code: def deform_inputs(x):
      _, _, h, w = x.shape
      spatial_shapes = paddle.to_tensor(
          [(h // 8, w // 8), (h // 16, w // 16), (h // 32, w // 32)],
          dtype="int64",
      )
      level_start_index = paddle.concat(
          (
              paddle.zeros((1,), dtype="int64"),
              spatial_shapes.prod(1).cumsum(0)[:-1],
          )
      )
      reference_points = get_reference_points([(h // 16, w // 16)])
      deform_inputs1 = [
          reference_points,
          spatial_shapes,
          level_start_index,
      ]
  
      spatial_shapes = paddle.to_tensor(
          [(h // 16, w // 16)], dtype="int64"
      )
      level_start_index = paddle.concat(
          (
              paddle.zeros((1,), dtype="int64"),
              spatial_shapes.prod(1).cumsum(0)[:-1],
          )
      )
      reference_points = get_reference_points(
          [(h // 8, w // 8), (h // 16, w // 16), (h // 32, w // 32)]
      )
      deform_inputs2 = [
          reference_points,
          spatial_shapes,
          level_start_index,
      ]
  
      return deform_inputs1, deform_inputs2
  
imports: import math
  import warnings
  from functools import partial
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.models.backbones.transformer_utils import DropPath
  from paddleseg.models.layers.ms_deformable_attention import MSDeformAttn
label_desc: Use image node_id 2 for calling a global function with example usage: deform_inputs(x) and returns: deform_inputs1,  deform_inputs2