class_docstr: Prompt embeddings
  
  Arugments:
      init_from_prompt_text: Whether to intialize prompt embeddings
                             from from certain lm embeddings
                             corresponding to a prompt string
      hidden_size: hidden size should match lm embedding size
      total_virtual_tokens: length of prompt initalized from torch init method
docstr: Does forward pass
docstr_tok: ["Does","forward","pass"]
code: def forward(
      self,
  ):
      """
      Does forward pass
      """
      return self.prompt_embeddings(self.indices)
  
imports: import copy
  import enum
  from typing import Dict, Optional
  import torch
  import torch.nn.init
  from torch import nn
  from nemo.collections.nlp.modules.common.megatron.fused_bias_gelu import fused_bias_gelu
  from nemo.collections.nlp.modules.common.megatron.utils import ApexGuardDefaults, init_method_normal
  from nemo.core.classes import Exportable, NeuralModule
  from nemo.core.classes.common import typecheck
label_desc: Use image node_id 4 for calling the PromptEmbedding obj's underlying member method code with example usage: obj.forward() and returns: self