



def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				lowercase__					:   Optional[Any]													=					set()
				# edges = list of graph's edges
				lowercase__					:   Dict													=					get_edges(lowerCamelCase__						)

				# While there are still elements in edges list, take an arbitrary edge
				# (from_node, to_node) and add his extremity to chosen_vertices and then
				# remove all arcs adjacent to the from_node and to_node
				while edges:
								lowercase__							,							lowercase__					:   Tuple													=					edges.pop()
								chosen_vertices.add(lowerCamelCase__						)
								chosen_vertices.add(lowerCamelCase__						)
								for edge in edges.copy():
												if from_node in edge or to_node in edge:
																edges.discard(lowerCamelCase__						)
				return chosen_vertices


def  __lowerCamelCase (       lowerCamelCase__						):

				"""simple docstring"""


				lowercase__					:   Optional[int]													=					set()
				for from_node, to_nodes in graph.items():
								for to_node in to_nodes:
												edges.add((from_node, to_node)						)
				return edges


if __name__ == "__main__":
				import doctest

				doctest.testmod()

				# graph = {0: [1, 3], 1: [0, 3], 2: [0, 3, 4], 3: [0, 1, 2], 4: [2, 3]}
				# print(f"Matching vertex cover:\n{matching_min_vertex_cover(graph)}")









from typing import Union

import fire
import torch
from tqdm import tqdm


def  __lowerCamelCase (       lowerCamelCase__					,			lowerCamelCase__ = "cpu"					,			lowerCamelCase__ = None						):

				"""simple docstring"""


				lowercase__					:   Any													=					torch.load(lowerCamelCase__					,			map_location=lowerCamelCase__						)
				for k, v in tqdm(state_dict.items()						):
								if not isinstance(lowerCamelCase__					,			torch.Tensor						):
												raise TypeError("FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin"						)
								lowercase__					:   int													=					v.half()
				if save_path is None:  # overwrite src_path
								lowercase__					:   Optional[Any]													=					src_path
				torch.save(lowerCamelCase__					,			lowerCamelCase__						)


if __name__ == "__main__":
				fire.Fire(convert)




