code: def test_mean_var_std(executor_kind):
      for func in [
          [relay.mean_variance, np.var],
          [relay.mean_std, np.std],
      ]:
          verify_mean_var_std(executor_kind, func, (2, 3, 4), 1, True)
          verify_mean_var_std(
              executor_kind, func, (2, 3, 4), (1,), True
          )
          verify_mean_var_std(executor_kind, func, (2, 3, 4), -1, True)
          verify_mean_var_std(
              executor_kind, func, (2, 3, 4), (0, 1, 2), False
          )
          verify_mean_var_std(
              executor_kind, func, (4, 4, 3), None, False
          )
          verify_mean_var_std(
              executor_kind, func, (4, 4, 3), (0, 2), False
          )
          verify_mean_var_std(
              executor_kind, func, (128, 24, 128), (0, 1), False
          )
          verify_mean_var_std(
              executor_kind, func, (128, 24, 128), (0, 2), False
          )
          verify_mean_var_std(
              executor_kind, func, (128, 24, 128), (0, 1), True
          )
          verify_mean_var_std(
              executor_kind, func, (128, 24, 128), (0, 2), True
          )
          # Test FP16 reduction with large indices.
          verify_mean_var_std(
              executor_kind,
              func,
              (128, 24, 128),
              (0, 2),
              True,
              "float16",
          )
          verify_mean_var_std(
              executor_kind,
              func,
              (128, 24, 128),
              None,
              False,
              "float16",
          )
  
imports: import sys
  import numpy
  import numpy.random
  import pytest
  import tvm
  import tvm.testing
  import tvm.topi.testing
  from tvm import relay, te
  from tvm.relay import transform
  from tvm.relay.testing import run_infer_type
label_desc: Use image node_id 13 for calling a global function with example usage: test_mean_var_std(executor_kind) without return types