PyTorch 是一个深度学习框架,而 torchvision 则包含了许多用于计算机视觉的工具和数据集。 importtorchimporttorchvision.transformsastransformsfromtorchvisionimportdatasetsimporttorch.nnasnnimporttorch.optimasoptim 1. 2. 3. 4. 5. torch:PyTorch 的核心库。 torchvision.transforms:包含图像转换的工具。 torchvision.dat...
from torchvision import datasets, transforms # Define a transform to normalize the data transform = transforms.Compose([transforms.ToTensor(), transforms.Normalize((0.5,), (0.5,)), ]) # Download and load the training data trainset = datasets.MNIST('~/.pytorch/MNIST_data/', download=True, tr...
跑通环境:win11 + pycharm2023 + pytorch 2.1.0/cu121 importtorchimporttorch.nnasnnimporttorch.nn.functionalasFfromeinopsimportrearrangefromtypingimportListimportrandomimportmathfromtorchvisionimportdatasets,transformsfromtorch.utils.dataimportDataLoaderfromtimm.utilsimportModelEmaV3fromtqdmimporttqdmimportmatplotlib.p...
1.数据预处理 (1)导包 importosimportmatplotlib.pyplotasplt %matplotlib inlineimportnumpyasnpimporttorchfromtorchimportnnimporttorch.optimasoptimimporttorchvision#pip install torchvisionfromtorchvisionimporttransforms, models, datasets#https://pytorch.org/docs/stable/torchvision/index.htmlimportimageioimporttimeimp...
import torch from torchvision import datasets, transforms from torch.utils.data import DataLoader from model import TokensToTokenViT # 假设已定义了TokensToTokenViT模型 # 数据加载和预处理 transform = transforms.Compose([ transforms.Resize(256), transforms.CenterCrop(224), transforms.ToTensor(), transform...
GANs from Scratch 1: A deep introduction. With code in PyTorch and TensorFlow 修改文章代码中的错误后的代码如下: importtorchfromtorchimportnn, optimfromtorch.autograd.variableimportVariablefromtorchvisionimporttransforms, datasetsimportmatplotlib.pyplotasplt ...
~/anaconda3/lib/python3.7/site-packages/torchvision/__init__.py in <module> 1 from torchvision import models ---> 2 from torchvision import datasets 3 from torchvision import transforms 4 from torchvision import utils 5 ~/anaconda3/lib/python3.7/site-packages/torchvision/datasets/__init__.py ...
importnumpyasnpimporttorchimporttorch.nnasnnfromtorchvisionimportdatasetsfromtorchvisionimporttransformsfromtorch.utils.data.samplerimportSubsetRandomSampler# Device configurationdevice=torch.device('cuda'iftorch.cuda.is_available()else'cpu') Copy Importing the libraries ...
importnumpyasnpimporttorchimporttorch.nnasnnfromtorchvisionimportdatasetsfromtorchvisionimporttransformsfromtorch.utils.data.samplerimportSubsetRandomSampler# Device configurationdevice=torch.device('cuda'iftorch.cuda.is_available()else'cpu') Copy Loading the Data ...
从trochvision,我们导入datasets和transforms,用于准备数据和做些数据变换。我们从torch.nn导入funcational as F。从torch.utils.data导入DataLoader,用于创建mini-batch sizes(可理解成batch_size大小的数据块)。从torchvision.utisl导入save_image函数,用于保存一些fake samples(模型生成图片)。从math,导入log2和sqrt函数...