先上代码
- from torch.utils import tensorboard
- import numpy as np
-
- writer = {
- 'loss': tensorboard.SummaryWriter("./drive/MyDrive/logs/loss"), #必须要不同的writer
- 'acc': tensorboard.SummaryWriter("./drive/MyDrive/logs/acc"),
- 'lr': tensorboard.SummaryWriter("./drive/MyDrive/logs/lr")
- }
-
- data = np.random.random((3, 10)) #生成模拟数据
-
- loss_data = data[0]
- acc_data = data[1]
- lr_data = data[2]
-
- for i in range(10):
- writer['loss'].add_scalar("data", loss_data[i], i) #要想显示在一张图 表格名字要一样!!
- writer['acc'].add_scalar("data", acc_data[i], i)
- writer['lr'].add_scalar("data", lr_data[i], i)
-
- writer['loss'].close()
- writer['acc'].close()
- writer['lr'].close()
- exit()
终端命令:
tensorboard --logdir="drive/mydrive/logs"
运行结果:
要点:
1、每条线一个单独的文件夹
2、每条线一个单独的writer
3、表格名必须相同
屁大点事搞了好久,到处查,都不对!!三句话就能说清楚的,要么搞一大篇,要么代码乱七八糟