Pytorch 下使用 tensorboard 可视化

最新推荐文章于 2025-02-04 01:26:34 发布

Hansry

最新推荐文章于 2025-02-04 01:26:34 发布

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分类专栏： Tensorflow/Pytorch

本文链接：https://blog.youkuaiyun.com/Hansry/article/details/83058971

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这篇博客介绍了如何在Pytorch环境中安装并使用Tensorboard进行数据和模型可视化的详细步骤，包括安装过程、运行代码、查看生成的日志以及如何在浏览器中打开和交互展示结果。

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1. 安装tensorboard

pip install tensorboardX

2. 运行代码

import torch
import torchvision.utils as vutils
import numpy as np
import torchvision.models as models
from torchvision import datasets
from tensorboardX import SummaryWriter

resnet18 = models.resnet18(False)
writer = SummaryWriter()
sample_rate = 44100
freqs = [262, 294, 330, 349, 392, 440, 440, 440, 440, 440, 440]

for n_iter in range(100):

    dummy_s1 = torch.rand(1)
    dummy_s2 = torch.rand(1)
    # data grouping by `slash`
    writer.add_scalar('data/scalar1', dummy_s1[0], n_iter)
    writer.add_scalar('data/scalar2', dummy_s2[0], n_iter)

    writer.add_scalars('data/scalar_group', {'xsinx': n_iter * np.sin(n_iter),
                                             'xcosx': n_iter * np.cos(n_iter),
                                             'arctanx':