在没有GPU的情况下加载张量流时的错误消息

Question

当使用tensorflow时，我不想安装Cuda。现在，在用pip安装了当前版本(2.4.1)并运行任何代码后，我得到了一堆错误消息

2021-02-22 18:03:10.286577: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2021-02-22 18:03:10.286603: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2021-02-22 18:03:11.427455: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-02-22 18:03:11.427576: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcuda.so.1'; dlerror: libcuda.so.1: cannot open shared object file: No such file or directory
2021-02-22 18:03:11.427590: W tensorflow/stream_executor/cuda/cuda_driver.cc:326] failed call to cuInit: UNKNOWN ERROR (303)
2021-02-22 18:03:11.427607: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:156] kernel driver does not appear to be running on this host (XXX): /proc/driver/nvidia/version does not exist
2021-02-22 18:03:11.427774: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2021-02-22 18:03:11.427918: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set

它们由以下三行代码生成

import tensorflow as tf
from tensorflow import keras
model = keras.Sequential()

我知道一个类似问题的答案在不能加载动态库'cudart64_101.dll'在tensorflow仅CPU安装

但是解决方案建议通过设置环境变量来提高调试级别。不过，我确实希望收到有关我的编程不一致的警告。

真的没有办法单独禁用这些消息并使张量流接受我不想使用GPU或没有GPU吗？

Answer 1

您可以使用以下代码来禁用这些信息性的< code>I和警告< code>W消息。

import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'