code: def _init_loss_weights(self):
      n_features = self.hparams.continuous_dim + len(
          self.hparams.embedding_dims
      )
      return [
          len(self.embedding_layer._binary_feat_idx) / n_features,
          len(self.embedding_layer._onehot_feat_idx) / n_features,
          self.hparams.continuous_dim
          + len(self.embedding_layer._embedding_feat_idx) / n_features,
          self.hparams.mask_loss_weight,
      ]
  
imports: from collections import namedtuple
  from typing import Dict
  import torch
  import torch.nn
  from omegaconf import DictConfig
  from ..base_model import SSLBaseModel
  from ..common.heads import MultiTaskHead
  from ..common.layers import MixedEmbedding1dLayer
  from ..common.noise_generators import SwapNoiseCorrupter
label_desc: Use image node_id 7 for calling the DenoisingAutoEncoderModel obj's underlying member method code with example usage: obj._init_loss_weights() and returns: list