code: def mlp_fusion_check(x, qtype, training):
      invalidInputError(x.dim() == 2, "Here input x's dim should be 2.")
      if x.shape[0] != 1:
          return False
      if x.device.type != "xpu":
          return False
      if qtype not in [
          ggml_tensor_qtype["sym_int4"],
          ggml_tensor_qtype["fp8_e5m2"],
      ]:
          return False
      if training or x.requires_grad:
          return False
      return True
  
imports: import os
  import torch
  from bigdl.llm.utils.common import invalidInputError
  from bigdl.llm.ggml.quantize import ggml_tensor_qtype
  from bigdl.llm.transformers.utils import get_ipex_version, get_xpu_device_type
label_desc: Use image node_id 17 for calling a global function with example usage: mlp_fusion_check(x, qtype, training) and returns: True, False, False, False, False