docstr: Forward pass
docstr_tok: ["Forward","pass"]
code: def forward(self, x, padding_mask):
      """Forward pass"""
      x, _ = self.embedding(
          tokens=x[:, 0], position=x[:, 1], age=x[:, 2], segment=x[:, 3]
      )
      x, _ = self.encoder(x)
      x = torch.einsum("bsh, bs -> bsh", x, padding_mask)
      return x
  
imports: from turtle import forward
  from ..transformer.cls_model import Transformer_CLS, Transformer_PSY
  from ..transformer.transformer import AttentionDecoder, AttentionDecoderP, CLS_Decoder_FT2, Deep_Decoder
  from ..transformer.embeddings import Embeddings
  import torch
  import torch.nn
  import logging
label_desc: Use image node_id 2 for calling the GRU_Encoder obj's underlying member method code with example usage: obj.forward(x, padding_mask) and returns: x