code: def compute_locations(h, w, stride, device):
      shifts_x = torch.arange(
          0, w * stride, step=stride, dtype=torch.float32, device=device
      )
      shifts_y = torch.arange(
          0, h * stride, step=stride, dtype=torch.float32, device=device
      )
      shift_y, shift_x = torch.meshgrid(shifts_y, shifts_x)
      shift_x = shift_x.reshape(-1)
      shift_y = shift_y.reshape(-1)
      locations = torch.stack((shift_x, shift_y), dim=1) + stride // 2
      return locations
  
imports: import functools
  import logging
  import pickle
  import numpy
  import torch
  import torch.distributed
label_desc: Use image node_id 3 for calling a global function with example usage: compute_locations(h, w, stride, device) and returns: locations