





import sys
from collections import defaultdict


class   __SCREAMING_SNAKE_CASE     :







       def __init__( self	:      List[Any]     )  ->Optional[int]:
          lowerCamelCase__  :		Tuple     =				[]







       def 		__lowerCamelCase       ( self	:      Optional[Any]						,   A	:      Tuple     )  ->str:
          return self.node_position[vertex]







       def 		__lowerCamelCase       ( self	:      Tuple						,   A	:      str						,   A	:      Optional[Any]     )  ->Optional[int]:
          lowerCamelCase__  :		List[str]     =				pos







       def 		__lowerCamelCase       ( self	:      Any						,   A	:      List[Any]						,   A	:      Tuple						,   A	:      Optional[int]						,   A	:      Union[str, Any]     )  ->Any:

          if start > size // 2 - 1:
             return
          else:
             if 2 * start + 2 >= size:
                lowerCamelCase__  :		Union[str, Any]     =				2 * start + 1
             else:
                if heap[2 * start + 1] < heap[2 * start + 2]:
                   lowerCamelCase__  :		Union[str, Any]     =				2 * start + 1
                else:
                   lowerCamelCase__  :		Tuple     =				2 * start + 2
             if heap[smallest_child] < heap[start]:
                lowerCamelCase__  ,				lowerCamelCase__  :		Union[str, Any]     =				heap[smallest_child], positions[smallest_child]
                lowerCamelCase__  ,				lowerCamelCase__  :		Optional[Any]     =				(
                    heap[start],
                    positions[start],
                )
                lowerCamelCase__  ,				lowerCamelCase__  :		List[Any]     =				temp, tempa

                lowerCamelCase__  :		List[str]     =				self.get_position(positions[smallest_child]     )
                self.set_position(
                    positions[smallest_child]						,   self.get_position(positions[start]     )     )
                self.set_position(positions[start]						,   A     )

                self.top_to_bottom(A						,   A						,   A						,   A     )







       def 		__lowerCamelCase       ( self	:      Union[str, Any]						,   A	:      Dict						,   A	:      List[Any]						,   A	:      Union[str, Any]						,   A	:      Union[str, Any]     )  ->Optional[Any]:
          lowerCamelCase__  :		Optional[int]     =				position[index]

          while index != 0:
             lowerCamelCase__  :		List[Any]     =				int((index - 2) / 2     ) if index % 2 == 0 else int((index - 1) / 2     )

             if val < heap[parent]:
                lowerCamelCase__  :		Optional[int]     =				heap[parent]
                lowerCamelCase__  :		Any     =				position[parent]
                self.set_position(position[parent]						,   A     )
             else:
                lowerCamelCase__  :		Tuple     =				val
                lowerCamelCase__  :		Optional[int]     =				temp
                self.set_position(A						,   A     )
                break
             lowerCamelCase__  :		Optional[Any]     =				parent
          else:
             lowerCamelCase__  :		Dict     =				val
             lowerCamelCase__  :		List[Any]     =				temp
             self.set_position(A						,   0     )







       def 		__lowerCamelCase       ( self	:      List[Any]						,   A	:      Union[str, Any]						,   A	:      Dict     )  ->str:
          lowerCamelCase__  :		List[str]     =				len(A     ) // 2 - 1
          for i in range(A						,   -1						,   -1     ):
             self.top_to_bottom(A						,   A						,   len(A     )						,   A     )







       def 		__lowerCamelCase       ( self	:      Optional[int]						,   A	:      str						,   A	:      Any     )  ->int:
          lowerCamelCase__  :		Any     =				positions[0]
          lowerCamelCase__  :		Tuple     =				sys.maxsize
          self.top_to_bottom(A						,   0						,   len(A     )						,   A     )
          return temp



def 			_a		(       UpperCAmelCase	)							->							Optional[int]:







