code: def tile_with_tensor_intrin(
      sch: Schedule,
      block: BlockRV,
      intrin_name: str,
      allow_padding: bool = False,
  ) -> Optional[LoopRV]:
      """Tile a subset of loops in the block according to the given tensor intrinsic.
  
      Parameters
      ----------
      sch : Schedule
          The schedule to which tiling is applied
      block : BlockRV
          The block whose subset of loops will be tiled
      intrin_name : str
          The name of a tensor intrinsic, must be registerd via TensorIntrin.register(...) beforehand
      allow_padding : bool
          Whether to allow padding when tiling
  
      Returns
      -------
      tiled_loop_rv : Optional[LoopRV]
          LoopRV corresponding to the outermost loop of a block tiled according to the given intrin
          NullOpt if no valid loop mapping is found
      """
      return _ffi_api.TileWithTensorIntrin(
          sch, block, intrin_name, allow_padding
      )
  
imports: from typing import Optional
  from tvm.tir.schedule import Schedule, BlockRV, LoopRV
  from .None import _ffi_api
label_desc: Use image node_id 1 for calling a global function with example usage: tile_with_tensor_intrin(sch, block, intrin_name, allow_padding) and returns: _ffi_api