docstr: Parameters
  ----------
  x
      - layout = 'NT'
          Shape (batch_size, seq_length, C_in)
      - layout = 'TN'
          Shape (seq_length, batch_size, C_in)
  
  layer_states
      - layout = 'NT'
          Shape (2, batch_size, prev_len, C_in)
      - layout = 'TN'
          Shape (2, prev_len, batch_size, C_in)
  
  Returns
  -------
  new_x
      - layout = 'NT'
          Shape (batch_size, seq_length, C_out)
      - layout = 'TN'
          Shape (seq_length, batch_size, C_out)
  
  new_states
      - layout = 'NT'
          Shape (2, batch_size, prev_len + seq_length, C_in)
      - layout = 'TN'
          Shape (2, prev_len + seq_length, batch_size, C_in)
docstr_tok: ["Parameters","--","--","--","--","--","x","-","layout","=","'NT'","Shape","(","batch_size",",","seq_length",",","C_in",")","-","layout","=","'TN'","Shape","(","seq_length",",","batch_size",",","C_in",")","layer_states","-","layout","=","'NT'","Shape","(","2",",","batch_size",",","prev_len",",","C_in",")","-","layout","=","'TN'","Shape","(","2",",","prev_len",",","batch_size",",","C_in",")","Returns","--","--","--","-","new_x","-","layout","=","'NT'","Shape","(","batch_size",",","seq_length",",","C_out",")","-","layout","=","'TN'","Shape","(","seq_length",",","batch_size",",","C_out",")","new_states","-","layout","=","'NT'","Shape","(","2",",","batch_size",",","prev_len","+","seq_length",",","C_in",")","-","layout","=","'TN'","Shape","(","2",",","prev_len","+","seq_length",",","batch_size",",","C_in",")"]
code: def forward(self, x, layer_states):
      """
  
      Parameters
      ----------
      x
          - layout = 'NT'
              Shape (batch_size, seq_length, C_in)
          - layout = 'TN'
              Shape (seq_length, batch_size, C_in)
  
      layer_states
          - layout = 'NT'
              Shape (2, batch_size, prev_len, C_in)
          - layout = 'TN'
              Shape (2, prev_len, batch_size, C_in)
  
      Returns
      -------
      new_x
          - layout = 'NT'
              Shape (batch_size, seq_length, C_out)
          - layout = 'TN'
              Shape (seq_length, batch_size, C_out)
  
      new_states
          - layout = 'NT'
              Shape (2, batch_size, prev_len + seq_length, C_in)
          - layout = 'TN'
              Shape (2, prev_len + seq_length, batch_size, C_in)
      """
      h, new_layer_states = self.atten(x, layer_states)
      x = x + h
      h = self.ffn(x)
      return h, new_layer_states
  
imports: import os
  from typing import Tuple
  import mxnet
  from mxnet import use_np, np, npx
  from mxnet.gluon import HybridBlock, nn
  from .base import BACKBONE_REGISTRY
  from ..base import get_model_zoo_home_dir, get_repo_model_zoo_url, get_model_zoo_checksum_dir
  from ..utils.config import CfgNode
  from ..utils.misc import load_checksum_stats, download
  from ..utils.registry import Registry
  from ..initializer import TruncNorm
  from ..attention_cell import MultiHeadAttentionCell
  from ..layers import get_activation, PositionalEmbedding
  from ..data.tokenizers import HuggingFaceByteBPETokenizer
label_desc: Use image node_id 2 for calling the GPT2Layer obj's underlying member method code with example usage: obj.forward(x, layer_states) and returns: h,  new_layer_states