code: def decimate(tensors, ptr: Tensor, decimation_factor: int):
      """Decimates each element of the given tuple of tensors."""
      idx_decim, ptr_decim = decimation_indices(ptr, decimation_factor)
      tensors_decim = tuple(tensor[idx_decim] for tensor in tensors)
      return tensors_decim, ptr_decim
  
imports: import os.path
  import torch
  import torch.nn.functional
  from torch import Tensor
  from torch.nn import Linear
  from tqdm import tqdm
  import torch_geometric.transforms
  from torch_geometric.datasets import ModelNet
  from torch_geometric.loader import DataLoader
  from torch_geometric.nn import MLP
  from torch_geometric.nn.aggr import MaxAggregation
  from torch_geometric.nn.conv import MessagePassing
  from torch_geometric.nn.pool import knn_graph
  from torch_geometric.nn.pool.decimation import decimation_indices
  from torch_geometric.typing import WITH_TORCH_CLUSTER
  from torch_geometric.utils import softmax
label_desc: Use image node_id 1 for calling a global function with example usage: decimate(tensors, ptr, decimation_factor) and returns: tensors_decim,  ptr_decim