今天小编就为大家分享一篇tensorflow 打印内存中的变量方法，具有很好的参考价值，希望对大家有所帮助。一起跟随小编过来看看吧
法一：
循环打印
模板
for (x, y) in zip(tf.global_variables(), sess.run(tf.global_variables())): print 'n', x, y
实例
# coding=utf-8 import tensorflow as tf def func(in_put, layer_name, is_training=True): with tf.variable_scope(layer_name, reuse=tf.AUTO_REUSE): bn = tf.contrib.layers.batch_norm(inputs=in_put, decay=0.9, is_training=is_training, updates_collections=None) return bn def main(): with tf.Graph().as_default(): # input_x input_x = tf.placeholder(dtype=tf.float32, shape=[1, 4, 4, 1]) import numpy as np i_p = np.random.uniform(low=0, high=255, size=[1, 4, 4, 1]) # outputs output = func(input_x, 'my', is_training=True) with tf.Session() as sess: sess.run(tf.global_variables_initializer()) t = sess.run(output, Feed_dict={input_x:i_p}) # 法一： 循环打印 for (x, y) in zip(tf.global_variables(), sess.run(tf.global_variables())): print 'n', x, y if __name__ == "__main__": main()
2017-09-29 10:10:22.714213: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1052] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GTX 1070, pci bus id: 0000:01:00.0, compute capability: 6.1) [ 0.] [ 13.46412563] [ 452.62246704] Process finished with exit code 0
法二：
指定变量名打印
模板
print 'my/Batchnorm/beta:0', (sess.run('my/Batchnorm/beta:0'))
实例
# coding=utf-8 import tensorflow as tf def func(in_put, layer_name, is_training=True): with tf.variable_scope(layer_name, reuse=tf.AUTO_REUSE): bn = tf.contrib.layers.batch_norm(inputs=in_put, decay=0.9, is_training=is_training, updates_collections=None) return bn def main(): with tf.Graph().as_default(): # input_x input_x = tf.placeholder(dtype=tf.float32, shape=[1, 4, 4, 1]) import numpy as np i_p = np.random.uniform(low=0, high=255, size=[1, 4, 4, 1]) # outputs output = func(input_x, 'my', is_training=True) with tf.Session() as sess: sess.run(tf.global_variables_initializer()) t = sess.run(output, Feed_dict={input_x:i_p}) # 法二： 指定变量名打印 print 'my/Batchnorm/beta:0', (sess.run('my/Batchnorm/beta:0')) print 'my/Batchnorm/moving_mean:0', (sess.run('my/Batchnorm/moving_mean:0')) print 'my/Batchnorm/moving_variance:0', (sess.run('my/Batchnorm/moving_variance:0')) if __name__ == "__main__": main()
2017-09-29 10:12:41.374055: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1052] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce GTX 1070, pci bus id: 0000:01:00.0, compute capability: 6.1) my/Batchnorm/beta:0 [ 0.] my/Batchnorm/moving_mean:0 [ 8.08649635] my/Batchnorm/moving_variance:0 [ 368.03442383] Process finished with exit code 0
以上这篇tensorflow 打印内存中的变量方法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编程之家。
