昨天，我正在使用TensorFlow的Conda构建（即TF v1.12 ：）进行一些性能测试。>
conda create -n tf_conda python=3.6.8 tensorflow git clone -b cnn_tf_v1.12_compatible --single-branch https://github.com/tensorflow/benchmarks.git cd benchmarks/scripts/tf_cnn_benchmarks/ conda activate tf_conda python tf_cnn_benchmarks.py --device=cpu --model=resnet50 --data_format=NHWC --num_batches=10 --num_warmup_batches=1今天，当我在Conda中安装TensorFlow时，我得到的是v1.13：
conda create -n tf_conda python=3.6.8 tensorflow git clone -b cnn_tf_v1.13_compatible --single-branch https://github.com/tensorflow/benchmarks.git cd benchmarks/scripts/tf_cnn_benchmarks/ conda activate tf_conda python tf_cnn_benchmarks.py --device=cpu --model=resnet50 --data_format=NHWC --num_batches=10 --num_warmup_batches=1但是，基准测试失败了：
2019-04-05 08:41:04.146441: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX 2019-04-05 08:41:04.164798: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2599995000 Hz 2019-04-05 08:41:04.165499: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x563d6af00290 executing computations on platform Host. Devices: 2019-04-05 08:41:04.165542: I tensorflow/compiler/xla/service/service.cc:158] StreamExecutor device (0): <undefined>, <undefined> OMP: Info #212: KMP_AFFINITY: decoding x2APIC ids. OMP: Info #213: KMP_AFFINITY: cpuid leaf 11 not supported - decoding legacy APIC ids. OMP: Info #149: KMP_AFFINITY: Affinity capable, using global cpuid info OMP: Info #154: KMP_AFFINITY: Initial OS proc set respected: 0-3 OMP: Info #156: KMP_AFFINITY: 4 available OS procs OMP: Info #157: KMP_AFFINITY: Uniform topology OMP: Info #159: KMP_AFFINITY: 4 packages x 1 cores/pkg x 1 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 OMP: Info #171: KMP_AFFINITY: OS proc 1 maps to package 1 OMP: Info #171: KMP_AFFINITY: OS proc 2 maps to package 2 OMP: Info #171: KMP_AFFINITY: OS proc 3 maps to package 3 OMP: Info #250: KMP_AFFINITY: pid 1539 tid 1539 thread 0 bound to OS proc set 0 2019-04-05 08:41:04.166391: I tensorflow/core/common_runtime/process_util.cc:71] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance. W0405 08:41:04.172703 140193590863680 deprecation.py:323] From /home/nsapay/anaconda3/envs/tf_conda/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version. Instructions for updating: Colocations handled automatically by placer. ... OMP: Info #250: KMP_AFFINITY: pid 1539 tid 1557 thread 1 bound to OS proc set 1 OMP: Info #250: KMP_AFFINITY: pid 1539 tid 1585 thread 3 bound to OS proc set 3 OMP: Info #250: KMP_AFFINITY: pid 1539 tid 1586 thread 4 bound to OS proc set 0 OMP: Info #250: KMP_AFFINITY: pid 1539 tid 1584 thread 2 bound to OS proc set 2 OMP: Info #250: KMP_AFFINITY: pid 1539 tid 1556 thread 5 bound to OS proc set 1 OMP: Info #250: KMP_AFFINITY: pid 1539 tid 1588 thread 7 bound to OS proc set 3 OMP: Info #250: KMP_AFFINITY: pid 1539 tid 1587 thread 6 bound to OS proc set 2 OMP: Info #250: KMP_AFFINITY: pid 1539 tid 1589 thread 8 bound to OS proc set 0 Killed.我完全感到困惑……昨天和今天之间我没有更新系统。我正在使用4个（虚拟）内核（Intel Xeon E3）和常规的CentOS 7发行版。
[昨天，我使用TensorFlow的Conda版本运行了一些性能测试，即TF v1.12：conda create -n tf_conda python = 3.6.8 tensorflow git clone -b cnn_tf_v1.12_compatible --single-branch ...] >
确实，我内存不足。内存监视来自另一个虚拟机（同时使用多个计算机带来的不便）。