class_docstr: The class that can represent a batch of edges.
  
  Parameters
  ----------
  graph : DGLGraph
      Graph object.
  eid : Tensor
      Edge IDs.
  etype : (str, str, str)
      Edge type.
  src_data : dict[str, Tensor]
      Src node features.
  edge_data : dict[str, Tensor]
      Edge features.
  dst_data : dict[str, Tensor]
      Dst node features.
class_docstr_tok: ["The","class","that","can","represent","a","batch","of","edges",".","Parameters","--","--","--","--","--","graph",":","DGLGraph","Graph","object",".","eid",":","Tensor","Edge","IDs",".","etype",":","(","str",",","str",",","str",")","Edge","type",".","src_data",":","dict","[","str",",","Tensor","]","Src","node","features",".","edge_data",":","dict","[","str",",","Tensor","]","Edge","features",".","dst_data",":","dict","[","str",",","Tensor","]","Dst","node","features","."]
code: def __init__(self, graph, eid, etype, src_data, edge_data, dst_data):
      self._graph = graph
      self._eid = eid
      self._etype = etype
      self._src_data = src_data
      self._edge_data = edge_data
      self._dst_data = dst_data
  
file_path: dgl/python/dgl/udf.py
imports: from __future__ import absolute_import
label_desc: Use image node_id 1 to create a new EdgeBatch object from inherited base classes: object with example: obj = EdgeBatch(graph, eid, etype, src_data, edge_data, dst_data)