我正在尝试在 CIFAR10 数据集上训练一个非常基本的 CNN 并收到以下错误:AttributeError: 'CrossEntropyLoss' object has no attribute 'backward'
criterion =nn.CrossEntropyLoss
optimizer=optim.SGD(net.parameters(),lr=0.001,momentum=0.9)
for epoch in range(2): # loop over the dataset multiple times
running_loss = 0.0
for i, data in enumerate(trainloader, 0):
# get the inputs
inputs, labels = data
# wrap them in Variable
inputs, labels = Variable(inputs), Variable(labels)
# zero the parameter gradients
optimizer.zero_grad()
# forward + backward + optimize
outputs = net(inputs)
loss = criterion(outputs, labels)
loss.backward()
optimizer.step()
# print statistics
running_loss += loss.data[0]
if …Run Code Online (Sandbox Code Playgroud) python neural-network deep-learning conv-neural-network pytorch
当我们说“深度神经网络的非线性”时,在这种情况下“非线性”一词实际上是什么意思?
此外,激活函数的目的是将非线性引入网络。这种非线性意味着什么?(我是深度学习的新手。)