class_docstr: Gradient Based Task Scheduler
docstr: Constructor.
  
  Parameters
  ----------
  alpha : float = 0.2
      The parameter alpha in gradient computation.
  window_size : int = 3
      The parameter to control backward window size in gradient computation.
  seed : int = -1
      The random seed.
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code: def __init__(
      self,
      *,
      alpha: float = 0.2,
      window_size: int = 3,
      seed: int = -1,
  ) -> None:
      """Constructor.
  
      Parameters
      ----------
      alpha : float = 0.2
          The parameter alpha in gradient computation.
      window_size : int = 3
          The parameter to control backward window size in gradient computation.
      seed : int = -1
          The random seed.
      """
      self.__init_handle_by_constructor__(
          _ffi_api.TaskSchedulerGradientBased,  # type: ignore # pylint: disable=no-member
          get_logging_func(logger),
          alpha,
          window_size,
          seed,
      )
  
imports: from tvm._ffi import register_object
  from ..None import _ffi_api
  from ..logging import get_logger, get_logging_func
  from .task_scheduler import TaskScheduler
label_desc: Use image node_id 1 to create a new GradientBased object from inherited base classes: TaskScheduler with example: obj = GradientBased()