code: def set_jit_fusion_options():
      """Set PyTorch JIT layer fusion options."""
      # LSG: the latest pytorch and CUDA versions may not support
      # the following jit settings
      global JIT_OPTIONS_SET
      if JIT_OPTIONS_SET == False:
          # flags required to enable jit fusion kernels
          TORCH_MAJOR = int(torch.__version__.split(".")[0])
          TORCH_MINOR = int(torch.__version__.split(".")[1])
          if (TORCH_MAJOR > 1) or (
              TORCH_MAJOR == 1 and TORCH_MINOR >= 10
          ):
              # nvfuser
              torch._C._jit_set_profiling_executor(True)
              torch._C._jit_set_profiling_mode(True)
              torch._C._jit_override_can_fuse_on_cpu(False)
              torch._C._jit_override_can_fuse_on_gpu(False)
              torch._C._jit_set_texpr_fuser_enabled(False)
              torch._C._jit_set_nvfuser_enabled(True)
              torch._C._debug_set_autodiff_subgraph_inlining(False)
          else:
              # legacy pytorch fuser
              torch._C._jit_set_profiling_mode(False)
              torch._C._jit_set_profiling_executor(False)
              torch._C._jit_override_can_fuse_on_cpu(True)
              torch._C._jit_override_can_fuse_on_gpu(True)
  
          JIT_OPTIONS_SET = True
  
imports: import torch
  from colossalai.legacy.nn.layer.colossalai_layer import Embedding, Linear
  from colossalai.utils import get_current_device
  from .bias_dropout_add import bias_dropout_add_fused_train
  from .bias_gelu import bias_gelu_impl
label_desc: Use image node_id 1 for calling a global function with example usage: set_jit_fusion_options() without return types