code: def test_topk(executor_kind):
      def verify_topk(
          k, axis, ret_type, is_ascend, dtype, in_dtype="float32"
      ):
          shape = (20, 100)
          x = relay.var("x", relay.TensorType(shape, in_dtype))
          out = relay.topk(x, k, axis, ret_type, is_ascend, dtype)
          if isinstance(out, relay.expr.TupleWrapper):
              out = out.astuple()
          func = relay.Function([x], out)
          np_data = np.random.uniform(size=shape).astype(in_dtype)
          if is_ascend:
              np_indices = np.argsort(np_data, axis=axis, kind="stable")
          else:
              np_indices = np.argsort(
                  -np_data, axis=axis, kind="stable"
              )
          kk = k if k >= 1 else shape[axis]
          if axis == 0:
              np_indices = np_indices[:kk, :]
              np_values = np.zeros(np_indices.shape).astype(in_dtype)
              for i in range(shape[1]):
                  np_values[:, i] = np_data[np_indices[:, i], i]
          else:
              np_indices = np_indices[:, :kk]
              np_values = np.zeros(np_indices.shape).astype(in_dtype)
              for i in range(shape[0]):
                  np_values[i, :] = np_data[i, np_indices[i, :]]
          np_indices = np_indices.astype(dtype)
  
          for target, dev in tvm.testing.enabled_targets():
              op_res = relay.create_executor(
                  executor_kind, device=dev, target=target
              ).evaluate(func)(np_data)
              if ret_type == "both":
                  tvm.testing.assert_allclose(
                      op_res[0].numpy(), np_values
                  )
                  tvm.testing.assert_allclose(
                      op_res[1].numpy(), np_indices
                  )
              elif ret_type == "values":
                  tvm.testing.assert_allclose(op_res.numpy(), np_values)
              else:
                  tvm.testing.assert_allclose(
                      op_res.numpy(), np_indices
                  )
  
      np.random.seed(0)
      for k in [0, 1, 5]:
          for axis in [0, -1, 1]:
              for ret_type in ["both", "values", "indices"]:
                  verify_topk(k, axis, ret_type, True, "int64")
                  verify_topk(k, axis, ret_type, False, "float32")
                  verify_topk(
                      k, axis, ret_type, False, "int64", "float16"
                  )
  
file_path: tvm/tests/python/relay/test_op_level6.py
imports: import pytest
  import numpy
  import tvm
  from tvm import relay
  from tvm.topi.testing import searchsorted_ref
  import tvm.testing
label_desc: Use image node_id 3 for calling a global function with example usage: test_topk(executor_kind) without return types