   """simple docstring"""
   lowerCamelCase__  :		Optional[int]     =				Heap()

   lowerCamelCase__  :		List[Any]     =				[0] * len(A__	)
   lowerCamelCase__  :		Any     =				[-1] * len(A__	)  # Neighboring Tree Vertex of selected vertex
   # Minimum Distance of explored vertex with neighboring vertex of partial tree
   # formed in graph
   lowerCamelCase__  :		Optional[Any]     =				[]  # Heap of Distance of vertices from their neighboring vertex
   lowerCamelCase__  :		Tuple     =				[]

   for vertex in range(len(A__	)	):
      distance_tv.append(sys.maxsize	)
      positions.append(A__	)
      heap.node_position.append(A__	)

   lowerCamelCase__  :		Tuple     =				[]
   lowerCamelCase__  :		List[str]     =				1
   lowerCamelCase__  :		Any     =				sys.maxsize
   for neighbor, distance in adjacency_list[0]:
      lowerCamelCase__  :		str     =				0
      lowerCamelCase__  :		List[str]     =				distance
   heap.heapify(A__     ,    A__	)

   for _ in range(1     ,    len(A__	)	):
      lowerCamelCase__  :		Optional[Any]     =				heap.delete_minimum(A__     ,    A__	)
      if visited[vertex] == 0:
         tree_edges.append((nbr_tv[vertex], vertex)	)
         lowerCamelCase__  :		Union[str, Any]     =				1
         for neighbor, distance in adjacency_list[vertex]:
            if (
                visited[neighbor] == 0
                and distance < distance_tv[heap.get_position(A__	)]
            ):
               lowerCamelCase__  :		str     =				distance
               heap.bottom_to_top(
                   A__     ,    heap.get_position(A__	)     ,    A__     ,    A__	)
               lowerCamelCase__  :		Optional[Any]     =				vertex
   return tree_edges


if __name__ == "__main__":  # pragma: no cover
       # < --------- Prims Algorithm --------- >
       _A   :       List[str]    					=    int(input('Enter number of edges: ').strip())
       _A   :       Optional[Any]    					=    defaultdict(list)
       for _ in range(edges_number):
              _A   :       Optional[int]    					=    [int(x) for x in input().strip().split()]
              adjacency_list[edge[0]].append([edge[1], edge[2]])
              adjacency_list[edge[1]].append([edge[0], edge[2]])
       print(prisms_algorithm(adjacency_list))








import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_deebert

from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow


logging.basicConfig(level=logging.DEBUG)

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

def 	_lowerCAmelCase (    ):
      lowercase__  =	argparse.ArgumentParser()
      parser.add_argument('-f'						)
      lowercase__  =	parser.parse_args()
      return args.f



class    UpperCAmelCase__(				lowerCamelCase						):

   '''simple docstring'''




   def       UpperCAmelCase		(    self	:      List[str])						->					None:




         """simple docstring"""

         lowercase__  =	logging.StreamHandler(sys.stdout)
         logger.addHandler(lowerCAmelCase)


   def       UpperCAmelCase		(    self	:      List[str]      ,					lowerCAmelCase	:      Union[str, Any])						->					List[Any]:




         """simple docstring"""

         lowercase__  =	get_gpu_count()

         if n_gpu > 1:
               pass
               # XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
               # script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
               # distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
               # cmd = [sys.executable] + distributed_args + args
               # execute_subprocess_async(cmd, env=self.get_env())
               # XXX: test the results - need to save them first into .json file
         else:
               args.insert(0      ,					'run_glue_deebert.py')
               with patch.object(lowerCAmelCase      ,					'argv'      ,					lowerCAmelCase):
                     lowercase__  =	run_glue_deebert.main()
                     for value in result.values():
                           self.assertGreaterEqual(lowerCAmelCase      ,					0.6_66)



   @slow
   @require_torch_non_multi_gpu
   def       UpperCAmelCase		(    self	:      Optional[Any])						->					Union[str, Any]:




         """simple docstring"""

         lowercase__  =	'\n            --model_type roberta\n            --model_name_or_path roberta-base\n            --task_name MRPC\n            --do_train\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --max_seq_length 128\n            --per_gpu_eval_batch_size=1\n            --per_gpu_train_batch_size=8\n            --learning_rate 2e-4\n            --num_train_epochs 3\n            --overwrite_output_dir\n            --seed 42\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --save_steps 0\n            --overwrite_cache\n            --eval_after_first_stage\n            '.split()
         self.run_and_check(lowerCAmelCase)

         lowercase__  =	'\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --eval_each_highway\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            '.split()
         self.run_and_check(lowerCAmelCase)

         lowercase__  =	'\n            --model_type roberta\n            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --task_name MRPC\n            --do_eval\n            --do_lower_case\n            --data_dir ./tests/fixtures/tests_samples/MRPC/\n            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage\n            --plot_data_dir ./examples/deebert/results/\n            --max_seq_length 128\n            --early_exit_entropy 0.1\n            --eval_highway\n            --overwrite_cache\n            --per_gpu_eval_batch_size=1\n            '.split()
         self.run_and_check(lowerCAmelCase)
