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tensorflow中可以通过配置环境变量 'TF_CPP_MIN_LOG_LEVEL' 的值,控制tensorflow是否屏蔽通知信息、警告、报错等输出信息。
使用方法:
import os import tensorflow as tf os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # or any {'0', '1', '2'}
TF_CPP_MIN_LOG_LEVEL 取值 0 : 0也是默认值,输出所有信息
TF_CPP_MIN_LOG_LEVEL 取值 1 : 屏蔽通知信息
TF_CPP_MIN_LOG_LEVEL 取值 2 : 屏蔽通知信息和警告信息
TF_CPP_MIN_LOG_LEVEL 取值 3 : 屏蔽通知信息、警告信息和报错信息
测试代码:
import tensorflow as tf import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '0' # os.environ['TF_CPP_MIN_LOG_LEVEL'] = '1' # os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2' # os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' v1 = tf.constant([1.0, 2.0, 3.0], shape=[3], name='v1') v2 = tf.constant([1.0, 2.0, 3.0], shape=[3], name='v2') sumV12 = v1 + v2 with tf.Session(config=tf.ConfigProto(log_device_placement=True)) as sess: print sess.run(sumV12)
TF_CPP_MIN_LOG_LEVEL 为 0 的输出:
2018-04-21 14:59:09.910415: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. 2018-04-21 14:59:09.910442: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. 2018-04-21 14:59:09.910448: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. 2018-04-21 14:59:09.910453: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. 2018-04-21 14:59:09.910457: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. 2018-04-21 14:59:09.911260: I tensorflow/core/common_runtime/direct_session.cc:300] Device mapping: 2018-04-21 14:59:09.911816: I tensorflow/core/common_runtime/simple_placer.cc:872] add: (Add)/job:localhost/replica:0/task:0/cpu:0 2018-04-21 14:59:09.911835: I tensorflow/core/common_runtime/simple_placer.cc:872] v2: (Const)/job:localhost/replica:0/task:0/cpu:0 2018-04-21 14:59:09.911841: I tensorflow/core/common_runtime/simple_placer.cc:872] v1: (Const)/job:localhost/replica:0/task:0/cpu:0 Device mapping: no known devices. add: (Add): /job:localhost/replica:0/task:0/cpu:0 v2: (Const): /job:localhost/replica:0/task:0/cpu:0 v1: (Const): /job:localhost/replica:0/task:0/cpu:0 [ 2. 4. 6.]
值为0也是默认的输出,分为三部分,一个是警告信息说没有优化加速,二是通知信息告知操作所用的设备,三是程序中代码指定要输出的结果信息
TF_CPP_MIN_LOG_LEVEL 为 1 的输出,没有通知信息了: 2018-04-21 14:59:09.910415: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. 2018-04-21 14:59:09.910442: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. 2018-04-21 14:59:09.910448: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. 2018-04-21 14:59:09.910453: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. 2018-04-21 14:59:09.910457: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. Device mapping: no known devices. add: (Add): /job:localhost/replica:0/task:0/cpu:0 v2: (Const): /job:localhost/replica:0/task:0/cpu:0 v1: (Const): /job:localhost/replica:0/task:0/cpu:0 [ 2. 4. 6.]
TF_CPP_MIN_LOG_LEVEL 为 2和3 的输出,设置为2就没有警告信息了,设置为3警告和报错信息(如果有)就都没有了:
Device mapping: no known devices. add: (Add): /job:localhost/replica:0/task:0/cpu:0 v2: (Const): /job:localhost/replica:0/task:0/cpu:0 v1: (Const): /job:localhost/replica:0/task:0/cpu:0 [ 2. 4. 6.]
以上这篇在tensorflow中实现屏蔽输出的log信息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。
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