code: def test_tensorflow_resize(
      dtype_x_mode,
      antialias,
      frontend,
      test_flags,
      fn_tree,
      backend_fw,
      on_device,
  ):
      input_dtype, x, mode, size, _, _, preserve = dtype_x_mode
      try:
          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-01,
              atol=1e-01,
              image=x[0],
              size=size,
              method=mode,
              antialias=antialias,
              preserve_aspect_ratio=preserve,
          )
      except Exception as e:
          if hasattr(e, "message") and (
              "output dimensions must be positive" in e.message
              or "Input and output sizes should be greater than 0"
              in e.message
          ):
              assume(False)
          raise e
  
imports: from hypothesis import strategies, assume
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
  from ivy_tests.test_ivy.test_functional.test_experimental.test_nn.test_layers import _interp_args
label_desc: Use image node_id 3 for calling a global function with example usage: test_tensorflow_resize(dtype_x_mode, antialias, frontend, test_flags, fn_tree, backend_fw, on_device) without return types