






'''simple docstring'''







import sys
from collections import defaultdict

class _lowercase     :




							def __init__(							self:    Tuple					):
														lowerCamelCase__ :     int	  =	[]




							def 		lowerCamelCase_    (							self:    Dict      ,							UpperCamelCase__:    int					):
														return self.node_position[vertex]




							def 		lowerCamelCase_    (							self:    Any      ,							UpperCamelCase__:    Any      ,							UpperCamelCase__:    int					):
														lowerCamelCase__ :     Optional[Any]	  =	pos




							def 		lowerCamelCase_    (							self:    Optional[int]      ,							UpperCamelCase__:    int      ,							UpperCamelCase__:    Optional[int]      ,							UpperCamelCase__:    Optional[Any]      ,							UpperCamelCase__:    List[str]					):
														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__ :     Optional[Any]	  =	2 * start + 1
																												else:
																																			lowerCamelCase__ :     Tuple	  =	2 * start + 2
																					if heap[smallest_child] < heap[start]:
																												lowerCamelCase__ :     int	  =	heap[smallest_child], positions[smallest_child]
																												lowerCamelCase__ :     int	  =	(
																												    heap[start],
																												    positions[start],
																												)
																												lowerCamelCase__ :     Optional[Any]	  =	temp, tempa

																												lowerCamelCase__ :     Tuple	  =	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 		lowerCamelCase_    (							self:    Dict      ,							UpperCamelCase__:    Union[str, Any]      ,							UpperCamelCase__:    int      ,							UpperCamelCase__:    Tuple      ,							UpperCamelCase__:    int					):
														lowerCamelCase__ :     Any	  =	position[index]

														while index != 0:
																					lowerCamelCase__ :     Tuple	  =	int((index - 2) / 2					) if index % 2 == 0 else int((index - 1) / 2					)

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




							def 		lowerCamelCase_    (							self:    Any      ,							UpperCamelCase__:    Optional[Any]      ,							UpperCamelCase__:    Any					):
														lowerCamelCase__ :     Tuple	  =	len(UpperCamelCase__					) // 2 - 1
														for i in range(UpperCamelCase__      ,							-1      ,							-1					):
																					self.top_to_bottom(UpperCamelCase__      ,							UpperCamelCase__      ,							len(UpperCamelCase__					)      ,							UpperCamelCase__					)




							def 		lowerCamelCase_    (							self:    str      ,							UpperCamelCase__:    str      ,							UpperCamelCase__:    Any					):
														lowerCamelCase__ :     Union[str, Any]	  =	positions[0]
														lowerCamelCase__ :     Any	  =	sys.maxsize
														self.top_to_bottom(UpperCamelCase__      ,							0      ,							len(UpperCamelCase__					)      ,							UpperCamelCase__					)
														return temp





def 			SCREAMING_SNAKE_CASE_	(UpperCamelCase				)				->	str:
							lowerCamelCase__ :     Any	  =	Heap()

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

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

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

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


if __name__ == "__main__":  # pragma: no cover
			# < --------- Prims Algorithm --------- >
			_A     :      Tuple   					=int(input('''Enter number of edges: ''').strip())
			_A     :      Union[str, Any]   					=defaultdict(list)
			for _ in range(edges_number):
						_A     :      Any   					=[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))












'''simple docstring'''







import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List

from ..utils import logging
from . import BaseTransformersCLICommand


try:
			from cookiecutter.main import cookiecutter

			_A     :      List[Any]   					=True
except ImportError:
			_A     :      int   					=False

_A     :      Union[str, Any]   					=logging.get_logger(__name__)  # pylint: disable=invalid-name





def 			SCREAMING_SNAKE_CASE_	(UpperCamelCase				)				->	Tuple:
							return AddNewModelCommand(args.testing    ,      args.testing_file    ,      path=args.path				)



class _lowercase     (    _lowercase		):




							@staticmethod
							def 		lowerCamelCase_    (							UpperCamelCase__:    ArgumentParser					):
														lowerCamelCase__ :     List[str]	  =	parser.add_parser("""add-new-model"""					)
														add_new_model_parser.add_argument("""--testing"""      ,							action="""store_true"""      ,							help="""If in testing mode."""					)
														add_new_model_parser.add_argument("""--testing_file"""      ,							type=UpperCamelCase__      ,							help="""Configuration file on which to run."""					)
														add_new_model_parser.add_argument(
														    """--path"""      ,							type=UpperCamelCase__      ,							help="""Path to cookiecutter. Should only be used for testing purposes."""					)
														add_new_model_parser.set_defaults(func=UpperCamelCase__					)




							def __init__(							self:    Optional[int]      ,							UpperCamelCase__:    bool      ,							UpperCamelCase__:    str      ,							UpperCamelCase__:    str=None      ,							*UpperCamelCase__:    Optional[int]					):
														lowerCamelCase__ :     List[Any]	  =	testing
														lowerCamelCase__ :     Tuple	  =	testing_file
														lowerCamelCase__ :     int	  =	path




