I have tried to use tensorboard to visualize a model. I was following the pytorch.org tutorial. Here is the code for dataloader.
writer_train = SummaryWriter('runs/training')
train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=config.train_batch_size, shuffle=True,
num_workers=config.num_workers, pin_memory=True)
images, labels = next(iter(train_loader))
writer_train.graph_model(light_net, images)
and I got this error in the iter line.
images, labels = next(iter(train_loader)) ValueError: too many values to unpack (expected 2)
The error is likely caused by the use of a built-in function instead of the .next()
method of the train_loader
object.
next()
and iter()
are builtin methods in Python
. See from the docs iter and next.
In the tutorial is shows the following
# get some random training images
dataiter = iter(trainloader)
images, labels = dataiter.next()
Where it uses the next()
method to unpack values into the 2 variables. This is not the same as your usage of next(iter(train_loader))
. Do it in the way as shown and it should solve your problem.