一个简洁、好用的Pytorch训练模板

一个简洁、好用的Pytorch训练模板

代码地址：https://github.com/KinglittleQ/Pytorch-Template

怎么使用

1) 更改template.py

替换 __init__方法中的内容，增添自己的模型、优化器、评估器等等.

class Model():

    def __init__(self, args):
        self.writer = tX.SummaryWriter(log_dir=None, comment='')
        self.train_logger = None  # not neccessary
        self.eval_logger = None  # not neccessary
        self.args = args  # not neccessary

        self.step = 0
        self.epoch = 0
        self.best_error = float('Inf')

        self.model = None
        self.optimizer = None
        self.criterion = None
        self.metric = None

        self.train_loader = None
        self.test_loader = None

        self.device = None

        self.ckpt_dir = None
        self.log_per_step = None

2) 写部分训练代码

你所需要做的只是写一个简单的for循环：

model = Model()

for epoch in range(n_epochs):
    model.train()
    if (epoch + 1) % eval_per_epoch == 0:
        model.eval()

print('Done!!!')

3) 继续训练

继续训练十分方便，只需要加载之前保存好的模型。

model = Model()
if model_path:
    model.load_state(model_path)

for i in range(n_epochs):
    model.train()
    if model.epoch % eval_per_epoch == 0:
        model.eval()

Example

• LeNet: 训练一个LeNet对MNIST手写数字进行分类

  • 训练过程如下:

    ......
    epoch 1 step 3400   loss 0.0434
    epoch 1 step 3500   loss 0.0331
    epoch 1 step 3600   loss 0.00188
    epoch 1 step 3700   loss 0.00341
    save model at ../modelsest.pth.tar
    save model at ../models1.pth.tar
    epoch 1 error 0.0237
    epoch 2 step 3800   loss 0.0201
    epoch 2 step 3900   loss 0.00523
    epoch 2 step 4000   loss 0.0236
    ......
    

  • 使用tensorboard可视化输出：

    tensorboard --logdir example/LeNet/log
    

    
    

  • 继续训练

    load model from checkpoint/9.pth.tar
    epoch 10    step 33800  loss 0.000128
    epoch 10    step 33900  loss 6.64e-06
    epoch 10    step 34000  loss 0.000613
    epoch 10    step 34100  loss 2.41e-05
    ......