


'''simple docstring'''

import json
import os
from typing import Optional, Tuple

import regex as re

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


lowercase__				     =		logging.get_logger(__name__)

lowercase__				     =		{
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
}

lowercase__				     =		{
    "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"},
}

lowercase__				     =		{
    "ctrl": 256,
}

lowercase__				     =		{
    "Pregnancy": 168_629,
    "Christianity": 7_675,
    "Explain": 106_423,
    "Fitness": 63_440,
    "Saving": 63_163,
    "Ask": 27_171,
    "Ass": 95_985,
    "Joke": 163_509,
    "Questions": 45_622,
    "Thoughts": 49_605,
    "Retail": 52_342,
    "Feminism": 164_338,
    "Writing": 11_992,
    "Atheism": 192_263,
    "Netflix": 48_616,
    "Computing": 39_639,
    "Opinion": 43_213,
    "Alone": 44_967,
    "Funny": 58_917,
    "Gaming": 40_358,
    "Human": 4_088,
    "India": 1_331,
    "Joker": 77_138,
    "Diet": 36_206,
    "Legal": 11_859,
    "Norman": 4_939,
    "Tip": 72_689,
    "Weight": 52_343,
    "Movies": 46_273,
    "Running": 23_425,
    "Science": 2_090,
    "Horror": 37_793,
    "Confession": 60_572,
    "Finance": 12_250,
    "Politics": 16_360,
    "Scary": 191_985,
    "Support": 12_654,
    "Technologies": 32_516,
    "Teenage": 66_160,
    "Event": 32_769,
    "Learned": 67_460,
    "Notion": 182_770,
    "Wikipedia": 37_583,
    "Books": 6_665,
    "Extract": 76_050,
    "Confessions": 102_701,
    "Conspiracy": 75_932,
    "Links": 63_674,
    "Narcissus": 150_425,
    "Relationship": 54_766,
    "Relationships": 134_796,
    "Reviews": 41_671,
    "News": 4_256,
    "Translation": 26_820,
    "multilingual": 128_406,
}






def __UpperCamelCase   (			__lowerCamelCase		: int				)      ->     Union[str, Any]:







     '''simple docstring'''






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

     _a						=		set(__lowerCamelCase				)
     return pairs






class 						__SCREAMING_SNAKE_CASE					(      lowerCamelCase__ ):
     UpperCAmelCase 					=				VOCAB_FILES_NAMES
     UpperCAmelCase 					=				PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase 					=				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase 					=				CONTROL_CODES






     def __init__(			self     ,							__UpperCamelCase     ,							__UpperCamelCase     ,							__UpperCamelCase="<unk>"     ,							**__UpperCamelCase		)       ->    str:
          super().__init__(unk_token=__UpperCamelCase     ,							**__UpperCamelCase		)

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






     @property
     def  a_					(			self		)       ->    List[str]:
          return len(self.encoder		)






     def  a_					(			self		)       ->    List[str]:
          return dict(self.encoder     ,							**self.added_tokens_encoder		)






     def  a_					(			self     ,							__UpperCamelCase		)       ->    List[str]:
          if token in self.cache:
               return self.cache[token]
          _a						=		tuple(__UpperCamelCase		)
          _a						=		tuple(list(word[:-1]		) + [word[-1] + "</w>"]		)
          _a						=		get_pairs(__UpperCamelCase		)

          if not pairs:
               return token

          while True:
               _a						=		min(__UpperCamelCase     ,							key=lambda __UpperCamelCase		: self.bpe_ranks.get(__UpperCamelCase     ,							float("inf"		)		)		)
               if bigram not in self.bpe_ranks:
                    break
               _a			,			_a						=		bigram
               _a						=		[]
               _a						=		0
               while i < len(__UpperCamelCase		):
                    try:
                         _a						=		word.index(__UpperCamelCase     ,							__UpperCamelCase		)
                    except ValueError:
                         new_word.extend(word[i:]		)
                         break
                    else:
                         new_word.extend(word[i:j]		)
                         _a						=		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
               _a						=		tuple(__UpperCamelCase		)
               _a						=		new_word
               if len(__UpperCamelCase		) == 1:
                    break
               else:
                    _a						=		get_pairs(__UpperCamelCase		)
          _a						=		"@@ ".join(__UpperCamelCase		)
          _a						=		word[:-4]
          _a						=		word
          return word






     def  a_					(			self     ,							__UpperCamelCase		)       ->    Union[str, Any]:
          _a						=		[]

          _a						=		re.findall(R"\S+\n?"     ,							__UpperCamelCase		)

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






     def  a_					(			self     ,							__UpperCamelCase		)       ->    Dict:
          return self.encoder.get(__UpperCamelCase     ,							self.encoder.get(self.unk_token		)		)






     def  a_					(			self     ,							__UpperCamelCase		)       ->    Tuple:
          return self.decoder.get(__UpperCamelCase     ,							self.unk_token		)






     def  a_					(			self     ,							__UpperCamelCase		)       ->    Optional[int]:
          _a						=		" ".join(__UpperCamelCase		).replace("@@ "     ,							""		).strip()
          return out_string






     def  a_					(			self     ,							__UpperCamelCase     ,							__UpperCamelCase = None		)       ->    Tuple[str]:
          if not os.path.isdir(__UpperCamelCase		):
               logger.error(f"Vocabulary path ({save_directory}) should be a directory"		)
               return
          _a						=		os.path.join(
              __UpperCamelCase     ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)
          _a						=		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"		)

          _a						=		0
          with open(__UpperCamelCase     ,							"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 __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!"		)
                         _a						=		token_index
                    writer.write(" ".join(__UpperCamelCase		) + "\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 collections import defaultdict

from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst






def __UpperCamelCase   (			)      ->     Tuple:







     '''simple docstring'''






     _a			,			_a						=		9, 14  # noqa: F841
     _a						=		[
         [0, 1, 4],
         [0, 7, 8],
         [1, 2, 8],
         [7, 8, 7],
         [7, 6, 1],
         [2, 8, 2],
         [8, 6, 6],
         [2, 3, 7],
         [2, 5, 4],
         [6, 5, 2],
         [3, 5, 14],
         [3, 4, 9],
         [5, 4, 10],
         [1, 7, 11],
     ]

     _a						=		defaultdict(__lowerCamelCase				)
     for nodea, nodea, cost in edges:
          adjancency[nodea].append([nodea, cost]				)
          adjancency[nodea].append([nodea, cost]				)

     _a						=		mst(__lowerCamelCase				)

     _a						=		[
         [7, 6, 1],
         [2, 8, 2],
         [6, 5, 2],
         [0, 1, 4],
         [2, 5, 4],
         [2, 3, 7],
         [0, 7, 8],
         [3, 4, 9],
     ]

     for answer in expected:
          _a						=		tuple(answer[:2]				)
          _a						=		tuple(edge[::-1]				)
          assert edge in result or reverse in result

