

'''simple docstring'''







from collections import deque
from math import floor
from random import random
from time import time


class    A__ :



    def __init__(   self    )  -> List[str]:





           '''simple docstring'''
           A_		   = {}



    def    snake_case_     (   self						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__=1    )  -> List[Any]:





           '''simple docstring'''
           if self.graph.get(UpperCamelCase__    ):
                  if self.graph[u].count([w, v]    ) == 0:
                         self.graph[u].append([w, v]    )
           else:
                  A_		   = [[w, v]]
           if not self.graph.get(UpperCamelCase__    ):
                  A_		   = []



    def    snake_case_     (   self    )  -> Dict:





           '''simple docstring'''
           return list(self.graph    )



    def    snake_case_     (   self						,			UpperCamelCase__						,			UpperCamelCase__    )  -> Optional[int]:





           '''simple docstring'''
           if self.graph.get(UpperCamelCase__    ):
                  for _ in self.graph[u]:
                         if _[1] == v:
                                self.graph[u].remove(UpperCamelCase__    )



    def    snake_case_     (   self						,			UpperCamelCase__=-2						,			UpperCamelCase__=-1    )  -> List[Any]:





           '''simple docstring'''
           if s == d:
                  return []
           A_		   = []
           A_		   = []
           if s == -2:
                  A_		   = list(self.graph    )[0]
           stack.append(UpperCamelCase__    )
           visited.append(UpperCamelCase__    )
           A_		   = s

           while True:
                  # check if there is any non isolated nodes
                  if len(self.graph[s]    ) != 0:
                         A_		   = s
                         for node in self.graph[s]:
                                if visited.count(node[1]    ) < 1:
                                       if node[1] == d:
                                              visited.append(UpperCamelCase__    )
                                              return visited
                                       else:
                                              stack.append(node[1]    )
                                              visited.append(node[1]    )
                                              A_		   = node[1]
                                              break

            # check if all the children are visited
                  if s == ss:
                         stack.pop()
                         if len(UpperCamelCase__    ) != 0:
                                A_		   = stack[len(UpperCamelCase__    ) - 1]
                  else:
                         A_		   = ss

                  # check if se have reached the starting point
                  if len(UpperCamelCase__    ) == 0:
                         return visited



    def    snake_case_     (   self						,			UpperCamelCase__=-1    )  -> str:





           '''simple docstring'''
           if c == -1:
                  A_		   = floor(random() * 10000    ) + 10
           for i in range(UpperCamelCase__    ):
                  # every vertex has max 100 edges
                  for _ in range(floor(random() * 102    ) + 1    ):
                         A_		   = floor(random() * c    ) + 1
                         if n != i:
                                self.add_pair(UpperCamelCase__						,			UpperCamelCase__						,			1    )



    def    snake_case_     (   self						,			UpperCamelCase__=-2    )  -> int:





           '''simple docstring'''
           A_		   = deque()
           A_		   = []
           if s == -2:
                  A_		   = list(self.graph    )[0]
           d.append(UpperCamelCase__    )
           visited.append(UpperCamelCase__    )
           while d:
                  A_		   = d.popleft()
                  if len(self.graph[s]    ) != 0:
                         for node in self.graph[s]:
                                if visited.count(node[1]    ) < 1:
                                       d.append(node[1]    )
                                       visited.append(node[1]    )
           return visited



    def    snake_case_     (   self						,			UpperCamelCase__    )  -> str:





           '''simple docstring'''
           A_		   = 0
           for x in self.graph:
                  for y in self.graph[x]:
                         if y[1] == u:
                                count += 1
           return count



    def    snake_case_     (   self						,			UpperCamelCase__    )  -> Any:





           '''simple docstring'''
           return len(self.graph[u]    )



    def    snake_case_     (   self						,			UpperCamelCase__=-2    )  -> Optional[Any]:





           '''simple docstring'''
           A_		   = []
           A_		   = []
           if s == -2:
                  A_		   = list(self.graph    )[0]
           stack.append(UpperCamelCase__    )
           visited.append(UpperCamelCase__    )
           A_		   = s
           A_		   = []

           while True:
                  # check if there is any non isolated nodes
                  if len(self.graph[s]    ) != 0:
                         A_		   = s
                         for node in self.graph[s]:
                                if visited.count(node[1]    ) < 1:
                                       stack.append(node[1]    )
                                       visited.append(node[1]    )
                                       A_		   = node[1]
                                       break

