Pytorch中如何使用tensorboard

这期内容当中小编将会给大家带来有关Pytorch中如何使用tensorboard，文章内容丰富且以专业的角度为大家分析和叙述，阅读完这篇文章希望大家可以有所收获。

安装:pip install tensorboard
或者安装tensorflow,默认CPU版本即可:pip install tensorflow
运行:tensorboard --logdir=runs
实验代码:

import torchimport torchvisionfrom torch.utils.tensorboard import SummaryWriterfrom torchvision import datasets, transforms# Writer will output to ./runs/ directory by defaultwriter = SummaryWriter()transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (0.5,))])trainset = datasets.MNIST('mnist_train', train=True, download=True, transform=transform)trainloader = torch.utils.data.DataLoader(trainset, batch_size=64, shuffle=True)model = torchvision.models.resnet50(False)# Have ResNet model take in grayscale rather than RGBmodel.conv1 = torch.nn.Conv2d(1, 64, kernel_size=7, stride=2, padding=3, bias=False)images, labels = next(iter(trainloader))grid = torchvision.utils.make_grid(images)writer.add_image('images', grid, 0)writer.add_graph(model, images)writer.close()'''tensorboard --logdir=runs'''

运行完成之后在命令行下输入:tensorboard --logdir=runs
根据提示,打开链接: http://localhost:6006/
命令行下的输出是:

(base) PS C:\Users\chenxuqi\Desktop\News4cxq\tensorboard4cxq> conda activate pytorch_1.7.1_cu102(pytorch_1.7.1_cu102) PS C:\Users\chenxuqi\Desktop\News4cxq\tensorboard4cxq> tensorboard --logdir=runsTensorFlow installation not found - running with reduced feature set.Serving TensorBoard on localhost; to expose to the network, use a proxy or pass --bind_allTensorBoard 2.4.0 at http://localhost:6006/ (Press CTRL+C to quit)

浏览器下显示效果展示:

上述就是小编为大家分享的Pytorch中如何使用tensorboard了，如果刚好有类似的疑惑，不妨参照上述分析进行理解。如果想知道更多相关知识，欢迎关注行业资讯频道。