content: import torch
  from typing import Union, List, Optional, Tuple, Dict
  import nvdiffrast.torch as dr
  import utils3d
  class RastContext:
      def __init__(self, backend='cuda'):
          self.backend = backend
  
  def rasterize_triangle_faces(
      ctx: RastContext,
      vertices: torch.Tensor,
      faces: torch.Tensor,
      width: int,
      height: int,
      attr: torch.Tensor = None,
      uv: torch.Tensor = None,
      texture: torch.Tensor = None,
      model: torch.Tensor = None,
      view: torch.Tensor = None,
      projection: torch.Tensor = None,
      antialiasing: Union[bool, List[int]] = True,
      diff_attrs: Union[None, List[int]] = None,
  ) -> Dict[str, torch.Tensor]:
      """
      Rasterize a mesh with vertex attributes.
      """
      assert vertices.ndim == 3
      assert faces.ndim == 2
  
      # Handle vertices dimensions
      if vertices.shape[-1] == 2:
          vertices = torch.cat([vertices, torch.zeros_like(vertices[..., :1]), torch.ones_like(vertices[..., :1])], dim=-1)
      elif vertices.shape[-1] == 3:
          vertices = torch.cat([vertices, torch.ones_like(vertices[..., :1])], dim=-1)
      elif vertices.shape[-1] == 4:
          pass
      else:
          raise ValueError(f'Wrong shape of vertices: {vertices.shape}')
      
      # Calculate MVP matrix
      mvp = projection if projection is not None else torch.eye(4, device=vertices.device)
      if view is not None:
          mvp = mvp @ view
      if model is not None:
          mvp = mvp @ model
  
      # Transform vertices to clip space
      pos_clip = vertices @ mvp.transpose(-1, -2)
      faces = faces.contiguous()
      if attr is not None:
          attr = attr.contiguous()
  
      # Rasterize
      rast_out, rast_db = dr.rasterize(ctx.nvd_ctx, pos_clip, faces, resolution=[height, width], grad_db=True)
  
      # Extract basic outputs
      face_id = rast_out[..., 3].flip(1)
      depth = rast_out[..., 2].flip(1)
      mask = (face_id > 0).float()
      depth = (depth * 0.5 + 0.5) * mask + (1.0 - mask)
  
      ret = {
          'depth': depth,
          'mask': mask,
          'face_id': face_id,
      }
  
      # Handle attribute interpolation
      if attr is not None:
          image, image_dr = dr.interpolate(attr, rast_out, faces, rast_db, diff_attrs=diff_attrs)
          
          if antialiasing == True:
              image = dr.antialias(image, rast_out, pos_clip, faces)
          elif isinstance(antialiasing, list):
              aa_image = dr.antialias(image[..., antialiasing], rast_out, pos_clip, faces)
              image[..., antialiasing] = aa_image
  
          image = image.flip(1).permute(0, 3, 1, 2)
          ret['image'] = image
  
      # Handle UV mapping
      if uv is not None:
          uv_map, uv_map_dr = dr.interpolate(uv, rast_out, faces, rast_db, diff_attrs='all')
          ret['uv'] = uv_map
          ret['uv_dr'] = uv_map_dr
  
          if texture is not None:
              texture_map = dr.texture(texture, uv_map, uv_map_dr)
              ret['texture'] = texture_map.flip(1).permute(0, 3, 1, 2)
  
      # Handle derivatives
      if diff_attrs is not None:
          image_dr = image_dr.flip(1).permute(0, 3, 1, 2)
          ret['image_dr'] = image_dr
  
      return ret 