pytorch SummaryWriter保存日志的方法

from tensorboardX import SummaryWriter
 writer = SummaryWriter(logPath)
 ...
 writer.close()

from tensorboardX import SummaryWriter
import numpy as np

writer = SummaryWriter('run/logs')

max_epoch = 100
for x in range(max_epoch):

    writer.add_scalar('t/y=2x', x * 2, x)    #x*2为y轴数据，x为x轴数据
    writer.add_scalar('t/y=pow_2_x', 2^x, x)
    writer.add_scalars('scalar_group', {"xsinx": x * np.sin(x),
                                     "xcosx": x * np.cos(x)}, x)
    writer.close()

from tensorboardX import SummaryWriter
import numpy as np
img = np.zeros((3, 100, 100))
img[0] = np.arange(0, 10000).reshape(100, 100) / 10000
img[1] = 1 - np.arange(0, 10000).reshape(100, 100) / 10000

img_HWC = np.zeros((100, 100, 3))
img_HWC[:, :, 0] = np.arange(0, 10000).reshape(100, 100) / 10000
img_HWC[:, :, 1] = 1 - np.arange(0, 10000).reshape(100, 100) / 10000

writer = SummaryWriter('run/logs')
writer.add_image('my_image', img, 0)

# If you have non-default dimension setting, set the dataformats argument.
writer.add_image('my_image_HWC', img_HWC, 0, dataformats='HWC')
writer.close()

# 每个epoch，记录梯度，权值
for name, param in net.named_parameters():
    writer.add_histogram(name + '_grad', param.grad, epoch)
    writer.add_histogram(name + '_data', param, epoch)

writer = SummaryWriter(comment='test_your_comment', filename_suffix="_test_your_filename_suffix")
# 模型
fake_img = torch.randn(1, 3, 32, 32)
yolo = Yolo(classes=2)
writer.add_graph(yolo, fake_img)
writer.close()