帝王谷资源网 Design By www.wdxyy.com
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) <tf.Variable 'my/BatchNorm/beta:0' shape=(1,) dtype=float32_ref> [ 0.] <tf.Variable 'my/BatchNorm/moving_mean:0' shape=(1,) dtype=float32_ref> [ 13.46412563] <tf.Variable 'my/BatchNorm/moving_variance:0' shape=(1,) dtype=float32_ref> [ 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。
标签:
tensorflow,打印,变量
帝王谷资源网 Design By www.wdxyy.com
广告合作:本站广告合作请联系QQ:858582 申请时备注:广告合作(否则不回)
免责声明:本站文章均来自网站采集或用户投稿,网站不提供任何软件下载或自行开发的软件! 如有用户或公司发现本站内容信息存在侵权行为,请邮件告知! 858582#qq.com
免责声明:本站文章均来自网站采集或用户投稿,网站不提供任何软件下载或自行开发的软件! 如有用户或公司发现本站内容信息存在侵权行为,请邮件告知! 858582#qq.com
帝王谷资源网 Design By www.wdxyy.com
暂无评论...
更新日志
2024年12月23日
2024年12月23日
- 小骆驼-《草原狼2(蓝光CD)》[原抓WAV+CUE]
- 群星《欢迎来到我身边 电影原声专辑》[320K/MP3][105.02MB]
- 群星《欢迎来到我身边 电影原声专辑》[FLAC/分轨][480.9MB]
- 雷婷《梦里蓝天HQⅡ》 2023头版限量编号低速原抓[WAV+CUE][463M]
- 群星《2024好听新歌42》AI调整音效【WAV分轨】
- 王思雨-《思念陪着鸿雁飞》WAV
- 王思雨《喜马拉雅HQ》头版限量编号[WAV+CUE]
- 李健《无时无刻》[WAV+CUE][590M]
- 陈奕迅《酝酿》[WAV分轨][502M]
- 卓依婷《化蝶》2CD[WAV+CUE][1.1G]
- 群星《吉他王(黑胶CD)》[WAV+CUE]
- 齐秦《穿乐(穿越)》[WAV+CUE]
- 发烧珍品《数位CD音响测试-动向效果(九)》【WAV+CUE】
- 邝美云《邝美云精装歌集》[DSF][1.6G]
- 吕方《爱一回伤一回》[WAV+CUE][454M]