code: def test_tensorflow_eigvals(
      *,
      dtype_and_input,
      frontend,
      test_flags,
      fn_tree,
      on_device,
      backend_fw,
  ):
      input_dtype, x = dtype_and_input
      assume(matrix_is_stable(x[0]))
      if x[0].dtype == ivy.float32:
          x[0] = x[0].astype("float64")
          input_dtype = [ivy.float64]
      ret, frontend_ret = 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,
          tensor=x[0],
          test_values=False,
      )
  
      ret = ivy.to_numpy(ret)
      ret = ret.round(6)
      ret = np.sort(ret)
      frontend_ret = frontend_ret[0].numpy()
      frontend_ret = frontend_ret.round(6)
      frontend_ret = np.sort(frontend_ret)
  
      assert_all_close(
          ret_np=ret,
          ret_from_gt_np=frontend_ret,
          rtol=1e-06,
          atol=1e-06,
          ground_truth_backend=frontend,
          backend=backend_fw,
      )
  
imports: import numpy
  from hypothesis import assume, strategies
  import sys
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test, assert_all_close
  from ivy_tests.test_ivy.test_functional.test_core.test_linalg import _get_dtype_value1_value2_axis_for_tensordot
  from ivy_tests.test_ivy.helpers.hypothesis_helpers.general_helpers import matrix_is_stable
  from ivy_tests.test_ivy.test_functional.test_core.test_linalg import _matrix_rank_helper
label_desc: Use image node_id 15 for calling a global function with example usage: test_tensorflow_eigvals() without return types