code: def __init__(self, config):
      super().__init__()
  
      MAX_DEC_LENGTH = 100
      MAX_TYPE_NUM = 5
      hidden_size = config.hidden_size
      ln_eps = config.layer_norm_eps
  
      self.position_embeddings = nn.Embedding(
          MAX_DEC_LENGTH, hidden_size
      )
      self.token_type_embeddings = nn.Embedding(
          MAX_TYPE_NUM, hidden_size
      )
  
      self.ans_layer_norm = nn.LayerNorm(hidden_size, eps=ln_eps)
      self.ocr_layer_norm = nn.LayerNorm(hidden_size, eps=ln_eps)
      self.emb_layer_norm = nn.LayerNorm(hidden_size, eps=ln_eps)
      self.emb_dropout = nn.Dropout(config.hidden_dropout_prob)
  
imports: import functools
  import logging
  import math
  import torch
  import torch.nn.functional
  from mmf.common.registry import registry
  from mmf.models.base_model import BaseModel
  from mmf.modules.layers import ClassifierLayer
  from mmf.utils.build import build_image_encoder
  from omegaconf import OmegaConf
  from torch import nn
label_desc: Use image node_id 1 to create a new PrevPredEmbeddings object from inherited base classes: nn with example: obj = PrevPredEmbeddings(config)