code: def build(sch, inputs, outputs, name="hybrid_func"):
      """Dump the current schedule to hybrid module
  
      Parameters
      ----------
      sch: tvm.te.Schedule
          The schedule to be dumped
  
      inputs: An array of Tensors or Vars
          The inputs of the function body
  
      outputs: An array of Tensors
          The outputs of the function body
  
      Returns
      -------
      module: HybridModule
          The built results is wrapped in a HybridModule.
          The usage of HybridModule is roughly the same as normal TVM-built modules.
      """
      sch = sch.normalize()
      bounds = tvm.te.schedule.InferBound(sch)
      stmt = tvm.te.schedule.ScheduleOps(sch, bounds)
  
      src = _Dump(stmt, inputs, outputs, name)
  
      return HybridModule(src, name)
  
file_path: tvm/python/tvm/te/hybrid/__init__.py
imports: import inspect
  import tvm._ffi
  import tvm.te.schedule
  from tvm._ffi.base import decorate
  from .module import HybridModule
  from .parser import source_to_op
  from .utils import _pruned_source
label_desc: Use image node_id 2 for calling a global function with example usage: build(sch, inputs, outputs, name) and returns: HybridModule