code: def test_partial_element_shape(
      self, compute_unit, backend, size_dynamic_shape
  ):
      size, dynamic_size, element_shape = size_dynamic_shape
  
      @make_tf_graph([(3, 1, 8)])
      def build_model(x):
          ta = tf.TensorArray(
              tf.float32,
              size=size,
              dynamic_size=dynamic_size,
              element_shape=element_shape,
          )
          ta = ta.scatter(indices=[0, 1, 2], value=x)
          return ta.read(0), ta.read(1), ta.read(2)
  
      model, inputs, outputs = build_model
      input_values = [np.random.rand(3, 1, 8).astype(np.float32)]
      input_dict = dict(zip(inputs, input_values))
      TensorFlowBaseTest.run_compare_tf(
          model,
          input_dict,
          outputs,
          compute_unit=compute_unit,
          backend=backend,
      )
  
imports: import itertools
  import numpy
  import pytest
  import coremltools
  from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.frontend.tensorflow.test.testing_utils import TensorFlowBaseTest
  from coremltools.converters.mil.frontend.tensorflow2.test.testing_utils import TensorFlow2BaseTest
  from coremltools.converters.mil.frontend.tensorflow2.test.testing_utils import make_tf2_graph
  from coremltools.converters.mil.testing_utils import random_gen
label_desc: Use image node_id 5 for calling the TestTensorList obj's underlying member method code with example usage: obj.test_partial_element_shape(compute_unit, backend, size_dynamic_shape) and returns: ta,  ta,  ta