



import sys
from collections import defaultdict


class 				_a						:





							'''simple docstring'''

							def __init__(							self				):







											"""simple docstring"""



											a__	:							List[Any]      						= []



							def 		_A	(							self ,					__UpperCAmelCase				):







											"""simple docstring"""



											return self.node_position[vertex]



							def 		_A	(							self ,					__UpperCAmelCase ,					__UpperCAmelCase				):







											"""simple docstring"""



											a__	:							Union[str, Any]      						= pos



							def 		_A	(							self ,					__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase				):







											"""simple docstring"""



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

																			a__	:							int      						= self.get_position(positions[smallest_child]				)
																			self.set_position(
																			    positions[smallest_child] ,					self.get_position(positions[start]				)				)
																			self.set_position(positions[start] ,					__UpperCAmelCase				)

																			self.top_to_bottom(__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase				)



							def 		_A	(							self ,					__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase				):







											"""simple docstring"""



											a__	:							Optional[Any]      						= position[index]

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

															if val < heap[parent]:
																			a__	:							Union[str, Any]      						= heap[parent]
																			a__	:							int      						= position[parent]
																			self.set_position(position[parent] ,					__UpperCAmelCase				)
															else:
																			a__	:							List[str]      						= val
																			a__	:							Union[str, Any]      						= temp
																			self.set_position(__UpperCAmelCase ,					__UpperCAmelCase				)
																			break
															a__	:							Optional[Any]      						= parent
											else:
															a__	:							Optional[Any]      						= val
															a__	:							int      						= temp
															self.set_position(__UpperCAmelCase ,					0				)



							def 		_A	(							self ,					__UpperCAmelCase ,					__UpperCAmelCase				):







											"""simple docstring"""



											a__	:							List[Any]      						= len(__UpperCAmelCase				) // 2 - 1
											for i in range(__UpperCAmelCase ,					-1 ,					-1				):
															self.top_to_bottom(__UpperCAmelCase ,					__UpperCAmelCase ,					len(__UpperCAmelCase				) ,					__UpperCAmelCase				)




							def 		_A	(							self ,					__UpperCAmelCase ,					__UpperCAmelCase				):







											"""simple docstring"""



											a__	:							Tuple      						= positions[0]
											a__	:							Tuple      						= sys.maxsize
											self.top_to_bottom(__UpperCAmelCase ,					0 ,					len(__UpperCAmelCase				) ,					__UpperCAmelCase				)
											return temp






def     SCREAMING_SNAKE_CASE(      __UpperCamelCase )	->						List[Any]:
				a__	:							Tuple      						= Heap()

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

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

				a__	:							Optional[int]      						= []
				a__	:							Optional[Any]      						= 1
				a__	:							Dict      						= sys.maxsize
				for neighbor, distance in adjacency_list[0]:
								a__	:							Optional[int]      						= 0
								a__	:							Tuple      						= distance
				heap.heapify(__UpperCamelCase	,				__UpperCamelCase )

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


if __name__ == "__main__":  # pragma: no cover
						# < --------- Prims Algorithm --------- >
						lowerCamelCase		       =      int(input("""Enter number of edges: """).strip())
						lowerCamelCase		       =      defaultdict(list)
						for _ in range(edges_number):
												lowerCamelCase		       =      [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 os

import transformers

from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging


logging.set_verbosity_info()

lowerCamelCase		       =      logging.get_logger(__name__)


lowerCamelCase		       =      {name: getattr(transformers, name + """Fast""") for name in SLOW_TO_FAST_CONVERTERS}






def     SCREAMING_SNAKE_CASE(      __UpperCamelCase	,				__UpperCamelCase	,				__UpperCamelCase	,				__UpperCamelCase )	->						Dict:
				if tokenizer_name is not None and tokenizer_name not in TOKENIZER_CLASSES:
								raise ValueError(F'Unrecognized tokenizer name, should be one of {list(TOKENIZER_CLASSES.keys() )}.' )

