Looks like max() returned a tuple with one element. So, choosing the first element solved the issue. The corrected code as of PyTorch 0.4 is as below:
import torch


def normalize(x):
    x_normed = x / x.max(0, keepdim=True)[0]
    return x_normed


t = torch.tensor([[1000, 10, 0.5], [765, 5, 0.35], [800, 7, 0.09]])
print(normalize(t))