核心程式碼如下：

[tensor.name for tensor in tf.get_default_graph().as_graph_def().node]

例項程式碼：（載入了Inceptino_v3的模型，並獲取該模型所有節點的名稱）

# -*- coding: utf-8 -*-
 
import tensorflow as tf
import os
 
model_dir = 'C:/Inception_v3'
model_name = 'output_graph.pb'
 
# 讀取並建立一個圖graph來存放訓練好的 Inception_v3模型（函式）
def create_graph():
 with tf.gfile.FastGFile(os.path.join(
   model_dir,model_name),'rb') as f:
  # 使用tf.GraphDef()定義一個空的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='')
 
# 建立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')

輸出結果：

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

由於結果太長了，就省略了一些。

如果不想這樣print輸出也可以將其寫入txt 檢視。

寫入txt程式碼如下：

tensor_name_list = [tensor.name for tensor in tf.get_default_graph().as_graph_def().node]
 
txt_path = './txt/節點名稱'
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()

以上這篇TensorFlow獲取載入模型中的全部張量名稱程式碼就是小編分享給大家的全部內容了，希望能給大家一個參考，也希望大家多多支援我們。