code: def create_homo_minibatch():
      csc_formats = [
          gb.CSCFormatBase(
              indptr=torch.tensor([0, 1, 3, 5, 6]),
              indices=torch.tensor([0, 1, 2, 2, 1, 2]),
          ),
          gb.CSCFormatBase(
              indptr=torch.tensor([0, 2, 3]),
              indices=torch.tensor([1, 2, 0]),
          ),
      ]
      original_column_node_ids = [
          torch.tensor([10, 11, 12, 13]),
          torch.tensor([10, 11]),
      ]
      original_row_node_ids = [
          torch.tensor([10, 11, 12, 13]),
          torch.tensor([10, 11, 12]),
      ]
      original_edge_ids = [
          torch.tensor([19, 20, 21, 22, 25, 30]),
          torch.tensor([10, 15, 17]),
      ]
      node_features = {"x": torch.randint(0, 10, (4,))}
      edge_features = [
          {"x": torch.randint(0, 10, (6,))},
          {"x": torch.randint(0, 10, (3,))},
      ]
      subgraphs = []
      for i in range(2):
          subgraphs.append(
              gb.SampledSubgraphImpl(
                  sampled_csc=csc_formats[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=torch.tensor([10, 11, 12, 13]),
      )
  
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 6 for calling a global function with example usage: create_homo_minibatch() and returns: gb