#primary training code import numpy as np import torch import os.path as osp from training_utils.engine_pointnet import EnginePointnet from training_utils.find_top_models import find_top_models from kaolin.models.PointNet import PointNetClassifier as Pointnet from config.config_triumf_pointnet_adam import config if __name__ == '__main__': # Initialization model = Pointnet(**config.model_kwargs) engine = EnginePointnet(model, config) # Training engine.train() # Save network engine.save_state() #Validation models = find_top_models(engine.dirpath, 5) for model in models: engine.load_state(osp.join(engine.dirpath, model)) engine.validate("validation", name=osp.splitext(model)[0])