code: def onednn_fusion_enabled():
      """Return whether onednn JIT fusion is enabled."""
      return torch._C._jit_llga_enabled()
  
imports: import warnings
  from contextlib import contextmanager
  from typing import Any, Iterator
  import torch._C
  from torch._jit_internal import _Await, _drop, _IgnoreContextManager, _isinstance, _overload, _overload_method, export, Final, Future, ignore, is_scripting, unused
  from torch.jit._async import fork, wait
  from torch.jit._await import _awaitable, _awaitable_nowait, _awaitable_wait
  from torch.jit._decomposition_utils import _register_decomposition
  from torch.jit._freeze import freeze, optimize_for_inference, run_frozen_optimizations
  from torch.jit._fuser import fuser, last_executed_optimized_graph, optimized_execution, set_fusion_strategy
  from torch.jit._ir_utils import _InsertPoint
  from torch.jit._script import _ScriptProfile, _unwrap_optional, Attribute, CompilationUnit, interface, RecursiveScriptClass, RecursiveScriptModule, script, script_method, ScriptFunction, ScriptModule, ScriptWarning
  from torch.jit._serialization import jit_module_from_flatbuffer, load, save, save_jit_module_to_flatbuffer
  from torch.jit._trace import _flatten, _get_trace_graph, _script_if_tracing, _unique_state_dict, is_tracing, ONNXTracedModule, TopLevelTracedModule, trace, trace_module, TracedModule, TracerWarning, TracingCheckError
  from torch.utils import set_module
label_desc: Use image node_id 7 for calling a global function with example usage: onednn_fusion_enabled() and returns: torch