docstr: Unless we give it an actual image and use pretrained weights, we can't expect the number of detections
  to really match the limit.
docstr_tok: ["Unless","we","give","it","an","actual","image","and","use","pretrained","weights",",","we","ca","n't","expect","the","number","of","detections","to","really","match","the","limit","."]
code: def test_smoke_n_detections(self, dtype, device):
      """Unless we give it an actual image and use pretrained weights, we can't expect the number of detections
      to really match the limit."""
      disk = DISK().to(device, dtype)
      inp = torch.ones(1, 3, 64, 64, device=device, dtype=dtype)
      output = disk(inp, n=100)
      assert isinstance(output, list)
      assert len(output) == 1
      assert all(isinstance(e, DISKFeatures) for e in output)
  
file_path: kornia/test/feature/test_disk.py
imports: import sys
  import pytest
  import torch
  import kornia.testing
  from kornia.feature.disk import DISK, DISKFeatures
  from kornia.testing import assert_close
label_desc: Use image node_id 2 for calling the TestDisk obj's underlying member method code with example usage: obj.test_smoke_n_detections(dtype, device) without return types