code: def test_tensorflow_dct(
      *,
      dtype_and_x,
      n,
      norm,
      type,
      frontend,
      test_flags,
      fn_tree,
      backend_fw,
      on_device,
  ):
      (
          input_dtype,
          x,
      ) = dtype_and_x
      if norm == "ortho" and type == 1:
          norm = None
      axis = -1
      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],
          type=type,
          n=n,
          axis=axis,
          norm=norm,
          # atol=1e-01,
      )
  
file_path: ivy/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_signal.py
imports: from hypothesis import strategies
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
label_desc: Use image node_id 3 for calling a global function with example usage: test_tensorflow_dct() without return types