code: def backprop_clipped_linear(
      self,
      dY,
      X,
      slope: float = 1.0,
      offset: float = 0.0,
      min_val: float = 0.0,
      max_val: float = 1.0,
      inplace: bool = False,
  ):
      if X.dtype == dY.dtype and X.dtype in ("float32", "float64"):
          return _custom_kernels.backprop_clipped_linear(
              dY,
              X,
              slope=slope,
              offset=offset,
              min_val=min_val,
              max_val=max_val,
              inplace=inplace,
          )
      else:
          return super().backprop_clipped_linear(
              dY=dY,
              X=X,
              slope=slope,
              offset=offset,
              min_val=min_val,
              max_val=max_val,
              inplace=inplace,
          )
  
imports: import numpy
  from ..None import registry
  from ..compat import cupy, cupyx
  from ..types import DeviceTypes
  from ..util import is_cupy_array, is_mxnet_gpu_array, is_tensorflow_gpu_array, is_torch_cuda_array, mxnet2xp, tensorflow2xp, torch2xp
  from .None import _custom_kernels
  from .numpy_ops import NumpyOps
  from .ops import Ops
label_desc: Use image node_id 16 for calling the CupyOps obj's underlying member method code with example usage: obj.backprop_clipped_linear(dY, X, slope, offset, min_val, max_val, inplace) and returns: _custom_kernels, super