transfer denseConv ckpt to pb file error

[bolyor]

What did I do : python train_ocr_layer.py After I got ckpt file, I try to transfer it into pb file with code:

import tensorflow as tf
from tensorflow.python.framework import graph_util

def freeze_graph(input_checkpoint, output_graph):
    '''
    :param input_checkpoint:
    :param output_graph: PB模型保存路径
    :return:
    '''
    model_folder = './checkpoints/'
    checkpoint = tf.train.get_checkpoint_state(model_folder) #检查目录下ckpt文件状态是否可用
    input_checkpoint = checkpoint.model_checkpoint_path #得ckpt文件路径

    # 指定输出的节点名称,该节点名称必须是原模型中存在的节点
    output_node_names = "group_deps"
    saver = tf.train.import_meta_graph(input_checkpoint + '.meta', clear_devices=True)
    graph = tf.get_default_graph()  # 获得默认的图
    input_graph_def = graph.as_graph_def()  # 返回一个序列化的图代表当前的图

    with tf.Session() as sess:
        saver.restore(sess, input_checkpoint)  # 恢复图并得到数据
        output_graph_def = graph_util.convert_variables_to_constants(  # 模型持久化，将变量值固定
            sess=sess,
            input_graph_def=input_graph_def,  # 等于:sess.graph_def
            output_node_names=output_node_names.split(","))  # 如果有多个输出节点，以逗号隔开

        with tf.gfile.GFile(output_graph, "wb") as f:  # 保存模型
            f.write(output_graph_def.SerializeToString())  # 序列化输出
        print("%d ops in the final graph." % len(output_graph_def.node))  # 得到当前图有几个操作节点

        for op in graph.get_operations():
             print(op.name, op.values())

if __name__ == '__main__':

    input_checkpoint = './checkpoints/denseConv0.ckpt'
    output_graph = './checkpoints/frozen_graph.pb'
    freeze_graph(input_checkpoint, output_graph)

After I got pb file, I just can`t open it with tensorborad or transfer it into ONNX. I got this error message:

Traceback (most recent call last):
  File "/home/cenhong/.local/lib/python3.6/site-packages/tensorflow/python/framework/importer.py", line 418, in import_graph_def
    graph._c_graph, serialized, options)  # pylint: disable=protected-access
tensorflow.python.framework.errors_impl.InvalidArgumentError: Input 0 of node import/model/batchnorm/AssignMovingAvg was passed float from import/model/batchnorm//moving_mean:0 incompatible with expected float_ref.

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/cenhong/.local/bin/tfpb_tensorboard", line 11, in <module>
    load_entry_point('doml', 'console_scripts', 'tfpb_tensorboard')()
  File "/home/cenhong/do-ml/scripts/tfpb_tensorboard.py", line 33, in main
    tfpb_tensorboard(args.input_path, args.log_path, 6006 if args.port is None else args.port)
  File "/home/cenhong/do-ml/scripts/tfpb_tensorboard.py", line 18, in tfpb_tensorboard
    g_in = tf.import_graph_def(graph_def)
  File "/home/cenhong/.local/lib/python3.6/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
    return func(*args, **kwargs)
  File "/home/cenhong/.local/lib/python3.6/site-packages/tensorflow/python/framework/importer.py", line 422, in import_graph_def
    raise ValueError(str(e))
ValueError: Input 0 of node import/model/batchnorm/AssignMovingAvg was passed float from import/model/batchnorm//moving_mean:0 incompatible with expected float_ref.

Does anyone know how to solve this? Thanks.