message: Parameterize the mlir_coverage_test and add mobilenet_v2 to test.
  New models will should add new parameterized values to run.
diff: @@ -31,6 +31,7 @@ from tensorflow.lite.python import util as _util
  from tensorflow.python import keras as _keras
  from tensorflow.python.client import session as _session
  from tensorflow.python.framework import constant_op
  +from tensorflow.python.framework import ops
  from tensorflow.python.framework.importer import import_graph_def as _import_graph_def
  from tensorflow.python.keras.preprocessing import image
  from tensorflow.python.lib.io import file_io as _file_io
  @@ -178,7 +179,6 @@ def evaluate_frozen_graph(filename, input_arrays, output_arrays):
  Returns:
  Lambda function ([np.ndarray data] : [np.ndarray result]).
  """
  - with _session.Session().as_default() as sess:
  with _file_io.FileIO(filename, "rb") as f:
  file_content = f.read()
  @@ -192,12 +192,18 @@ def evaluate_frozen_graph(filename, input_arrays, output_arrays):
  else:
  file_content = file_content.encode("utf-8")
  _text_format.Merge(file_content, graph_def)
  +
  + graph = ops.Graph()
  + with graph.as_default():
  _import_graph_def(graph_def, name="")
  + inputs = _util.get_tensors_from_tensor_names(graph, input_arrays)
  + outputs = _util.get_tensors_from_tensor_names(graph, output_arrays)
  - inputs = _util.get_tensors_from_tensor_names(sess.graph, input_arrays)
  - outputs = _util.get_tensors_from_tensor_names(sess.graph, output_arrays)
  + def run_session(input_data):
  + with _session.Session(graph=graph) as sess:
  + return sess.run(outputs, dict(zip(inputs, input_data)))
  - return lambda input_data: sess.run(outputs, dict(zip(inputs, input_data)))
  + return run_session
  def evaluate_saved_model(directory, tag_set, signature_key):
  