code: def qkv_gemm_fallback(
      self,
      input,
      weight,
      q_scale,
      bias,
      gamma,
      beta,
      eps,
      add_bias,
      q_int8,
      transpose,
  ):
      if os.environ.get("DS_KI_FALLBACK") == "True" and not transpose:
          inp_norm = F.layer_norm(
              input, (input.shape[2],), gamma, beta, eps
          )
          tmp = torch.matmul(inp_norm, weight)
          if add_bias:
              tmp += bias
          output = [tmp, inp_norm]
          return output
      else:
          raise NotImplementedError
  
file_path: DeepSpeed/deepspeed/ops/transformer/inference/op_binding/qkv_gemm.py
imports: import os
  import torch
  import torch.nn.functional
  from ..config import DeepSpeedInferenceConfig
  from .base import BaseOp
  import deepspeed
  from deepspeed.utils.types import NormType
label_desc: Use image node_id 3 for calling the QKVGemmOp obj's underlying member method code with example usage: obj.qkv_gemm_fallback(input, weight, q_scale, bias, gamma, beta, eps, add_bias, q_int8, transpose) and returns: output