code: def __init__(self, datapipe, matrix, fanouts):
      super().__init__(datapipe)
      self.matrix = matrix
      # Convert fanouts to a list of tensors.
      self.fanouts = []
      for fanout in fanouts:
          if not isinstance(fanout, torch.Tensor):
              fanout = torch.LongTensor([int(fanout)])
          self.fanouts.insert(0, fanout)
  
imports: import argparse
  from functools import partial
  import dgl.graphbolt
  import dgl.sparse
  import torch
  import torch.nn
  import torch.nn.functional
  import torchmetrics.functional
  from dgl.graphbolt.subgraph_sampler import SubgraphSampler
  from torch.utils.data import functional_datapipe
label_desc: Use image node_id 1 to create a new SparseNeighborSampler object from inherited base classes: SubgraphSampler with example: obj = SparseNeighborSampler(datapipe, matrix, fanouts)