class_docstr: An implementation of an in-memory (heterogeneous) neighbor sampler used
  by :class:`~torch_geometric.loader.NeighborLoader`.
class_docstr_tok: ["An","implementation","of","an","in-memory","(","heterogeneous",")","neighbor","sampler","used","by",":","class",":","`","~torch_geometric.loader.NeighborLoader","`","."]
code: def is_temporal(self) -> bool:
      return self.node_time is not None or self.edge_time is not None
  
imports: import copy
  import math
  import sys
  import warnings
  from typing import Callable, Dict, List, Optional, Tuple, Union
  import torch
  from torch import Tensor
  import torch_geometric.typing
  from torch_geometric.data import Data, FeatureStore, GraphStore, HeteroData, remote_backend_utils
  from torch_geometric.data.graph_store import EdgeLayout
  from torch_geometric.sampler import BaseSampler, EdgeSamplerInput, HeteroSamplerOutput, NegativeSampling, NodeSamplerInput, SamplerOutput
  from torch_geometric.sampler.base import DataType, NumNeighbors, SubgraphType
  from torch_geometric.sampler.utils import remap_keys, to_csc, to_hetero_csc
  from torch_geometric.typing import EdgeType, NodeType, OptTensor
label_desc: Use image node_id 5 for calling the NeighborSampler obj's underlying member method code with example usage: obj.is_temporal() and returns: unknown