def assertExportable(self, model, batch_size=<NUM_LIT:1>):
batch_shape = [batch_size]<EOL>input_shape = batch_shape + model.input.shape[<NUM_LIT:1>:].as_list()<EOL>dtype = model.input.dtype.as_numpy_dtype()<EOL>model_dir = self.create_tempdir()<EOL>tfk.experimental.export_saved_model(model, model_dir.full_path)<EOL>model_copy = tfk.experimental.load_from_saved_model(model_dir.full_path)<EOL>x = np.random.uniform(-<NUM_LIT>, <NUM_LIT>, input_shape).astype(dtype)<EOL>self.assertAllEqual(self.evaluate(model(x)), self.evaluate(model_copy(x)))<EOL>self.assertAllEqual(model.predict(x), model_copy.predict(x))<EOL>
Assert a Keras model supports export_saved_model/load_from_saved_model.

        Arguments:
          model: A Keras model with Tensor output.
          batch_size: The batch size to use when checking that the model produces
            the same results as a serialized/deserialized copy.  Default value: 1.