如何在一个核心上运行Tensorflow？

Question

我在群集上使用Tensorflow,我想告诉Tensorflow只在一个核心上运行(即使有更多可用).

有人知道这是否可能？

Answer 1

要在一个CPU线程上运行Tensorflow,我使用:

session_conf = tf.ConfigProto(
      intra_op_parallelism_threads=1,
      inter_op_parallelism_threads=1)
sess = tf.Session(config=session_conf)

device_count 限制使用的CPU数量,而不是核心或线程数量.

tensorflow/tensorflow/core/protobuf/config.proto 说:

message ConfigProto {
  // Map from device type name (e.g., "CPU" or "GPU" ) to maximum
  // number of devices of that type to use.  If a particular device
  // type is not found in the map, the system picks an appropriate
  // number.
  map<string, int32> device_count = 1;

在Linux上,您可以运行sudo dmidecode -t 4 | egrep -i "Designation|Intel|core|thread"以查看您拥有多少CPU /核心/线程,例如,以下有2个CPU,每个CPU有8个核心,每个核心有2个线程,总共2*8*2 = 32主题:

fra@s:~$ sudo dmidecode -t 4 | egrep -i "Designation|Intel|core|thread"
    Socket Designation: CPU1
    Manufacturer: Intel
            HTT (Multi-threading)
    Version: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz
    Core Count: 8
    Core Enabled: 8
    Thread Count: 16
            Multi-Core
            Hardware Thread
    Socket Designation: CPU2
    Manufacturer: Intel
            HTT (Multi-threading)
    Version: Intel(R) Xeon(R) CPU E5-2667 v4 @ 3.20GHz
    Core Count: 8
    Core Enabled: 8
    Thread Count: 16
            Multi-Core
            Hardware Thread

使用Tensorflow 0.12.1和1.0.0使用Ubuntu 14.04.5 LTS x64和Ubuntu 16.04 LTS x64进行测试.