code: def test_dimensions(self, device, dtype):
      num_rays = 15
      num_ray_points = 11
      num_dims = 3
      x = torch.rand(
          num_rays, num_ray_points, num_dims, device=device, dtype=dtype
      )
      num_freqs = 10
      pos_encoder = PositionalEncoder(num_dims, num_freqs)
      x_encoded = pos_encoder(x)
      assert x_encoded.shape == (
          num_rays,
          num_ray_points,
          pos_encoder.num_encoded_dims,
      )
  
label_desc: Use image node_id 1 for calling the TestPositionalEncoder obj's underlying member method code with example usage: obj.test_dimensions(device, dtype) without return types