def METHOD_NAME():
    def tensorlist_stack_model(input_shape):
        class TensorArrayStackLayer(tf.keras.layers.Layer):
            def __init__(self):
                super().__init__()
            def call(self, inputs):
                inputs = tf.squeeze(inputs)
                outputs = tf.TensorArray(
                    tf.float32,
                    size=inputs.shape[0],
                    infer_shape=False,
                    element_shape=inputs.shape[1:],
                )
                outputs = outputs.unstack(inputs)
                return outputs.stack()
        input_shape = (3, 32)
        model = tf.keras.Sequential(
            [tf.keras.layers.Input(shape=input_shape, batch_size=1), TensorArrayStackLayer()]
        )
        return model
    run_sequential_model(tensorlist_stack_model, input_shape=(3, 32))