            # check if all the children are visited
                  if s == ss:
                         sorted_nodes.append(stack.pop()    )
                         if len(UpperCamelCase__    ) != 0:
                                A_		   = stack[len(UpperCamelCase__    ) - 1]
                  else:
                         A_		   = ss

                  # check if se have reached the starting point
                  if len(UpperCamelCase__    ) == 0:
                         return sorted_nodes



    def    snake_case_     (   self    )  -> List[str]:





           '''simple docstring'''
           A_		   = []
           A_		   = []
           A_		   = list(self.graph    )[0]
           stack.append(UpperCamelCase__    )
           visited.append(UpperCamelCase__    )
           A_		   = -2
           A_		   = []
           A_		   = s
           A_		   = False
           A_		   = set()

           while True:
                  # check if there is any non isolated nodes
                  if len(self.graph[s]    ) != 0:
                         A_		   = s
                         for node in self.graph[s]:
                                if (
                                    visited.count(node[1]    ) > 0
                                    and node[1] != parent
                                    and indirect_parents.count(node[1]    ) > 0
                                    and not on_the_way_back
                                ):
                                       A_		   = len(UpperCamelCase__    ) - 1
                                       while len_stack >= 0:
                                              if stack[len_stack] == node[1]:
                                                     anticipating_nodes.add(node[1]    )
                                                     break
                                              else:
                                                     anticipating_nodes.add(stack[len_stack]    )
                                                     len_stack -= 1
                                if visited.count(node[1]    ) < 1:
                                       stack.append(node[1]    )
                                       visited.append(node[1]    )
                                       A_		   = node[1]
                                       break

            # check if all the children are visited
                  if s == ss:
                         stack.pop()
                         A_		   = True
                         if len(UpperCamelCase__    ) != 0:
                                A_		   = stack[len(UpperCamelCase__    ) - 1]
                  else:
                         A_		   = False
                         indirect_parents.append(UpperCamelCase__    )
                         A_		   = s
                         A_		   = ss

                  # check if se have reached the starting point
                  if len(UpperCamelCase__    ) == 0:
                         return list(UpperCamelCase__    )



    def    snake_case_     (   self    )  -> Optional[int]:





           '''simple docstring'''
           A_		   = []
           A_		   = []
           A_		   = list(self.graph    )[0]
           stack.append(UpperCamelCase__    )
           visited.append(UpperCamelCase__    )
           A_		   = -2
           A_		   = []
           A_		   = s
           A_		   = False
           A_		   = set()

           while True:
                  # check if there is any non isolated nodes
                  if len(self.graph[s]    ) != 0:
                         A_		   = s
                         for node in self.graph[s]:
                                if (
                                    visited.count(node[1]    ) > 0
                                    and node[1] != parent
                                    and indirect_parents.count(node[1]    ) > 0
                                    and not on_the_way_back
                                ):
                                       A_		   = len(UpperCamelCase__    ) - 1
                                       while len_stack_minus_one >= 0:
                                              if stack[len_stack_minus_one] == node[1]:
                                                     anticipating_nodes.add(node[1]    )
                                                     break
                                              else:
                                                     return True
                                if visited.count(node[1]    ) < 1:
                                       stack.append(node[1]    )
                                       visited.append(node[1]    )
                                       A_		   = node[1]
                                       break

            # check if all the children are visited
                  if s == ss:
                         stack.pop()
                         A_		   = True
                         if len(UpperCamelCase__    ) != 0:
                                A_		   = stack[len(UpperCamelCase__    ) - 1]
                  else:
                         A_		   = False
                         indirect_parents.append(UpperCamelCase__    )
                         A_		   = s
                         A_		   = ss

                  # check if se have reached the starting point
                  if len(UpperCamelCase__    ) == 0:
                         return False



    def    snake_case_     (   self						,			UpperCamelCase__=-2						,			UpperCamelCase__=-1    )  -> str:





           '''simple docstring'''
           A_		   = time()
           self.dfs(UpperCamelCase__						,			UpperCamelCase__    )
           A_		   = time()
           return end - begin







    def    snake_case_     (   self						,			UpperCamelCase__=-2    )  -> int:





