code: def test_gradcheck(self, device, dtype):
      batch_size, channels, height, width = 1, 1, 16, 16
      patches = torch.rand(
          batch_size,
          channels,
          height,
          width,
          device=device,
          dtype=dtype,
      )
      patches = utils.tensor_to_gradcheck_var(patches)  # to var
      assert gradcheck(
          DenseSIFTDescriptor(4, 2, 2),
          (patches),
          raise_exception=True,
          nondet_tol=1e-4,
          fast_mode=True,
      )
  
imports: import pytest
  import torch
  from torch.autograd import gradcheck
  import kornia.testing
  from kornia.feature.siftdesc import DenseSIFTDescriptor, SIFTDescriptor, get_sift_bin_ksize_stride_pad, get_sift_pooling_kernel
  from kornia.testing import assert_close
label_desc: Use image node_id 5 for calling the TestDenseSIFTDescriptor obj's underlying member method code with example usage: obj.test_gradcheck(device, dtype) without return types