import torch
import numpy as np

def get_positional_encoding(n_positions, n_dimensions, device='cpu'):
  # TODO: implement positional encoding
  positional_encoding = np.zeros((n_positions, n_dimensions)) # placeholder
  pass
  # output shape: (seqlen, hiddendim)
  return torch.tensor(positional_encoding, dtype=torch.float, device=device)