





"""simple docstring"""
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, require_torch_tpu


logging.basicConfig(level=logging.DEBUG)

__UpperCamelCase     :						Optional[Any]						       =  logging.getLogger()

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    List[Any]			):
 lowerCAmelCase    				= {}
 lowerCAmelCase    				= os.path.join(_UpperCAmelCase  ,     'all_results.json'			)
 if os.path.exists(_UpperCAmelCase			):
  with open(_UpperCAmelCase  ,     'r'			) as f:
   lowerCAmelCase    				= json.load(_UpperCAmelCase			)
 else:
  raise ValueError(F'can\'t find {path}'			)
 return results


__UpperCamelCase     :						Union[str, Any]						       =  logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







@require_torch_tpu
class       a							(   a__  ):



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  import xla_spawn

  lowerCAmelCase    				= self.get_auto_remove_tmp_dir()
  lowerCAmelCase    				= F'\n            ./examples/pytorch/text-classification/run_glue.py\n            --num_cores=8\n            ./examples/pytorch/text-classification/run_glue.py\n            --model_name_or_path distilbert-base-uncased\n            --output_dir {tmp_dir}\n            --overwrite_output_dir\n            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv\n            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv\n            --do_train\n            --do_eval\n            --debug tpu_metrics_debug\n            --per_device_train_batch_size=2\n            --per_device_eval_batch_size=1\n            --learning_rate=1e-4\n            --max_steps=10\n            --warmup_steps=2\n            --seed=42\n            --max_seq_length=128\n            '.split()

  with patch.object(_snake_case				,       'argv'				,       _snake_case     ):
   lowerCAmelCase    				= time()
   xla_spawn.main()
   lowerCAmelCase    				= time()

   lowerCAmelCase    				= get_results(_snake_case     )
   self.assertGreaterEqual(result['eval_accuracy']				,       0.75     )

   # Assert that the script takes less than 500 seconds to make sure it doesn't hang.
   self.assertLess(end - start				,       5_00     )



 def    UpperCamelCase__  (     self     ):







  """simple docstring"""






  import xla_spawn

  lowerCAmelCase    				= '\n            ./tests/test_trainer_tpu.py\n            --num_cores=8\n            ./tests/test_trainer_tpu.py\n            '.split()
  with patch.object(_snake_case				,       'argv'				,       _snake_case     ):
   xla_spawn.main()






"""simple docstring"""


import heapq






def      __UpperCAmelCase       (      lowercase		):







  """simple docstring"""
  _UpperCAmelCase    			=   []

  # for each node and his adjacency list add them and the rank of the node to queue
  # using heapq module the queue will be filled like a Priority Queue
  # heapq works with a min priority queue, so I used -1*len(v) to build it
  for key, value in graph.items():
    # O(log(n))
    heapq.heappush(lowercase ,[-1 * len(lowercase		), (key, value)]		)

  # chosen_vertices = set of chosen vertices
  _UpperCAmelCase    			=   set()

  # while queue isn't empty and there are still edges
  #   (queue[0][0] is the rank of the node with max rank)
  while queue and queue[0][0] != 0:
    # extract vertex with max rank from queue and add it to chosen_vertices
    _UpperCAmelCase    			=   heapq.heappop(lowercase		)[1][0]
    chosen_vertices.add(lowercase		)

    # Remove all arcs adjacent to argmax
    for elem in queue:
      # if v haven't adjacent node, skip
      if elem[0] == 0:
        continue
      # if argmax is reachable from elem
      # remove argmax from elem's adjacent list and update his rank
      if argmax in elem[1][1]:
        _UpperCAmelCase    			=   elem[1][1].index(lowercase		)
        del elem[1][1][index]
        elem[0] += 1
        # re-order the queue
    heapq.heapify(lowercase		)
  return chosen_vertices


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    UpperCAmelCase__			=    {0: [1, 3], 1: [0, 3], 2: [0, 3, 4], 3: [0, 1, 2], 4: [2, 3]}
    print(F'''Minimum vertex cover:\n{greedy_min_vertex_cover(graph)}''')
