class_docstr: <a id="EncoderDecoder"></a>
  
  ## Combined Encoder-Decoder
code: def forward(
      self,
      src: torch.Tensor,
      tgt: torch.Tensor,
      src_mask: torch.Tensor,
      tgt_mask: torch.Tensor,
  ):
      # Run the source through encoder
      enc = self.encode(src, src_mask)
      # Run encodings and targets through decoder
      return self.decode(enc, src_mask, tgt, tgt_mask)
  
imports: import math
  import torch
  import torch.nn
  from labml_nn.utils import clone_module_list
  from .feed_forward import FeedForward
  from .mha import MultiHeadAttention
  from .positional_encoding import get_positional_encoding
label_desc: Use image node_id 2 for calling the EncoderDecoder obj's underlying member method code with example usage: obj.forward(src, tgt, src_mask, tgt_mask) and returns: self