def METHOD_NAME():
    import tensorflow as tf
    try:
        graph = tf.Graph()
        graph_def = tf.compat.v1.GraphDef()
        with tf.compat.v1.Session() as sess:
            x = tf.compat.v1.placeholder(tf.float32, shape=(1, 3, 3, 1), name="x")
            y = tf.constant(np.random.random((2, 2, 1, 1)).astype(np.float32), name="y")
            z = tf.constant(np.random.random((1, 1, 1, 1)).astype(np.float32), name="z")
            op = tf.nn.conv2d(input=tf.nn.relu(x), filters=y, strides=[1, 1, 1, 1], padding="VALID", name="op_to_store")
            op2 = tf.nn.conv2d(
                input=tf.nn.relu(op), filters=z, strides=[1, 1, 1, 1], padding="VALID", name="op2_to_store"
            )
            sess.run(tf.compat.v1.global_variables_initializer())
            constant_graph = tf.compat.v1.graph_util.convert_variables_to_constants(
                sess, sess.graph_def, ["op2_to_store"]
            )
        graph_def.ParseFromString(constant_graph.SerializeToString())
        with graph.as_default():
            tf.import_graph_def(graph_def, name="")
    except:
        graph = tf.Graph()
        graph_def = tf.compat.v1.GraphDef()
        with tf.compat.v1.Session() as sess:
            x = tf.compat.v1.placeholder(tf.float32, shape=(1, 3, 3, 1), name="x")
            y = tf.constant(np.random.random((2, 2, 1, 1)).astype(np.float32), name="y")
            z = tf.constant(np.random.random((1, 1, 1, 1)).astype(np.float32), name="z")
            op = tf.nn.conv2d(input=x, filters=y, strides=[1, 1, 1, 1], padding="VALID", name="op_to_store")
            op2 = tf.nn.conv2d(input=op, filters=z, strides=[1, 1, 1, 1], padding="VALID", name="op2_to_store")
            sess.run(tf.compat.v1.global_variables_initializer())
            constant_graph = tf.compat.v1.graph_util.convert_variables_to_constants(
                sess, sess.graph_def, ["op2_to_store"]
            )
        graph_def.ParseFromString(constant_graph.SerializeToString())
        with graph.as_default():
            tf.import_graph_def(graph_def, name="")
    return graph