def model_stats():

    print("============================================================")

    print("List of all Trainable Variables")

    tvars = tf.trainable_variables()

    all_params = []

    for idx, v in enumerate(tvars):

        print(" var {:3}: {:15} {}".format(idx, str(v.get_shape()), v.name))

        num_params = 1

        param_list = v.get_shape().as_list()

        if(len(param_list)>1):

            for p in param_list:

                if(p>0):

                    num_params = num_params * int(p)

        else:

            all_params.append(param_list[0])

        all_params.append(num_params)

    print("Total number of trainable parameters {}".format(np.sum(all_params)))