code: def _create_edge_frame(
      src_t: torch.Tensor, dst_t: torch.Tensor, single_gpu: bool
  ):
      """
      Create a edge dataframe from src_t and dst_t
      """
      src_ar = create_ar_from_tensor(src_t)
      dst_ar = create_ar_from_tensor(dst_t)
      edge_df = _create_df_from_edge_ar(
          src_ar, dst_ar, single_gpu=single_gpu
      )
      edge_df = edge_df.rename(
          columns={edge_df.columns[0]: src_n, edge_df.columns[1]: dst_n}
      )
      return edge_df
  
file_path: cugraph/python/cugraph-dgl/cugraph_dgl/utils/cugraph_conversion_utils.py
imports: from __future__ import annotations
  from typing import Dict, Tuple, Union
  import cudf
  import pandas
  import dask.dataframe
  import dask_cudf
  from dask.distributed import get_client
  import cupy
  from cugraph.utilities.utils import import_optional
  from cugraph.gnn.dgl_extensions.dgl_uniform_sampler import src_n, dst_n
label_desc: Use image node_id 3 for calling a global function with example usage: _create_edge_frame(src_t, dst_t, single_gpu) and returns: edge_df