tensorboard --logdir=runs 不工作:中止陷阱:6

问题描述

我正在尝试运行张量板:tensorboard --logdir=runs.
我也试过:tensorboard --logdir=runs --host=127.0.0.1.
我正在从包含 runs 文件夹的目录中的终端运行命令.

我收到以下错误:

[libprotobuf FATAL external/com_google_protobuf/src/google/protobuf/descriptor.cc:1367]检查失败:GeneratedDatabase()->Add(encoded_file_descriptor, size):libc++abi.dylib:以 google::protobuf::FatalException 类型的未捕获异常终止:检查失败:GeneratedDatabase()->Add(encoded_file_descriptor, size):中止陷阱:6

我的 Python 代码包含以下几行:

tb_path = './runs/SimpleLSTM_MNIST'如果 os.path.isdir(tb_path):关闭.rmtree(tb_path)writer = tb.SummaryWriter(log_dir=tb_path)

我的runs文件夹包含文件夹SimpleLSTM_MNIST，其中包含events.out.tfevents.1591953948.computername.local.29440.0.>

操作系统:MacOS Catalina

我该如何解决问题?

解决方案

显然这是在运行 macOS Catalina 时出现的特定问题，可以通过切换到 protobuf version 3.8 来解决.0 和 tensorflow 版本 2.0.0.
所以基本上卸载 tensorflow 和 protobuf 并重新安装 pip3 install protobuf==3.8.0 和 pip3 install tensorflow==2.0.0.

I am trying to run tensorboard: tensorboard --logdir=runs.
I have also tried: tensorboard --logdir=runs --host=127.0.0.1.
I am running the command from the terminal from within the the directory, which contains the runs folder.

I get the following error:

[libprotobuf FATAL external/com_google_protobuf/src/google/protobuf/descriptor.cc:1367]
CHECK failed: GeneratedDatabase()->Add(encoded_file_descriptor, size):
libc++abi.dylib: terminating with uncaught exception of type google::protobuf::FatalException:
CHECK failed: GeneratedDatabase()->Add(encoded_file_descriptor, size):
Abort trap: 6

My Python code contains the following lines:

tb_path = './runs/SimpleLSTM_MNIST'
if os.path.isdir(tb_path):
    shutil.rmtree(tb_path)

writer = tb.SummaryWriter(log_dir=tb_path)

My runs folder contains the folder SimpleLSTM_MNIST, which contains events.out.tfevents.1591953948.computername.local.29440.0.

Operating System: MacOS Catalina

How can I resolve the problem?

解决方案

Apparently this is a specific issue that occurs when running macOS Catalina, and can be solved by switching to protobuf version 3.8.0 and tensorflow version 2.0.0.
So basically uninstalling tensorflow and protobuf and re-installing with pip3 install protobuf==3.8.0 and pip3 install tensorflow==2.0.0.

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