在 Keras 上使用 TensorFlow 后端时的奇怪输出（OMP：Info #xx KMP_AFFINITY）

Question

我使用带有 TensorFlow 后端的 Keras 来训练神经网络模型。这是一个简单的模型（来自教程），一切正常。模型预测它应该的方式。似乎只有 tensorflow 输出信息，我不知道我是否可以安全地忽略它/它意味着什么。有人能解释一下下面的输出告诉我们什么吗？尤其是所有以 开头的台词OMP我都不清楚。弃用警告并没有真正让我担心。

Using TensorFlow backend.
OMP: Info #212: KMP_AFFINITY: decoding x2APIC ids.
OMP: Info #210: KMP_AFFINITY: Affinity capable, using global cpuid leaf 11 info
OMP: Info #154: KMP_AFFINITY: Initial OS proc set respected: 0-7
OMP: Info #156: KMP_AFFINITY: 8 available OS procs
OMP: Info #157: KMP_AFFINITY: Uniform topology
OMP: Info #179: KMP_AFFINITY: 1 packages x 4 cores/pkg x 2 threads/core (4 total cores)
OMP: Info #214: KMP_AFFINITY: OS proc to physical thread map:
OMP: Info #171: KMP_AFFINITY: OS proc 0 maps to package 0 core 0 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 1 maps to package 0 core 0 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 2 maps to package 0 core 1 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 3 maps to package 0 core 1 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 4 maps to package 0 core 2 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 5 maps to package 0 core 2 thread 1 
OMP: Info #171: KMP_AFFINITY: OS proc 6 maps to package 0 core 3 thread 0 
OMP: Info #171: KMP_AFFINITY: OS proc 7 maps to package 0 core 3 thread 1 
OMP: Info #250: KMP_AFFINITY: pid 14400 tid 5252 thread 0 bound to OS proc set 0
WARNING: Logging before flag parsing goes to stderr.
W0820 14:05:56.256548  5252 deprecation.py:323] From C:\Users\Gebruiker\Anaconda3\envs\Anaconda3.7\lib\site-packages\tensorflow\python\ops\nn_impl.py:180: add_dispatch_support.<locals>.wrapper (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.where in 2.0, which has the same broadcast rule as np.where
2019-08-20 14:05:56.449349: I tensorflow/core/platform/cpu_feature_guard.cc:145] This TensorFlow binary is optimized with Intel(R) MKL-DNN to use the following CPU instructions in performance critical operations:  AVX AVX2
To enable them in non-MKL-DNN operations, rebuild TensorFlow with the appropriate compiler flags.
2019-08-20 14:05:56.451182: I tensorflow/core/common_runtime/process_util.cc:115] Creating new thread pool with default inter op setting: 8. Tune using inter_op_parallelism_threads for best performance.
OMP: Info #250: KMP_AFFINITY: pid 14400 tid 13256 thread 1 bound to OS proc set 2
OMP: Info #250: KMP_AFFINITY: pid 14400 tid 5064 thread 2 bound to OS proc set 4
OMP: Info #250: KMP_AFFINITY: pid 14400 tid 8904 thread 3 bound to OS proc set 6
OMP: Info #250: KMP_AFFINITY: pid 14400 tid 9408 thread 4 bound to OS proc set 1
OMP: Info #250: KMP_AFFINITY: pid 14400 tid 14360 thread 5 bound to OS proc set 3
OMP: Info #250: KMP_AFFINITY: pid 14400 tid 14616 thread 6 bound to OS proc set 5
OMP: Info #250: KMP_AFFINITY: pid 14400 tid 2692 thread 7 bound to OS proc set 7
OMP: Info #250: KMP_AFFINITY: pid 14400 tid 14172 thread 8 bound to OS proc set 0

Answer 1

OpenMP 正在将线程绑定到您的 CPU 以运行。这只是后勤输出，我不会担心。您可以在此处找到记录的类似输出。

英特尔® 编译器的 OpenMP* 运行时库能够将 OpenMP* 线程绑定到物理处理单元。

本文将向您展示如何使用来自英特尔编译器的 KMP_AFFINITY 环境变量扩展（高级关联接口）来确定机器拓扑并根据处理器在机器中的物理位置将 OpenMP* 线程分配给处理器。

示例 1：

您拥有一个启用了英特尔® 超线程技术（英特尔® HT 技术）的四核系统。默认情况下，英特尔编译器 OpenMP* 运行时库将创建 8 个线程，在操作系统提供的 8 个逻辑处理器上自由运行。

如上文所述，根据您的物理 CPU 配置，线程被分配给不同的内核。