code: def vector_matmul_fallback(
      self, input, weight, async_op, q_scale, q_int8, transpose
  ):
      if os.environ.get("DS_KI_FALLBACK") == "True" and not transpose:
          return torch.matmul(input, weight)
      else:
          raise NotImplementedError
  
file_path: DeepSpeed/deepspeed/ops/transformer/inference/op_binding/vector_matmul.py
imports: import os
  import torch
  from ..config import DeepSpeedInferenceConfig
  from .base import BaseOp
  import deepspeed
label_desc: Use image node_id 2 for calling the VectorMatMulOp obj's underlying member method code with example usage: obj.vector_matmul_fallback(input, weight, async_op, q_scale, q_int8, transpose) and returns: torch