code: def reduce_tensor_elems(
      tensor: torch.Tensor, m=2**24
  ) -> torch.Tensor:
      """Flattens n-dimensional tensors,  selects m elements from it
      and returns the selected elements as tensor. It is used to select
      at most 2**24 for torch.quantile operation, as it is the maximum
      supported number of elements.
      https://github.com/pytorch/pytorch/blob/b9f81a483a7879cd3709fd26bcec5f1ee33577e6/aten/src/ATen/native/Sorting.cpp#L291
  
      Args:
          tensor (torch.Tensor): input tensor from which elements are selected
          m (int): number of maximum tensor elements. Default: 2**24
  
      Returns:
              Tensor: reduced tensor
      """
      tensor = torch.flatten(tensor)
      if len(tensor) > m:
          # select a random subset with m elements.
          perm = torch.randperm(len(tensor), device=tensor.device)
          idx = perm[:m]
          tensor = tensor[idx]
      return tensor
  
imports: from __future__ import annotations
  import logging
  import random
  from enum import Enum
  import torch
  import torch.nn.functional
  from torch import Tensor, nn
  from torchvision import transforms
label_desc: Use image node_id 2 for calling a global function with example usage: reduce_tensor_elems(tensor, m) and returns: tensor