code: def verify_non_max_suppression(
      target,
      dev,
      np_data,
      np_valid_count,
      np_indices,
      np_result,
      np_indices_result,
      max_output_size,
      iou_threshold,
      force_suppress,
      top_k,
      coord_start,
      score_index,
      id_index,
  ):
      dshape = np_data.shape
      batch, num_anchors, _ = dshape
      indices_dshape = (batch, num_anchors)
      data = te.placeholder(dshape, name="data")
      valid_count = te.placeholder(
          (batch,), dtype="int32", name="valid_count"
      )
      indices = te.placeholder(
          (batch, num_anchors), dtype="int32", name="indices"
      )
  
      with tvm.target.Target(target):
          fcompute, fschedule = tvm.topi.testing.dispatch(
              target, _nms_implement
          )
          out = fcompute(
              data,
              valid_count,
              indices,
              max_output_size,
              iou_threshold,
              force_suppress,
              top_k,
              coord_start=coord_start,
              score_index=score_index,
              id_index=id_index,
              return_indices=False,
          )
          indices_out = fcompute(
              data,
              valid_count,
              indices,
              max_output_size,
              iou_threshold,
              force_suppress,
              top_k,
              coord_start=coord_start,
              score_index=score_index,
              id_index=id_index,
              return_indices=True,
          )
          s = fschedule(out)
          indices_s = fschedule(indices_out)
  
      tvm_data = tvm.nd.array(np_data, dev)
      tvm_valid_count = tvm.nd.array(np_valid_count, dev)
      tvm_indices = tvm.nd.array(np_indices, dev)
  
      tvm_out = tvm.nd.array(np.zeros(dshape, dtype=data.dtype), dev)
      f = tvm.build(s, [data, valid_count, indices, out], target)
      f(tvm_data, tvm_valid_count, tvm_indices, tvm_out)
      tvm.testing.assert_allclose(tvm_out.numpy(), np_result, rtol=1e-4)
  
      tvm_indices_out = tvm.nd.array(
          np.zeros(indices_dshape, dtype="int32"), dev
      )
      f = tvm.build(
          indices_s,
          [data, valid_count, indices, indices_out[0]],
          target,
      )
      f(tvm_data, tvm_valid_count, tvm_indices, tvm_indices_out)
      tvm.testing.assert_allclose(
          tvm_indices_out.numpy(), np_indices_result, rtol=1e-4
      )
  
imports: import math
  import sys
  import numpy
  import pytest
  import tvm
  import tvm.testing
  import tvm.topi.testing
  from tvm import te, topi
  from tvm.topi.vision import ssd, non_max_suppression, get_valid_counts
label_desc: Use image node_id 1 for calling a global function with example usage: verify_non_max_suppression(target, dev, np_data, np_valid_count, np_indices, np_result, np_indices_result, max_output_size, iou_threshold, force_suppress, top_k, coord_start, score_index, id_index) without return types