code: def forward(self, input, residual, residual_norm, bias):
      return DeepSpeedMLPFunction.apply(
          input,
          residual,
          residual_norm,
          bias,
          self.inter_w,
          self.inter_b,
          self.attn_nw,
          self.attn_nb,
          self.config,
          self.mp_group,
          self.output_b,
          self.output_w,
          self.q_scales,
          self.q_groups,
          self.merge_count,
          self.mlp_gemm_func,
          self.fused_gemm_gelu,
          self.vector_matmul_func,
          self.bias_residual_func,
          self.residual_add_func,
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/DeepSpeed/deepspeed/ops/transformer/inference/ds_mlp.py
imports: import torch
  from torch.autograd import Function
  from deepspeed.utils.types import ActivationFuncType
  from deepspeed import comm
  import torch.nn
  import math
  from ...None import op_builder
label_desc: Use image node_id 2 for calling the DeepSpeedMLP obj's underlying member method code with example usage: obj.forward(input, residual, residual_norm, bias) and returns: DeepSpeedMLPFunction