tensorflow小技巧之查看保存模型参数的 name 和 value

简介# http://blog.csdn.net/u011961856/article/details/77064631 # coding:utf-8 # tensorflow模型保存文件分析 import tensorflow as tf import os from tensorflow.python import pywrap_tensorflow # # 保存model # v1 = tf.Variable(tf.random_normal([784, 200], stddev=0.
# http://blog.csdn.net/u011961856/article/details/77064631
# coding:utf-8
# tensorflow模型保存文件分析
import tensorflow as tf
import os
from tensorflow.python import pywrap_tensorflow

# # 保存model
# v1 = tf.Variable(tf.random_normal([784, 200], stddev=0.35), name="v1")
# v2 = tf.Variable(tf.zeros([200]), name="v2")
# v3 = tf.Variable(tf.zeros([100]), name="v3")
# saver = tf.train.Saver()
# with tf.Session() as sess:
#     init_op = tf.global_variables_initializer()
#     sess.run(init_op)
#     # saver.save(sess,"model.ckpt",global_step=1)
#     saver.save(sess, "./model.ckpt")

# 恢复model
# with tf.Session() as sess:
#     saver.restore(sess, "./model.ckpt-10.index")

# http://blog.csdn.net/u010698086/article/details/77916532
# 显示打印模型的信息
model_dir = ".\checkpoints\ped2_l_2_alpha_1_lp_1.0_adv_0.05_gdl_1.0_flow_2.0_channel_1_flow_2_his_6_numobject_5"
checkpoint_path = os.path.join(model_dir, "model.ckpt-10")
reader = pywrap_tensorflow.NewCheckpointReader(checkpoint_path)
var_to_shape_map = reader.get_variable_to_shape_map()
var_to_shape_map = sorted(var_to_shape_map)
for key in var_to_shape_map:
    print("tensor_name: ", key)
    print(reader.get_tensor(key))  # Remove this is you want to print only variable names
本文转自:https://blog.csdn.net/fovever_/article/details/106016132