           '''simple docstring'''
           A_		   = time()
           self.bfs(UpperCamelCase__    )
           A_		   = time()
           return end - begin


class    A__ :



    def __init__(   self    )  -> str:





           '''simple docstring'''
           A_		   = {}



    def    snake_case_     (   self						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__=1    )  -> Tuple:





           '''simple docstring'''
           # check if the u exists
           if self.graph.get(UpperCamelCase__    ):
                  # if there already is a edge
                  if self.graph[u].count([w, v]    ) == 0:
                         self.graph[u].append([w, v]    )
           else:
                  # if u does not exist
                  A_		   = [[w, v]]
           # add the other way
           if self.graph.get(UpperCamelCase__    ):
                  # if there already is a edge
                  if self.graph[v].count([w, u]    ) == 0:
                         self.graph[v].append([w, u]    )
           else:
                  # if u does not exist
                  A_		   = [[w, u]]



    def    snake_case_     (   self						,			UpperCamelCase__						,			UpperCamelCase__    )  -> int:





           '''simple docstring'''
           if self.graph.get(UpperCamelCase__    ):
                  for _ in self.graph[u]:
                         if _[1] == v:
                                self.graph[u].remove(UpperCamelCase__    )
        # the other way round
           if self.graph.get(UpperCamelCase__    ):
                  for _ in self.graph[v]:
                         if _[1] == u:
                                self.graph[v].remove(UpperCamelCase__    )



    def    snake_case_     (   self						,			UpperCamelCase__=-2						,			UpperCamelCase__=-1    )  -> Optional[int]:





           '''simple docstring'''
           if s == d:
                  return []
           A_		   = []
           A_		   = []
           if s == -2:
                  A_		   = list(self.graph    )[0]
           stack.append(UpperCamelCase__    )
           visited.append(UpperCamelCase__    )
           A_		   = s

           while True:
                  # check if there is any non isolated nodes
                  if len(self.graph[s]    ) != 0:
                         A_		   = s
                         for node in self.graph[s]:
                                if visited.count(node[1]    ) < 1:
                                       if node[1] == d:
                                              visited.append(UpperCamelCase__    )
                                              return visited
                                       else:
                                              stack.append(node[1]    )
                                              visited.append(node[1]    )
                                              A_		   = node[1]
                                              break

            # check if all the children are visited
                  if s == ss:
                         stack.pop()
                         if len(UpperCamelCase__    ) != 0:
                                A_		   = stack[len(UpperCamelCase__    ) - 1]
                  else:
                         A_		   = ss

                  # check if se have reached the starting point
                  if len(UpperCamelCase__    ) == 0:
                         return visited



    def    snake_case_     (   self						,			UpperCamelCase__=-1    )  -> Optional[Any]:





           '''simple docstring'''
           if c == -1:
                  A_		   = floor(random() * 10000    ) + 10
           for i in range(UpperCamelCase__    ):
                  # every vertex has max 100 edges
                  for _ in range(floor(random() * 102    ) + 1    ):
                         A_		   = floor(random() * c    ) + 1
                         if n != i:
                                self.add_pair(UpperCamelCase__						,			UpperCamelCase__						,			1    )



    def    snake_case_     (   self						,			UpperCamelCase__=-2    )  -> Optional[Any]:





           '''simple docstring'''
           A_		   = deque()
           A_		   = []
           if s == -2:
                  A_		   = list(self.graph    )[0]
           d.append(UpperCamelCase__    )
           visited.append(UpperCamelCase__    )
           while d:
                  A_		   = d.popleft()
                  if len(self.graph[s]    ) != 0:
                         for node in self.graph[s]:
                                if visited.count(node[1]    ) < 1:
                                       d.append(node[1]    )
                                       visited.append(node[1]    )
           return visited



    def    snake_case_     (   self						,			UpperCamelCase__    )  -> Union[str, Any]:





           '''simple docstring'''
           return len(self.graph[u]    )



    def    snake_case_     (   self    )  -> Dict:





