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。
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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=runs TensorFlow installation not found - running with reduced feature set. Serving TensorBoard on localhost; to expose to the network, use a proxy or pass --bind_all TensorBoard 2.4.0 at http://localhost:6006/ (Press CTRL+C to quit)
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