I’ve read all the similar topics here, but can’t figures this out. How do I change my labels (y_train) to the correct dimensions?
data = ImageFolder(data_dir, transform=transforms.Compose([transforms.Resize((224,224)),transforms.ToTensor()]))
trainloader = torch.utils.data.DataLoader(data, batch_size=3600,
shuffle=True, num_workers=2)
dataiter = iter(trainloader)
x_train, y_train = dataiter.next()
print(x_train.size())
print(y_train.size())
torch.Size([3600, 3, 224, 224])
torch.Size([3600])
class Net(torch.nn.Module):
def __init__(self):
super().__init__()
# here we set up the tensors......
self.layer1 = torch.nn.Linear(224, 12)
self.layer2 = torch.nn.Linear(12, 10)
def forward(self, x):
# here we define the (forward) computational graph,
# in terms of the tensors, and elt-wise non-linearities
x = F.relu(self.layer1(x))
x = self.layer2(x)
return x
net = Net()
y = net.forward(x_train)
lossFn = torch.nn.CrossEntropyLoss()
loss = lossFn(y, y_train)
print(loss)
