code: def __init__(
      self, num_nodes, emb_size, dgl_sparse_emb=False, dev_id="cpu"
  ):
      super().__init__()
      self.dev_id = dev_id
      self.emb_size = emb_size
      self.dgl_sparse_emb = dgl_sparse_emb
      if dgl_sparse_emb:
          self.sparse_emb = DistEmbedding(
              num_nodes, emb_size, name="sage", init_func=initializer
          )
      else:
          self.sparse_emb = th.nn.Embedding(
              num_nodes, emb_size, sparse=True
          )
          nn.init.uniform_(self.sparse_emb.weight, -1.0, 1.0)
  
file_path: dgl/examples/pytorch/graphsage/dist/train_dist_transductive.py
imports: import argparse
  import time
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import dgl
  from dgl.distributed import DistEmbedding
  from train_dist import DistSAGE, compute_acc
label_desc: Use image node_id 1 to create a new DistEmb object from inherited base classes: nn with example: obj = DistEmb(num_nodes, emb_size, dgl_sparse_emb, dev_id)