class_docstr: Introspective rationale generator used in paper
      
class_docstr_tok: ["Introspective","rationale","generator","used","in","paper"]
code: def _create_label_embed_layer(self):
      embed_layer = nn.Embedding(
          self.num_labels, self.label_embedding_dim
      )
      embed_layer.weight.data.normal_(mean=0, std=0.1)
      embed_layer.weight.requires_grad = True
      return embed_layer
  
imports: import os
  import logging
  import numpy
  import torch
  import torch.nn
  from torch.autograd import Variable
  from tqdm import tqdm
  from interpret_text.experimental.common.utils_introspective_rationale import generate_data
label_desc: Use image node_id 2 for calling the IntrospectionGeneratorModule obj's underlying member method code with example usage: obj._create_label_embed_layer() and returns: embed_layer