我一直使用tensorflow没有问题,直到我添加了以下代码行:
log_dir = os.path.join("logs",
"fit",
datetime.datetime.now().strftime("%Y%m%d-%H%M%S"))
tensorboard_callback = TensorBoard(log_dir)
Run Code Online (Sandbox Code Playgroud)
运行此命令后,我会在控制台上打印大量信息。我尝试查看 tf.keras.callbacks.TensorBoard 文档,看看是否可以减少冗长,但我没有看到任何选项。
从各种stackoverflow 答案中,我也尝试设置tfdown 的详细程度,但无济于事:
tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.ERROR)
tf.get_logger().setLevel('ERROR')
tf.autograph.set_verbosity(3)
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
Run Code Online (Sandbox Code Playgroud)
我有以下规格:
Python = 3.8
Tensorflow = 2.3.1
Cuda Toolkit = 10.1
cuDNN = 7.6.4
GPU=Nvidia RTX2060
Run Code Online (Sandbox Code Playgroud)
打印到控制台的信息都是I消息,如果它们添加了任何重要的细节,我已将它们粘贴在下面。
2020-10-19 20:59:45.205887: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library cudart64_101.dll
2020-10-19 20:59:47.463539: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library nvcuda.dll
2020-10-19 20:59:48.540417: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1716] Found device 0 with properties:
pciBusID: 0000:01:00.0 name: GeForce RTX 2060 …Run Code Online (Sandbox Code Playgroud)