PyTorch Tensorboard使用

https://pytorch.org/docs/stable/tensorboard.html

from torch.utils.tensorboard import SummaryWriter
import numpy as np
writer = SummaryWriter() # 创建一个记录器
'''
add_scalar(tag, scalar_value, global_step=None, walltime=None)
- tag：数据标签名
- scalar_value：记录值 (python:float or string/blobname) 
- global_step：记录第几个step 
'''
for n_iter in range(100):
    writer.add_scalar('Loss/train', np.random.random(), n_iter)
    writer.add_scalar('Loss/test', np.random.random(), n_iter)
    writer.add_scalar('Accuracy/train', np.random.random(), n_iter)
    writer.add_scalar('Accuracy/test', np.random.random(), n_iter)

from torch.utils.tensorboard import SummaryWriter
writer = SummaryWriter()
r = 5
for i in range(100):
    writer.add_scalars('run_14h', {'xsinx':i*np.sin(i/r),
                                    'xcosx':i*np.cos(i/r),
                                    'tanx': np.tan(i/r)}, i)
writer.close()
# This call adds three values to the same scalar plot with the tag
# 'run_14h' in TensorBoard's scalar section.