							def 		lowerCamelCase_    (							self:    int					):
														warnings.warn(
														    """The command `transformers-cli add-new-model` is deprecated and will be removed in v5 of Transformers. """
														    """It is not actively maintained anymore, so might give a result that won't pass all tests and quality """
														    """checks, you should use `transformers-cli add-new-model-like` instead."""					)
														if not _has_cookiecutter:
																					raise ImportError(
																					    """Model creation dependencies are required to use the `add_new_model` command. Install them by running """
																					    """the following at the root of your `transformers` clone:\n\n\t$ pip install -e .[modelcreation]\n"""					)
														# Ensure that there is no other `cookiecutter-template-xxx` directory in the current working directory
														lowerCamelCase__ :     List[Any]	  =	[directory for directory in os.listdir() if """cookiecutter-template-""" == directory[:22]]
														if len(UpperCamelCase__					) > 0:
																					raise ValueError(
																					    """Several directories starting with `cookiecutter-template-` in current working directory. """
																					    """Please clean your directory by removing all folders starting with `cookiecutter-template-` or """
																					    """change your working directory."""					)

														lowerCamelCase__ :     int	  =	(
														    Path(UpperCamelCase__					).parent.parent.parent.parent if self._path is None else Path(self._path					).parent.parent
														)
														lowerCamelCase__ :     int	  =	path_to_transformer_root / """templates""" / """adding_a_new_model"""

														# Execute cookiecutter
														if not self._testing:
																					cookiecutter(str(UpperCamelCase__					)					)
														else:
																					with open(self._testing_file      ,							"""r"""					) as configuration_file:
																												lowerCamelCase__ :     List[str]	  =	json.load(UpperCamelCase__					)

																					cookiecutter(
																					    str(path_to_cookiecutter if self._path is None else self._path					)      ,							no_input=UpperCamelCase__      ,							extra_context=UpperCamelCase__      ,							)

														lowerCamelCase__ :     Optional[Any]	  =	[directory for directory in os.listdir() if """cookiecutter-template-""" in directory[:22]][0]

														# Retrieve configuration
														with open(directory + """/configuration.json"""      ,							"""r"""					) as configuration_file:
																					lowerCamelCase__ :     int	  =	json.load(UpperCamelCase__					)

														lowerCamelCase__ :     Tuple	  =	configuration["""lowercase_modelname"""]
														lowerCamelCase__ :     int	  =	configuration["""generate_tensorflow_pytorch_and_flax"""]
														os.remove(F'''{directory}/configuration.json'''					)

														lowerCamelCase__ :     Union[str, Any]	  =	"""PyTorch""" in generate_tensorflow_pytorch_and_flax
														lowerCamelCase__ :     Union[str, Any]	  =	"""TensorFlow""" in generate_tensorflow_pytorch_and_flax
														lowerCamelCase__ :     Tuple	  =	"""Flax""" in generate_tensorflow_pytorch_and_flax

														lowerCamelCase__ :     List[str]	  =	F'''{path_to_transformer_root}/src/transformers/models/{lowercase_model_name}'''
														os.makedirs(UpperCamelCase__      ,							exist_ok=UpperCamelCase__					)
														os.makedirs(F'''{path_to_transformer_root}/tests/models/{lowercase_model_name}'''      ,							exist_ok=UpperCamelCase__					)

														# Tests require submodules as they have parent imports
														with open(F'''{path_to_transformer_root}/tests/models/{lowercase_model_name}/__init__.py'''      ,							"""w"""					):
																					pass

														shutil.move(
														    F'''{directory}/__init__.py'''      ,							F'''{model_dir}/__init__.py'''      ,							)
														shutil.move(
														    F'''{directory}/configuration_{lowercase_model_name}.py'''      ,							F'''{model_dir}/configuration_{lowercase_model_name}.py'''      ,							)

														def remove_copy_lines(UpperCamelCase__:    Optional[int]					):
																					with open(UpperCamelCase__      ,							"""r"""					) as f:
																												lowerCamelCase__ :     Union[str, Any]	  =	f.readlines()
																					with open(UpperCamelCase__      ,							"""w"""					) as f:
																												for line in lines:
																																			if "# Copied from transformers." not in line:
																																										f.write(UpperCamelCase__					)

														if output_pytorch:
																					if not self._testing:
																												remove_copy_lines(F'''{directory}/modeling_{lowercase_model_name}.py'''					)

																					shutil.move(
																					    F'''{directory}/modeling_{lowercase_model_name}.py'''      ,							F'''{model_dir}/modeling_{lowercase_model_name}.py'''      ,							)

																					shutil.move(
																					    F'''{directory}/test_modeling_{lowercase_model_name}.py'''      ,							F'''{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_{lowercase_model_name}.py'''      ,							)
														else:
																					os.remove(F'''{directory}/modeling_{lowercase_model_name}.py'''					)
																					os.remove(F'''{directory}/test_modeling_{lowercase_model_name}.py'''					)

														if output_tensorflow:
																					if not self._testing:
																												remove_copy_lines(F'''{directory}/modeling_tf_{lowercase_model_name}.py'''					)

