code: def phong_renderer_from_pinhole_cam(cam, device="cpu"):
      focal_length = torch.tensor([[cam.fx, cam.fy]])
      principal_point = torch.tensor(
          [[cam.width - cam.cx, cam.height - cam.cy]]
      )  # In PyTorch3D, we assume that +X points left, and +Y points up and +Z points out from the image plane.
      image_size = torch.tensor([[cam.height, cam.width]])
      cameras = PerspectiveCameras(
          focal_length=focal_length,
          principal_point=principal_point,
          in_ndc=False,
          image_size=image_size,
          device=device,
      )
      lights = PointLights(device=device, location=((2.0, 2.0, -2.0),))
      raster_settings = RasterizationSettings(
          image_size=(cam.height, cam.width),
          blur_radius=0.0,
          faces_per_pixel=1,
      )
      silhouette_renderer = MeshRenderer(
          rasterizer=MeshRasterizer(
              cameras=cameras, raster_settings=raster_settings
          ),
          shader=HardPhongShader(
              device=device, cameras=cameras, lights=lights
          ),
      )
      return silhouette_renderer
  
file_path: ml-neuman/utils/render_utils.py
imports: import random
  import numpy
  import torch
  import torch.nn.functional
  from pytorch3d.structures import Meshes
  from pytorch3d.renderer import RasterizationSettings, MeshRenderer, MeshRasterizer, HardPhongShader, PointLights, TexturesVertex, PerspectiveCameras
  from PIL import Image
  from cameras.camera_pose import CameraPose
  from utils import ray_utils
  from utils.constant import DEFAULT_GEO_THRESH
  from geometry import transformations
label_desc: Use image node_id 8 for calling a global function with example usage: phong_renderer_from_pinhole_cam(cam, device) and returns: silhouette_renderer