pytorch 无法打乱数据集
pytorch can't shuffle the dataset
我正在尝试使用来自 torchvision 的 mnist 数据集制作一个 ai,并使用 pytorch 制作它,但是当我键入一些打乱数据的代码时,运行 它说:
trainset = torch.utils.data.Dataloader(train, batch_size=10, shuffle=True)
AttributeError: module 'torch.utils.data' has no attribute 'Dataloader'
我尝试了一种不同的方法,但它仍然不起作用,它说:
trainset = torch.autograd.Variable.DataLoader(train, batch_size=10, shuffle=True)
AttributeError: type object 'Variable' has no attribute 'DataLoader'
我使用的代码是:
import torch
import numpy as np
import torchvision
from torchvision import transforms, datasets
train = datasets.MNIST("", train=True, download=True,
transform = transforms.Compose([transforms.ToTensor()]))
test = datasets.MNIST("", train=False, download=True,
transform = transforms.Compose([transforms.ToTensor()]))
trainset = torch.utils.data.Dataloader(train, batch_size=10, shuffle=True)
testset = torch.utils.data.Dataloader(test, batch_size=10, shuffle=True)
for data in trainset:
print(data)
break
此代码的错误:
trainset = torch.utils.data.Dataloader(train, batch_size=10, shuffle=True)
AttributeError: module 'torch.utils.data' has no attribute 'Dataloader'
我试了一个新版本,但还是不行:
import torch
import numpy as np
import torchvision
from torchvision import transforms, datasets
train = datasets.MNIST("", train=True, download=True,
transform = transforms.Compose([transforms.ToTensor()]))
test = datasets.MNIST("", train=False, download=True,
transform = transforms.Compose([transforms.ToTensor()])
trainset = torch.autograd.Variable.DataLoader(train, batch_size=10, shuffle=True)
testset = torch.autograd.Variable.DataLoader(test, batch_size=10, shuffle=True)
for data in trainset:
print(data)
break
此代码的错误:
trainset = torch.autograd.Variable.DataLoader(train, batch_size=10, shuffle=True)
AttributeError: type object 'Variable' has no attribute 'DataLoader'
我仍然很困惑为什么它不起作用,我正在学习教程但它不起作用
您有一个简单的错字:Dataloader
-> DataLoader
(大写 L
)。
尝试:
trainset = torch.utils.data.DataLoader(train, batch_size=10, shuffle=True)
我正在尝试使用来自 torchvision 的 mnist 数据集制作一个 ai,并使用 pytorch 制作它,但是当我键入一些打乱数据的代码时,运行 它说:
trainset = torch.utils.data.Dataloader(train, batch_size=10, shuffle=True)
AttributeError: module 'torch.utils.data' has no attribute 'Dataloader'
我尝试了一种不同的方法,但它仍然不起作用,它说:
trainset = torch.autograd.Variable.DataLoader(train, batch_size=10, shuffle=True)
AttributeError: type object 'Variable' has no attribute 'DataLoader'
我使用的代码是:
import torch
import numpy as np
import torchvision
from torchvision import transforms, datasets
train = datasets.MNIST("", train=True, download=True,
transform = transforms.Compose([transforms.ToTensor()]))
test = datasets.MNIST("", train=False, download=True,
transform = transforms.Compose([transforms.ToTensor()]))
trainset = torch.utils.data.Dataloader(train, batch_size=10, shuffle=True)
testset = torch.utils.data.Dataloader(test, batch_size=10, shuffle=True)
for data in trainset:
print(data)
break
此代码的错误:
trainset = torch.utils.data.Dataloader(train, batch_size=10, shuffle=True)
AttributeError: module 'torch.utils.data' has no attribute 'Dataloader'
我试了一个新版本,但还是不行:
import torch
import numpy as np
import torchvision
from torchvision import transforms, datasets
train = datasets.MNIST("", train=True, download=True,
transform = transforms.Compose([transforms.ToTensor()]))
test = datasets.MNIST("", train=False, download=True,
transform = transforms.Compose([transforms.ToTensor()])
trainset = torch.autograd.Variable.DataLoader(train, batch_size=10, shuffle=True)
testset = torch.autograd.Variable.DataLoader(test, batch_size=10, shuffle=True)
for data in trainset:
print(data)
break
此代码的错误:
trainset = torch.autograd.Variable.DataLoader(train, batch_size=10, shuffle=True)
AttributeError: type object 'Variable' has no attribute 'DataLoader'
我仍然很困惑为什么它不起作用,我正在学习教程但它不起作用
您有一个简单的错字:Dataloader
-> DataLoader
(大写 L
)。
尝试:
trainset = torch.utils.data.DataLoader(train, batch_size=10, shuffle=True)