code: def test_torch_matrix_norm(
      *,
      dtype_values_axis,
      ord,
      keepdim,
      dtype,
      frontend,
      test_flags,
      fn_tree,
      backend_fw,
      on_device,
  ):
      input_dtype, x, axis = dtype_values_axis
  
      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,
          rtol=1e-03,
          atol=1e-03,
          input=x[0],
          ord=ord,
          dim=axis,
          keepdim=keepdim,
          dtype=dtype[0],
      )
  
imports: import math
  import sys
  import numpy
  from hypothesis import strategies, assume
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import assert_all_close
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  from ivy_tests.test_ivy.test_frontends.test_torch.test_miscellaneous_ops import dtype_value1_value2_axis
  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 22 for calling a global function with example usage: test_torch_matrix_norm() without return types