																					shutil.move(
																					    F'''{directory}/modeling_tf_{lowercase_model_name}.py'''      ,							F'''{model_dir}/modeling_tf_{lowercase_model_name}.py'''      ,							)

																					shutil.move(
																					    F'''{directory}/test_modeling_tf_{lowercase_model_name}.py'''      ,							F'''{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_tf_{lowercase_model_name}.py'''      ,							)
														else:
																					os.remove(F'''{directory}/modeling_tf_{lowercase_model_name}.py'''					)
																					os.remove(F'''{directory}/test_modeling_tf_{lowercase_model_name}.py'''					)

														if output_flax:
																					if not self._testing:
																												remove_copy_lines(F'''{directory}/modeling_flax_{lowercase_model_name}.py'''					)

																					shutil.move(
																					    F'''{directory}/modeling_flax_{lowercase_model_name}.py'''      ,							F'''{model_dir}/modeling_flax_{lowercase_model_name}.py'''      ,							)

																					shutil.move(
																					    F'''{directory}/test_modeling_flax_{lowercase_model_name}.py'''      ,							F'''{path_to_transformer_root}/tests/models/{lowercase_model_name}/test_modeling_flax_{lowercase_model_name}.py'''      ,							)
														else:
																					os.remove(F'''{directory}/modeling_flax_{lowercase_model_name}.py'''					)
																					os.remove(F'''{directory}/test_modeling_flax_{lowercase_model_name}.py'''					)

														shutil.move(
														    F'''{directory}/{lowercase_model_name}.md'''      ,							F'''{path_to_transformer_root}/docs/source/en/model_doc/{lowercase_model_name}.md'''      ,							)

														shutil.move(
														    F'''{directory}/tokenization_{lowercase_model_name}.py'''      ,							F'''{model_dir}/tokenization_{lowercase_model_name}.py'''      ,							)

														shutil.move(
														    F'''{directory}/tokenization_fast_{lowercase_model_name}.py'''      ,							F'''{model_dir}/tokenization_{lowercase_model_name}_fast.py'''      ,							)

														from os import fdopen, remove
														from shutil import copymode, move
														from tempfile import mkstemp

														def replace(UpperCamelCase__:    str      ,							UpperCamelCase__:    str      ,							UpperCamelCase__:    List[str]					):
																					# Create temp file
																					lowerCamelCase__  ,		lowerCamelCase__ :     Any	  =	mkstemp()
																					lowerCamelCase__ :     Tuple	  =	False
																					with fdopen(UpperCamelCase__      ,							"""w"""					) as new_file:
																												with open(UpperCamelCase__					) as old_file:
																																			for line in old_file:
																																										new_file.write(UpperCamelCase__					)
																																										if line_to_copy_below in line:
																																																	lowerCamelCase__ :     int	  =	True
																																																	for line_to_copy in lines_to_copy:
																																																								new_file.write(UpperCamelCase__					)

																					if not line_found:
																												raise ValueError(F'''Line {line_to_copy_below} was not found in file.'''					)

																					# Copy the file permissions from the old file to the new file
																					copymode(UpperCamelCase__      ,							UpperCamelCase__					)
																					# Remove original file
																					remove(UpperCamelCase__					)
																					# Move new file
																					move(UpperCamelCase__      ,							UpperCamelCase__					)

														def skip_units(UpperCamelCase__:    Optional[int]					):
																					return (
																					    ("generating PyTorch" in line and not output_pytorch)
																					    or ("generating TensorFlow" in line and not output_tensorflow)
																					    or ("generating Flax" in line and not output_flax)
																					)

														def replace_in_files(UpperCamelCase__:    List[str]					):
																					with open(UpperCamelCase__					) as datafile:
																												lowerCamelCase__ :     int	  =	[]
																												lowerCamelCase__ :     Tuple	  =	False
																												lowerCamelCase__ :     int	  =	False
																												for line in datafile:
																																			if "# To replace in: " in line and "##" not in line:
																																										lowerCamelCase__ :     List[str]	  =	line.split("""\""""					)[1]
																																										lowerCamelCase__ :     List[str]	  =	skip_units(UpperCamelCase__					)
																																			elif "# Below: " in line and "##" not in line:
																																										lowerCamelCase__ :     List[Any]	  =	line.split("""\""""					)[1]
																																										lowerCamelCase__ :     Union[str, Any]	  =	skip_units(UpperCamelCase__					)
																																			elif "# End." in line and "##" not in line:
																																										if not skip_file and not skip_snippet:
																																																	replace(UpperCamelCase__      ,							UpperCamelCase__      ,							UpperCamelCase__					)

																																										lowerCamelCase__ :     Union[str, Any]	  =	[]
																																			elif "# Replace with" in line and "##" not in line:
																																										lowerCamelCase__ :     str	  =	[]
																																			elif "##" not in line:
																																										lines_to_copy.append(UpperCamelCase__					)

																					remove(UpperCamelCase__					)

														replace_in_files(F'''{directory}/to_replace_{lowercase_model_name}.py'''					)
														os.rmdir(UpperCamelCase__					)

