code: def create_camera_dimensions(device, dtype):
      n_cams1 = 3
      n_cams2 = 2
      heights: torch.Tensor = torch.cat(
          (
              torch.tensor([200] * n_cams1, device=device, dtype=dtype),
              torch.tensor([100] * n_cams2, device=device, dtype=dtype),
          )
      )
      widths: torch.Tensor = torch.cat(
          (
              torch.tensor([300] * n_cams1, device=device, dtype=dtype),
              torch.tensor([400] * n_cams2, device=device, dtype=dtype),
          )
      )
      num_img_rays: torch.Tensor = torch.cat(
          (
              torch.tensor([10] * n_cams1, device=device, dtype=dtype),
              torch.tensor([15] * n_cams2, device=device, dtype=dtype),
          )
      )
      return heights, widths, num_img_rays
  
imports: import math
  import torch
  from kornia.core import Device
  from kornia.geometry.camera import PinholeCamera
  from kornia.nerf.samplers import RandomGridRaySampler, RandomRaySampler, UniformRaySampler, calc_ray_t_vals, cameras_for_ids, sample_lengths, sample_ray_points
  from kornia.testing import assert_close
label_desc: Use image node_id 1 for calling a global function with example usage: create_camera_dimensions(device, dtype) and returns: heights,  widths,  num_img_rays