code: def forward(
      ctx,
      decoder_states,
      encoder_out,
      encoder_padding_mask,
      config,
      cache,
  ):
      cuda_module = cuda_layer_module
      forward_func = (
          cuda_module.transformer_decoder_layer_fw_fp16
          if config.fp16
          else cuda_module.transformer_decoder_layer_fw_fp32
      )
  
      (output,) = forward_func(
          config.layer_id,
          decoder_states,
          encoder_out,
          encoder_padding_mask,
          config.pre_layer_norm,
          config.quant_mode,
          cache,
          0,
      )
  
      return output
  
imports: import __init__
  from itertools import zip_longest
  import copy
  import torch
  from torch import nn
  import math
  from dataclasses import dataclass
  from csrc.pytorch.layer_base import TransformerDecoderLayerBase
  from csrc.pytorch.util import copy_para, state_dict, calc_offset
  from csrc.pytorch.torch_transformer_layers import act_quant_config, weight_quant_config
  from csrc.pytorch.builder.cuda_layer_builder import CudaLayerBuilder
label_desc: Use image node_id 1 for calling the LSTransformerDecoderFunc obj's underlying member method code with example usage: obj.forward(ctx, decoder_states, encoder_out, encoder_padding_mask, config, cache) and returns: output