tensorboard

import torch
from torch.utils.tensorboard import SummaryWriter
import matplotlib.pyplot as plt
import numpy as np


def main():
    log_path = './log'
    logger = SummaryWriter(log_path)

    fig, axes = plt.subplots(4, 1, squeeze=False)
    for i in range(4):
        img = np.arange(10000).reshape((100, 100))
        axes[i][0].imshow(img)

    audio = torch.randn(10000)

    for step in range(1000):
        if step % 10 == 0:
            logger.add_scalar("Loss/loss1", 2 + step, step)
            logger.add_scalar("Loss/loss2", 2 + step, step)
            logger.add_figure("fig_tag", fig, step)
            logger.add_audio("audio_tag", audio / max(abs(audio)), step, sample_rate=22050)


if __name__ == '__main__':
    main()

tensorboard --logdir=log --bind_all

没有bind_all：TensorBoard 2.5.0 at http://localhost:6006/ (Press CTRL+C to quit)
有bind_all： TensorBoard 2.5.0 at http://N705:6006/ (Press CTRL+C to quit)