code: def test_tensorflow__array__(
      dtype_and_x,
      dtype,
      frontend,
      backend_fw,
  ):
      input_dtype, x = dtype_and_x
      dtype[0] = np.dtype(dtype[0])
      ret_gt = tf.constant(x[0]).__array__(dtype[0])
      with BackendHandler.update_backend(backend_fw) as ivy_backend:
          local_importer = ivy_backend.utils.dynamic_import
          function_module = local_importer.import_module(
              "ivy.functional.frontends.tensorflow"
          )
          ret = function_module.constant(x[0]).__array__(dtype[0])
      helpers.value_test(
          ret_np_flat=ret.ravel(),
          ret_np_from_gt_flat=ret_gt.ravel(),
          ground_truth_backend="tensorflow",
          backend=backend_fw,
      )
  
imports: from hypothesis import strategies, given, assume
  import numpy
  import tensorflow
  import ivy
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_method, BackendHandler
  from ivy_tests.test_ivy.test_frontends.test_tensorflow.test_raw_ops import _pow_helper_shared_dtype
  from ivy.functional.frontends.tensorflow import EagerTensor
label_desc: Use image node_id 5 for calling a global function with example usage: test_tensorflow__array__(dtype_and_x, dtype, frontend, backend_fw) without return types