class_docstr: Uniformly samples a fixed number of points on the mesh faces according
  to their face area (functional name: :obj:`sample_points`).
  
  Args:
      num (int): The number of points to sample.
      remove_faces (bool, optional): If set to :obj:`False`, the face tensor
          will not be removed. (default: :obj:`True`)
      include_normals (bool, optional): If set to :obj:`True`, then compute
          normals for each sampled point. (default: :obj:`False`)
code: def __init__(
      self,
      num: int,
      remove_faces: bool = True,
      include_normals: bool = False,
  ):
      self.num = num
      self.remove_faces = remove_faces
      self.include_normals = include_normals
  
file_path: pytorch_geometric/torch_geometric/transforms/sample_points.py
imports: import torch
  from torch_geometric.data import Data
  from torch_geometric.data.datapipes import functional_transform
  from torch_geometric.transforms import BaseTransform
label_desc: Use image node_id 1 to create a new SamplePoints object from inherited base classes: BaseTransform with example: obj = SamplePoints(num, remove_faces, include_normals)