code: def test_torch_var_mean(
      *,
      dtype_and_x,
      keepdims,
      on_device,
      fn_tree,
      frontend,
      test_flags,
      backend_fw,
  ):
      input_dtype, x, axis, correction = dtype_and_x
      helpers.test_frontend_function(
          input_dtypes=input_dtype,
          backend_to_test=backend_fw,
          frontend=frontend,
          test_flags=test_flags,
          fn_tree=fn_tree,
          on_device=on_device,
          input=x[0],
          dim=axis,
          unbiased=bool(correction),
          keepdim=keepdims,
      )
  
imports: from hypothesis import strategies
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  from ivy_tests.test_ivy.test_functional.test_core.test_statistical import _statistical_dtype_values, _get_castable_dtype
  from ivy_tests.test_ivy.test_functional.test_experimental.test_core.test_statistical import _quantile_helper
label_desc: Use image node_id 29 for calling a global function with example usage: test_torch_var_mean() without return types