版权声明:本文为博主原创文章,未经博主允许不得转载。 https://blog.csdn.net/hao5335156/article/details/82999108
import torch
from tensorboardX import SummaryWriter
#writer = SummaryWriter()
# 声明writer对象,保存的文件夹,默认是runs文件夹(在当前目录运行tensorboard --logdir runs)
#在当前目录运行tensorboard --logdir log
writer = SummaryWriter(log_dir='./log', comment='test_net')
x = torch.FloatTensor([100])
y = torch.FloatTensor([200])
for epoch in range(100):
x /= 2.0
y /= 2.0
loss = y - x
print(loss)
#添加正常显示
writer.add_histogram('zz/x', x, epoch)
writer.add_histogram('zz/y', y, epoch)
#添加标量化显示
writer.add_scalar('data/x', x, epoch)
writer.add_scalar('data/y', y, epoch)
writer.add_scalar('data/loss', loss, epoch)
#添加标量组,一起显示
writer.add_scalars('data/scalar_group', {'x': x,
'y': y,
'loss': loss}, epoch)
writer.add_text('zz/text', 'zz: this is epoch ' + str(epoch), epoch)