code: def test_tensorflow_ivy_array(
      dtype_x,
      backend_fw,
  ):
      ivy.set_backend(backend_fw)
      _, data = dtype_x
      x = EagerTensor(data[0])
      ret = helpers.flatten_and_to_np(
          ret=x.ivy_array.data, backend=backend_fw
      )
      ret_gt = helpers.flatten_and_to_np(
          ret=data[0], backend=backend_fw
      )
      helpers.value_test(
          ret_np_flat=ret,
          ret_np_from_gt_flat=ret_gt,
          ground_truth_backend="tensorflow",
          backend=backend_fw,
      )
      ivy.previous_backend()
  
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 41 for calling a global function with example usage: test_tensorflow_ivy_array(dtype_x, backend_fw) without return types