code: def _build_embedding_layer(self):
      return Embedding2dLayer(
          continuous_dim=0,  # Only passing and embedding categorical features
          categorical_cardinality=self.hparams.categorical_cardinality,
          embedding_dim=self.hparams.input_embed_dim,
          shared_embedding_strategy=self.hparams.share_embedding_strategy,
          frac_shared_embed=self.hparams.shared_embedding_fraction,
          embedding_bias=self.hparams.embedding_bias,
          embedding_dropout=self.hparams.embedding_dropout,
          initialization=self.hparams.embedding_initialization,
          virtual_batch_size=self.hparams.virtual_batch_size,
      )
  
imports: from collections import OrderedDict
  from typing import Dict
  import torch
  import torch.nn
  from einops import rearrange
  from omegaconf import DictConfig
  from pytorch_tabular.models.common.layers.batch_norm import BatchNorm1d
  from ..base_model import BaseModel
  from ..common.layers import Embedding2dLayer, TransformerEncoderBlock
label_desc: Use image node_id 3 for calling the TabTransformerBackbone obj's underlying member method code with example usage: obj._build_embedding_layer() and returns: Embedding2dLayer