


"""simple docstring"""
import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
			from .tokenization_reformer import ReformerTokenizer
else:
			SCREAMING_SNAKE_CASE					:       Union[str, Any]							   =							None


SCREAMING_SNAKE_CASE					:       int							   =							logging.get_logger(__name__)


SCREAMING_SNAKE_CASE					:       Union[str, Any]							   =							"""▁"""

SCREAMING_SNAKE_CASE					:       Optional[int]							   =							{"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

SCREAMING_SNAKE_CASE					:       Tuple							   =							{
    """vocab_file""": {
        """google/reformer-crime-and-punishment""": (
            """https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"""
        )
    },
    """tokenizer_file""": {
        """google/reformer-crime-and-punishment""": (
            """https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json"""
        )
    },
}

SCREAMING_SNAKE_CASE					:       List[Any]							   =							{
    """google/reformer-crime-and-punishment""": 52_4288,
}



class      _UpperCAmelCase					(				__snake_case							):






		'''simple docstring'''

		lowerCamelCase__           =VOCAB_FILES_NAMES
		lowerCamelCase__           =PRETRAINED_VOCAB_FILES_MAP
		lowerCamelCase__           =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowerCamelCase__           =['input_ids', 'attention_mask']
		lowerCamelCase__           =ReformerTokenizer



		def __init__(self							,			a_=None							,			a_=None							,			a_="</s>"							,			a_="<unk>"							,			a_=[]							,			**a_							,			):





			'''simple docstring'''

			super().__init__(
			    a_							,			tokenizer_file=a_							,			eos_token=a_							,			unk_token=a_							,			additional_special_tokens=a_							,			**a_							,			)

			__snake_case      :		List[Any]         =							vocab_file
			__snake_case      :		Any         =							False if not self.vocab_file else True



		def 							SCREAMING_SNAKE_CASE    (self							,			a_							,			a_ = None   ):





			'''simple docstring'''

			if not self.can_save_slow_tokenizer:
				raise ValueError(
				    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
				    '''tokenizer.'''   )

			if not os.path.isdir(a_   ):
				logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""   )
				return
			__snake_case      :		Union[str, Any]         =							os.path.join(
			    a_							,			(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']   )

			if os.path.abspath(self.vocab_file   ) != os.path.abspath(a_   ):
				copyfile(self.vocab_file							,			a_   )

			return (out_vocab_file,)












'''simple docstring'''

from __future__ import annotations

import random

# Adjacency list representation of this graph:
# https://en.wikipedia.org/wiki/File:Single_run_of_Karger%E2%80%99s_Mincut_algorithm.svg
UpperCAmelCase       :		List[Any]		=				{
    '1': ['2', '3', '4', '5'],
    '2': ['1', '3', '4', '5'],
    '3': ['1', '2', '4', '5', '10'],
    '4': ['1', '2', '3', '5', '6'],
    '5': ['1', '2', '3', '4', '7'],
    '6': ['7', '8', '9', '10', '4'],
    '7': ['6', '8', '9', '10', '5'],
    '8': ['6', '7', '9', '10'],
    '9': ['6', '7', '8', '10'],
    '10': ['6', '7', '8', '9', '3'],
}




def  _a     (				lowerCAmelCase_						):





      """simple docstring"""



      _snake_case		:						Dict         =  {node: {node} for node in graph}

      _snake_case		:						str         =  {node: graph[node][:] for node in graph}

      while len(lowerCAmelCase_						) > 2:
            # Choose a random edge.
            _snake_case		:						Optional[Any]         =  random.choice(list(graph_copy.keys()						)						)
            _snake_case		:						Union[str, Any]         =  random.choice(graph_copy[u]						)

            # Contract edge (u, v) to new node uv
            _snake_case		:						List[str]         =  u + v
            _snake_case		:						List[str]         =  list(set(graph_copy[u] + graph_copy[v]						)						)
            uv_neighbors.remove(lowerCAmelCase_						)
            uv_neighbors.remove(lowerCAmelCase_						)
            _snake_case		:						Tuple         =  uv_neighbors
            for neighbor in uv_neighbors:
                  graph_copy[neighbor].append(lowerCAmelCase_						)

            _snake_case		:						Tuple         =  set(contracted_nodes[u].union(contracted_nodes[v]						)						)

            # Remove nodes u and v.
            del graph_copy[u]
            del graph_copy[v]
            for neighbor in uv_neighbors:
                  if u in graph_copy[neighbor]:
                        graph_copy[neighbor].remove(lowerCAmelCase_						)
                  if v in graph_copy[neighbor]:
                        graph_copy[neighbor].remove(lowerCAmelCase_						)

    # Find cutset.
      _snake_case		:						Any         =  [contracted_nodes[node] for node in graph_copy]
      return {
          (node, neighbor)
          for node in groups[0]
          for neighbor in graph[node]
          if neighbor in groups[1]
      }


if __name__ == "__main__":
   print(partition_graph(TEST_GRAPH))


