCamelCase__				(		lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase							,     lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase												=							cva.getAffineTransform(lowerCAmelCase							,     lowerCAmelCase  )
      return cva.warpAffine(lowerCAmelCase							,     lowerCAmelCase							,     (rows, cols)  )


if __name__ == "__main__":
      # read original image
      A__    :       Any              =cva.imread(
          str(Path(__file__).resolve().parent.parent / '''image_data''' / '''lena.jpg''')
      )
      # turn image in gray scale value
      A__    :       Any              =cva.cvtColor(image, cva.COLOR_BGR2GRAY)
      # get image shape
      A__       ,						A__    :       Tuple              =gray_img.shape

      # set different points to rotate image
      A__    :       Optional[int]              =np.array([[50, 50], [2_00, 50], [50, 2_00]], np.floataa)
      A__    :       Tuple              =np.array([[10, 1_00], [2_00, 50], [1_00, 2_50]], np.floataa)
      A__    :       List[str]              =np.array([[50, 50], [1_50, 50], [1_20, 2_00]], np.floataa)
      A__    :       Dict              =np.array([[10, 1_00], [80, 50], [1_80, 2_50]], np.floataa)

      # add all rotated images in a list
      A__    :       List[Any]              =[
          gray_img,
          get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
          get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
          get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
      ]

      # plot different image rotations
      A__    :       Tuple              =plt.figure(1)
      A__    :       int              =['''Original''', '''Rotation 1''', '''Rotation 2''', '''Rotation 3''']
      for i, image in enumerate(images):
            plt.subplot(2, 2, i + 1), plt.imshow(image, '''gray''')
            plt.title(titles[i])
            plt.axis('''off''')
            plt.subplots_adjust(left=0.0, bottom=0.05, right=1.0, top=0.95)
      plt.show()