           '''simple docstring'''
           A_		   = []
           A_		   = []
           A_		   = list(self.graph    )[0]
           stack.append(UpperCamelCase__    )
           visited.append(UpperCamelCase__    )
           A_		   = -2
           A_		   = []
           A_		   = s
           A_		   = False
           A_		   = set()

           while True:
                  # check if there is any non isolated nodes
                  if len(self.graph[s]    ) != 0:
                         A_		   = s
                         for node in self.graph[s]:
                                if (
                                    visited.count(node[1]    ) > 0
                                    and node[1] != parent
                                    and indirect_parents.count(node[1]    ) > 0
                                    and not on_the_way_back
                                ):
                                       A_		   = len(UpperCamelCase__    ) - 1
                                       while len_stack >= 0:
                                              if stack[len_stack] == node[1]:
                                                     anticipating_nodes.add(node[1]    )
                                                     break
                                              else:
                                                     anticipating_nodes.add(stack[len_stack]    )
                                                     len_stack -= 1
                                if visited.count(node[1]    ) < 1:
                                       stack.append(node[1]    )
                                       visited.append(node[1]    )
                                       A_		   = node[1]
                                       break

            # check if all the children are visited
                  if s == ss:
                         stack.pop()
                         A_		   = True
                         if len(UpperCamelCase__    ) != 0:
                                A_		   = stack[len(UpperCamelCase__    ) - 1]
                  else:
                         A_		   = False
                         indirect_parents.append(UpperCamelCase__    )
                         A_		   = s
                         A_		   = ss

                  # check if se have reached the starting point
                  if len(UpperCamelCase__    ) == 0:
                         return list(UpperCamelCase__    )



    def    snake_case_     (   self    )  -> str:





           '''simple docstring'''
           A_		   = []
           A_		   = []
           A_		   = list(self.graph    )[0]
           stack.append(UpperCamelCase__    )
           visited.append(UpperCamelCase__    )
           A_		   = -2
           A_		   = []
           A_		   = s
           A_		   = False
           A_		   = set()

           while True:
                  # check if there is any non isolated nodes
                  if len(self.graph[s]    ) != 0:
                         A_		   = s
                         for node in self.graph[s]:
                                if (
                                    visited.count(node[1]    ) > 0
                                    and node[1] != parent
                                    and indirect_parents.count(node[1]    ) > 0
                                    and not on_the_way_back
                                ):
                                       A_		   = len(UpperCamelCase__    ) - 1
                                       while len_stack_minus_one >= 0:
                                              if stack[len_stack_minus_one] == node[1]:
                                                     anticipating_nodes.add(node[1]    )
                                                     break
                                              else:
                                                     return True
                                if visited.count(node[1]    ) < 1:
                                       stack.append(node[1]    )
                                       visited.append(node[1]    )
                                       A_		   = node[1]
                                       break

            # check if all the children are visited
                  if s == ss:
                         stack.pop()
                         A_		   = True
                         if len(UpperCamelCase__    ) != 0:
                                A_		   = stack[len(UpperCamelCase__    ) - 1]
                  else:
                         A_		   = False
                         indirect_parents.append(UpperCamelCase__    )
                         A_		   = s
                         A_		   = ss

                  # check if se have reached the starting point
                  if len(UpperCamelCase__    ) == 0:
                         return False



    def    snake_case_     (   self    )  -> List[Any]:





           '''simple docstring'''
           return list(self.graph    )



    def    snake_case_     (   self						,			UpperCamelCase__=-2						,			UpperCamelCase__=-1    )  -> str:





           '''simple docstring'''
           A_		   = time()
           self.dfs(UpperCamelCase__						,			UpperCamelCase__    )
           A_		   = time()
           return end - begin







    def    snake_case_     (   self						,			UpperCamelCase__=-2    )  -> List[Any]:





           '''simple docstring'''
           A_		   = time()
           self.bfs(UpperCamelCase__    )
           A_		   = time()
           return end - begin



'''simple docstring'''







import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union

import torch
from filelock import FileLock
from torch.utils.data import Dataset

from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import logging
from ..processors.glue import glue_convert_examples_to_features, glue_output_modes, glue_processors
from ..processors.utils import InputFeatures