				if tokenizer_name is None:
								a__	:							str      						= TOKENIZER_CLASSES
				else:
								a__	:							int      						= {tokenizer_name: getattr(__UpperCamelCase	,				tokenizer_name + "Fast" )}

				logger.info(F'Loading tokenizer classes: {tokenizer_names}' )

				for tokenizer_name in tokenizer_names:
								a__	:							Any      						= TOKENIZER_CLASSES[tokenizer_name]

								a__	:							Dict      						= True
								if checkpoint_name is None:
												a__	:							Tuple      						= list(tokenizer_class.max_model_input_sizes.keys() )
								else:
												a__	:							List[str]      						= [checkpoint_name]

								logger.info(F'For tokenizer {tokenizer_class.__class__.__name__} loading checkpoints: {checkpoint_names}' )

								for checkpoint in checkpoint_names:
												logger.info(F'Loading {tokenizer_class.__class__.__name__} {checkpoint}' )

												# Load tokenizer
												a__	:							List[str]      						= tokenizer_class.from_pretrained(__UpperCamelCase	,				force_download=__UpperCamelCase )

												# Save fast tokenizer
												logger.info(F'Save fast tokenizer to {dump_path} with prefix {checkpoint} add_prefix {add_prefix}' )

												# For organization names we create sub-directories
												if "/" in checkpoint:
																a__						,   a__	:							Dict      						= checkpoint.split("/" )
																a__	:							Any      						= os.path.join(__UpperCamelCase	,				__UpperCamelCase )
												elif add_prefix:
																a__	:							int      						= checkpoint
																a__	:							Optional[Any]      						= dump_path
												else:
																a__	:							Dict      						= None
																a__	:							Optional[Any]      						= dump_path

												logger.info(F'=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}' )

												if checkpoint in list(tokenizer.pretrained_vocab_files_map.values() )[0]:
																a__	:							Dict      						= list(tokenizer.pretrained_vocab_files_map.values() )[0][checkpoint]
																a__	:							Optional[Any]      						= file_path.split(__UpperCamelCase )[-1][0]
																if next_char == "/":
																				a__	:							Union[str, Any]      						= os.path.join(__UpperCamelCase	,				__UpperCamelCase )
																				a__	:							Any      						= None

																logger.info(F'=> {dump_path_full} with prefix {checkpoint_prefix_name}, add_prefix {add_prefix}' )

												a__	:							Any      						= tokenizer.save_pretrained(
												    __UpperCamelCase	,				legacy_format=__UpperCamelCase	,				filename_prefix=__UpperCamelCase )
												logger.info(F'=> File names {file_names}' )

												for file_name in file_names:
																if not file_name.endswith("tokenizer.json" ):
																				os.remove(__UpperCamelCase )
																				logger.info(F'=> removing {file_name}' )


if __name__ == "__main__":
						lowerCamelCase		       =      argparse.ArgumentParser()
						# Required parameters
						parser.add_argument(
						    """--dump_path""", default=None, type=str, required=True, help="""Path to output generated fast tokenizer files."""
						)
						parser.add_argument(
						    """--tokenizer_name""",
						    default=None,
						    type=str,
						    help=(
						        F'Optional tokenizer type selected in the list of {list(TOKENIZER_CLASSES.keys())}. If not given, will '
						        """download and convert all the checkpoints from AWS."""
						    ),
						)
						parser.add_argument(
						    """--checkpoint_name""",
						    default=None,
						    type=str,
						    help="""Optional checkpoint name. If not given, will download and convert the canonical checkpoints from AWS.""",
						)
						parser.add_argument(
						    """--force_download""",
						    action="""store_true""",
						    help="""Re-download checkpoints.""",
						)
						lowerCamelCase		       =      parser.parse_args()

						convert_slow_checkpoint_to_fast(args.tokenizer_name, args.checkpoint_name, args.dump_path, args.force_download)


