code: def create_hetero_minibatch():
      sampled_csc = [
          {
              relation: gb.CSCFormatBase(
                  indptr=torch.tensor([0, 1, 2, 3]),
                  indices=torch.tensor([0, 1, 1]),
              ),
              reverse_relation: gb.CSCFormatBase(
                  indptr=torch.tensor([0, 0, 0, 1, 2]),
                  indices=torch.tensor([1, 0]),
              ),
          },
          {
              relation: gb.CSCFormatBase(
                  indptr=torch.tensor([0, 1, 2]),
                  indices=torch.tensor([1, 0]),
              )
          },
      ]
      original_column_node_ids = [
          {
              "B": torch.tensor([10, 11, 12]),
              "A": torch.tensor([5, 7, 9, 11]),
          },
          {"B": torch.tensor([10, 11])},
      ]
      original_row_node_ids = [
          {
              "A": torch.tensor([5, 7, 9, 11]),
              "B": torch.tensor([10, 11, 12]),
          },
          {
              "A": torch.tensor([5, 7]),
              "B": torch.tensor([10, 11]),
          },
      ]
      original_edge_ids = [
          {
              relation: torch.tensor([19, 20, 21]),
              reverse_relation: torch.tensor([23, 26]),
          },
          {relation: torch.tensor([10, 12])},
      ]
      node_features = {
          ("A", "x"): torch.randint(0, 10, (4,)),
      }
      edge_features = [
          {(relation, "x"): torch.randint(0, 10, (3,))},
          {(relation, "x"): torch.randint(0, 10, (2,))},
      ]
      subgraphs = []
      for i in range(2):
          subgraphs.append(
              gb.SampledSubgraphImpl(
                  sampled_csc=sampled_csc[i],
                  original_column_node_ids=original_column_node_ids[i],
                  original_row_node_ids=original_row_node_ids[i],
                  original_edge_ids=original_edge_ids[i],
              )
          )
      return gb.MiniBatch(
          sampled_subgraphs=subgraphs,
          node_features=node_features,
          edge_features=edge_features,
          input_nodes={
              "A": torch.tensor([5, 7, 9, 11]),
              "B": torch.tensor([10, 11, 12]),
          },
      )
  
file_path: dgl/tests/python/pytorch/graphbolt/impl/test_minibatch.py
imports: import dgl
  import dgl.graphbolt
  import pytest
  import torch
label_desc: Use image node_id 7 for calling a global function with example usage: create_hetero_minibatch() and returns: gb