class_docstr: Wrapper for negative graph
  
  Parameters
  ----------
  neg_g : DGLGraph
      Graph holding negative edges.
  num_chunks : int
      Number of chunks in sampled graph.
  chunk_size : int
      Info of chunk_size.
  neg_sample_size : int
      Info of neg_sample_size.
  neg_head : bool
      If True, negative_mode is 'head'
      If False, negative_mode is 'tail'
class_docstr_tok: ["Wrapper","for","negative","graph","Parameters","--","--","--","--","--","neg_g",":","DGLGraph","Graph","holding","negative","edges",".","num_chunks",":","int","Number","of","chunks","in","sampled","graph",".","chunk_size",":","int","Info","of","chunk_size",".","neg_sample_size",":","int","Info","of","neg_sample_size",".","neg_head",":","bool","If","True",",","negative_mode","is","'head'","If","False",",","negative_mode","is","'tail","'"]
code: def __init__(
      self, subg, num_chunks, chunk_size, neg_sample_size, neg_head
  ):
      super(ChunkNegEdgeSubgraph, self).__init__(
          graph_data=subg.sgi.graph, readonly=True, parent=subg._parent
      )
      self.ndata[NID] = subg.sgi.induced_nodes.tousertensor()
      self.edata[EID] = subg.sgi.induced_edges.tousertensor()
      self.subg = subg
      self.num_chunks = num_chunks
      self.chunk_size = chunk_size
      self.neg_sample_size = neg_sample_size
      self.neg_head = neg_head
  
imports: import math
  import numpy
  import scipy
  import dgl.backend
  import dgl
  import os
  import sys
  import pickle
  import time
  from dgl.base import NID, EID
  import pdb
label_desc: Use image node_id 1 to create a new ChunkNegEdgeSubgraph object from inherited base classes: dgl with example: obj = ChunkNegEdgeSubgraph(subg, num_chunks, chunk_size, neg_sample_size, neg_head)