class_docstr: Latent depth (https://arxiv.org/abs/2009.13102) implemented in
  TransformerEncoder.
class_docstr_tok: ["Latent","depth","(","https",":","\/\/arxiv.org\/abs\/2009.13102",")","implemented","in","TransformerEncoder","."]
code: def forward(
      self, src_tokens, src_lengths, return_all_hiddens: bool = False
  ):
      self.layer_select.sample(self.lang_idx)
      return super().forward(
          src_tokens, src_lengths, return_all_hiddens
      )
  
imports: from typing import Any, Dict, Optional
  import torch.nn
  from fairseq.models.fairseq_encoder import EncoderOut
  from fairseq.models.transformer import TransformerDecoder, TransformerEncoder
  from fairseq.modules import TransformerDecoderLayer, TransformerEncoderLayer
  from torch import Tensor
  from ..modules.latent_layers import LayerSelect
label_desc: Use image node_id 4 for calling the LatentTransformerEncoder obj's underlying member method code with example usage: obj.forward(src_tokens, src_lengths, return_all_hiddens) and returns: super