class_docstr: Represent a single graph with additional attributes.
class_docstr_tok: ["Represent","a","single","graph","with","additional","attributes","."]
docstr: An edge version of :py:method `batch_node_features`.
  
  Returns
  -------
  dict or torch.Tensor
      A dictionary containing the edge feature names and the corresponding batch-view tensors.
code: def _get_batch_edge_features(
      self, item: str = None
  ) -> Union[Dict[str, torch.Tensor], torch.Tensor]:
      """
      An edge version of :py:method `batch_node_features`.
  
      Returns
      -------
      dict or torch.Tensor
          A dictionary containing the edge feature names and the corresponding batch-view tensors.
      """
      if not self._is_batch:
          raise Exception(
              "Calling batch_edge_features() method on a non-batch graph."
          )
      if item is None:
          batch_edge_features = dict()
          for k, v in self.split_edge_features.items():
              batch_edge_features[k] = pad_sequence(
                  list(v), batch_first=True
              )
          return batch_edge_features
      else:
          if (item not in self.edge_features.keys()) or (
              self.edge_features[item] is None
          ):
              raise Exception(
                  "Edge feature {} doesn't exist!".format(item)
              )
          return pad_sequence(
              self.split_edge_features[item], batch_first=True
          )
  
imports: import os
  import warnings
  from collections import namedtuple
  from typing import Any, Callable, Dict, List, Tuple, Union
  import dgl
  import scipy.sparse
  import torch
  from torch.nn.utils.rnn import pad_sequence
  from .utils import EdgeNotFoundException, SizeMismatchException, check_and_expand, entail_zero_padding, int_to_list, slice_to_list
  from .views import BatchEdgeFeatView, BatchNodeFeatView, EdgeView, NodeFeatView, NodeView
label_desc: Use image node_id 36 for calling the GraphData obj's underlying member method code with example usage: obj._get_batch_edge_features(item) and returns: batch_edge_features, pad_sequence