code: def jit_load(self, verbose=True):
      if not self.is_compatible(verbose):
          raise RuntimeError(
              f"Unable to JIT load the {self.name} op due to it not being compatible due to hardware/software issue. {self.error_log}"
          )
      try:
          import ninja  # noqa: F401
      except ImportError:
          raise RuntimeError(
              f"Unable to JIT load the {self.name} op due to ninja not being installed."
          )
  
      self.jit_mode = True
      from intel_extension_for_pytorch.xpu.cpp_extension import load
  
      start_build = time.time()
      # Recognize relative paths as absolute paths for jit load
  
      sources = [
          self.deepspeed_src_path(path) for path in self.sources()
      ]
      extra_include_paths = [
          self.deepspeed_src_path(path) for path in self.include_paths()
      ]
  
      # Torch will try and apply whatever CCs are in the arch list at compile time,
      # we have already set the intended targets ourselves we know that will be
      # needed at runtime. This prevents CC collisions such as multiple __half
      # implementations. Stash arch list to reset after build.
      """
          torch_arch_list = None
          if "TORCH_CUDA_ARCH_LIST" in os.environ:
              torch_arch_list = os.environ.get("TORCH_CUDA_ARCH_LIST")
              os.environ["TORCH_CUDA_ARCH_LIST"] = ""
          """
  
      op_module = load(
          name=self.name,
          sources=self.strip_empty_entries(sources),
          extra_include_paths=self.strip_empty_entries(
              extra_include_paths
          ),
          extra_cflags=self.strip_empty_entries(self.cxx_args()),
          # extra_cuda_cflags=self.strip_empty_entries(self.nvcc_args()),
          extra_ldflags=self.strip_empty_entries(self.extra_ldflags()),
          verbose=verbose,
      )
  
      build_duration = time.time() - start_build
      if verbose:
          print(
              f"Time to load {self.name} op: {build_duration} seconds"
          )
      """
          # Reset arch list so we are not silently removing it for other possible use cases
          if torch_arch_list:
              os.environ["TORCH_CUDA_ARCH_LIST"] = torch_arch_list
          """
      return op_module
  
file_path: DeepSpeed/deepspeed/ops/op_builder/xpu/builder.py
imports: import os
  import time
  import importlib
label_desc: Use image node_id 7 for calling the SYCLOpBuilder obj's underlying member method code with example usage: obj.jit_load(verbose) and returns: op_module