__lowerCamelCase						    =      logging.get_logger(__name__)


@dataclass
class    A__ :
    lowercase		   =						field(metadata={"help": "The name of the task to train on: " + ", ".join(glue_processors.keys()     )}     )
    lowercase		   =						field(
        metadata={"help": "The input data dir. Should contain the .tsv files (or other data files) for the task."}     )
    lowercase		   =						field(
        default=128  ,  metadata={
            "help": (
                "The maximum total input sequence length after tokenization. Sequences longer "
                "than this will be truncated, sequences shorter will be padded."
            )
        }  ,  )
    lowercase		   =						field(
        default=_snake_case  ,  metadata={"help": "Overwrite the cached training and evaluation sets"}     )



    def    snake_case_     (   self    )  -> Any:





           '''simple docstring'''
           A_		   = self.task_name.lower()


class    A__ ( _snake_case     ):
    lowercase		   =						"train"
    lowercase		   =						"dev"
    lowercase		   =						"test"


class    A__ ( _snake_case     ):
    lowercase		   =						42
    lowercase		   =						42
    lowercase		   =						42



    def __init__(   self						,			UpperCamelCase__						,			UpperCamelCase__						,			UpperCamelCase__ = None						,			UpperCamelCase__ = Split.train						,			UpperCamelCase__ = None						,			)  -> List[Any]:





           '''simple docstring'''
           warnings.warn(
               """This dataset will be removed from the library soon, preprocessing should be handled with the 🤗 Datasets """
               """library. You can have a look at this example script for pointers: """
               """https://github.com/huggingface/transformers/blob/main/examples/pytorch/text-classification/run_glue.py"""						,			UpperCamelCase__						,			)
           A_		   = args
           A_		   = glue_processors[args.task_name]()
           A_		   = glue_output_modes[args.task_name]
           if isinstance(UpperCamelCase__						,			UpperCamelCase__    ):
                  try:
                         A_		   = Split[mode]
                  except KeyError:
                         raise KeyError("""mode is not a valid split name"""    )
        # Load data features from cache or dataset file
           A_		   = os.path.join(
               cache_dir if cache_dir is not None else args.data_dir						,			f'''cached_{mode.value}_{tokenizer.__class__.__name__}_{args.max_seq_length}_{args.task_name}'''						,			)
           A_		   = self.processor.get_labels()
           if args.task_name in ["mnli", "mnli-mm"] and tokenizer.__class__.__name__ in (
               "RobertaTokenizer",
               "RobertaTokenizerFast",
               "XLMRobertaTokenizer",
               "BartTokenizer",
               "BartTokenizerFast",
           ):
                  # HACK(label indices are swapped in RoBERTa pretrained model)
                  A_   ,     A_		   = label_list[2], label_list[1]
           A_		   = label_list

           # Make sure only the first process in distributed training processes the dataset,
           # and the others will use the cache.
           A_		   = cached_features_file + """.lock"""
           with FileLock(UpperCamelCase__    ):
                  if os.path.exists(UpperCamelCase__    ) and not args.overwrite_cache:
                         A_		   = time.time()
                         A_		   = torch.load(UpperCamelCase__    )
                         logger.info(
                             f'''Loading features from cached file {cached_features_file} [took %.3f s]'''						,			time.time() - start    )
                  else:
                         logger.info(f'''Creating features from dataset file at {args.data_dir}'''    )

                         if mode == Split.dev:
                                A_		   = self.processor.get_dev_examples(args.data_dir    )
                         elif mode == Split.test:
                                A_		   = self.processor.get_test_examples(args.data_dir    )
                         else:
                                A_		   = self.processor.get_train_examples(args.data_dir    )
                         if limit_length is not None:
                                A_		   = examples[:limit_length]
                         A_		   = glue_convert_examples_to_features(
                             UpperCamelCase__						,			UpperCamelCase__						,			max_length=args.max_seq_length						,			label_list=UpperCamelCase__						,			output_mode=self.output_mode						,			)
                         A_		   = time.time()
                         torch.save(self.features						,			UpperCamelCase__    )
                         # ^ This seems to take a lot of time so I want to investigate why and how we can improve.
                         logger.info(
                             f'''Saving features into cached file {cached_features_file} [took {time.time() - start:.3f} s]'''    )



    def __len__(   self    )  -> str:





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



    def __getitem__(   self						,			UpperCamelCase__    )  -> InputFeatures:





           '''simple docstring'''
           return self.features[i]







    def    snake_case_     (   self    )  -> Dict:





           '''simple docstring'''
           return self.label_list
