class_docstr: Samples a fixed number of points and features from a point cloud
  (functional name: :obj:`fixed_points`).
  
  Args:
      num (int): The number of points to sample.
      replace (bool, optional): If set to :obj:`False`, samples points
          without replacement. (default: :obj:`True`)
      allow_duplicates (bool, optional): In case :obj:`replace` is
          :obj`False` and :obj:`num` is greater than the number of points,
          this option determines whether to add duplicated nodes to the
          output points or not.
          In case :obj:`allow_duplicates` is :obj:`False`, the number of
          output points might be smaller than :obj:`num`.
          In case :obj:`allow_duplicates` is :obj:`True`, the number of
          duplicated points are kept to a minimum. (default: :obj:`False`)
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code: def __repr__(self) -> str:
      return f"{self.__class__.__name__}({self.num}, replace={self.replace})"
  
file_path: pytorch_geometric/torch_geometric/transforms/fixed_points.py
imports: import math
  import re
  import numpy
  import torch
  from torch import Tensor
  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 3 for calling the FixedPoints obj's underlying member method code with example usage: obj.__repr__() and returns: self, str, self, str, self, str