卷积神经网络实例

    import torch
    import torch.nn as nn
    import torchvision.datasets as dsets
    import torchvision.transforms as transforms
    from torch.autograd import Variable
    import time ,os
    
    #卷积网络参数，迭代次数，一批量的样本数，学习率，准确率，时间成本
    #迭代次数*一批量的样本数 = 总样本数
    epochs = 10
    batch_size = 100
    learning_rate = [0.001, 0.005, 0.01, 0.05, 0.1]
    accuracy = []
    time_cost = []
    
    os.environ["CUDA_DEVIC_ORDER"] = "PCI_BUS_ID"#指定使用某一块GPU，编号从0号开始
    os.environ["CUDA_VISIBLE_DEVICES"] = "0"
    
    #Minst数据集下载以及导入，root下载目录，是否设为训练集，转变成Tensor
    train_dataset = dsets.MNIST(root='.