核心代码如下：
[tensor.name for tensor in tf.get_default_graph().as_graph_def().node]
实例代码：（加载了Inceptino_v3的模型，并获取该模型所有节点的名称）
# -*- coding: utf-8 -*- import tensorflow as tf import os model_dir = 'C:/Inception_v3' model_name = 'output_graph.pb' # 读取并创建一个图graph来存放训练好的 Inception_v3模型（函数） def create_graph(): with tf.gfile.FastGFile(os.path.join( model_dir, model_name), 'rb') as f: # 使用tf.GraphDef()定义一个空的Graph graph_def = tf.GraphDef() graph_def.ParseFromString(f.read()) # Imports the graph from graph_def into the current default Graph. tf.import_graph_def(graph_def, name='') # 创建graph create_graph() tensor_name_list = [tensor.name for tensor in tf.get_default_graph().as_graph_def().node] for tensor_name in tensor_name_list: print(tensor_name,'\n')
输出结果：
mixed_8/tower/conv_1/batchnorm/moving_variance mixed_8/tower/conv_1/batchnorm r_1/mixed/conv_1/batchnorm . . . mixed_10/tower_1/mixed/conv_1/CheckNumerics mixed_10/tower_1/mixed/conv_1/control_dependency mixed_10/tower_1/mixed/conv_1 pool_3 pool_3/_reshape/shape pool_3/_reshape input/BottleneckInputPlaceholder . . . . final_training_ops/weights/final_weights final_training_ops/weights/final_weights/read final_training_ops/biases/final_biases final_training_ops/biases/final_biases/read final_training_ops/Wx_plus_b/MatMul final_training_ops/Wx_plus_b/add final_result
由于结果太长了，就省略了一些。
如果不想这样print输出也可以将其写入txt 查看。
写入txt代码如下：
tensor_name_list = [tensor.name for tensor in tf.get_default_graph().as_graph_def().node] txt_path = './txt/节点名称' full_path = txt_path+ '.txt' for tensor_name in tensor_name_list: name = tensor_name + '\n' file = open(full_path,'a+') file.write(name) file.close()
以上这篇TensorFlow获取加载模型中的全部张量名称代码就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。