class_docstr: Node classification network for graphs
class_docstr_tok: ["Node","classification","network","for","graphs"]
code: def __init__(self, embedding, num_class, normalization=False):
      super(NodeClassifier, self).__init__()
      if normalization:
          embedding = embedding / np.linalg.norm(
              embedding, axis=1, keepdims=True
          )
      embedding = torch.as_tensor(embedding)
      self.embeddings = nn.Embedding.from_pretrained(
          embedding, freeze=True
      )
      self.linear = nn.Linear(embedding.size(1), num_class, bias=True)
  
file_path: graphvite/python/graphvite/application/network.py
imports: from __future__ import absolute_import
  import types
  import numpy
  import torch
  from torch import nn
label_desc: Use image node_id 1 to create a new NodeClassifier object from inherited base classes: nn with example: obj = NodeClassifier(embedding, num_class, normalization)