Python find_top_models示例

示例#1

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

# this must be changed to the model that was used...
from config.config_triumf_pointnet_adam_all_features import config

if __name__ == '__main__':
    # Initialization
    model = Pointnet(**config.model_kwargs) 
    engine = EnginePointnet(model, config)

    #Validation
    dump_path = "/home/dgreen/training_outputs/pointnet/all_features/adam/20200302_002018/"
    models = find_top_models(dump_path, 5)
    print(models)
    for model in models:
        engine.load_state(osp.join(dump_path, model))
        engine.validate("validation", name=osp.splitext(model)[0])

示例#2

文件： triumf_main.py 项目： WatChMaL/GraphNets

import torch
import numpy as np

from models.selector import Model
from training_utils.engine_graph import EngineGraph
from training_utils.find_top_models import find_top_models

from config.config_triumf import config

import os.path as osp

if __name__ == '__main__':
    # Initialization
    model = Model(name=config.model_name, **config.model_kwargs)
    engine = EngineGraph(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])