thanks, i am getting below error  trying to print shape
def train_epoch(
model,
data_loader,
loss_fn,
optimizer,
device,
scheduler,
n_examples
):
model = xlnet_model.train()
losses = []
correct_predictions = 0
for d in data_loader:
input_ids = d[“input_ids”].reshape(4,512).to(device)
print(d[‘input_ids’].shape)
attention_mask = d[“attention_mask”].to(device)
labels = d[“labels”].to(device)
outputs = xlnet_model(input_ids=input_ids, attention_mask=attention_mask)
_, preds = torch.max(outputs, dim=1)
loss = loss_fn(outputs, labels)
correct_predictions += torch.sum(preds == labels)
losses.append(loss.item())
loss.backward()
nn.utils.clip_grad_norm_(model.parameters(), max_norm=1.0)
optimizer.step()
scheduler.step()
optimizer.zero_grad()

return correct_predictions.double() / n_examples, np.mean(losses)
error:ValueError: not enough values to unpack (expected 2, got 1)