A cookie associated with a cross-site resource at http://baidu.com/ was set without the `SameSite` attribute. A future release of Chrome will only deliver cookies with cross-site requests if they are set with `SameSite=None` and `Secure`. You can review cookies in developer tools under Application>Storage>Cookies and see more details at https://www.chromestatus.com/feature/5088147346030592 and https://www.chromestatus.com/feature/5633521622188032.", source: http://192.168.66.236:8088/index (0)

这似乎是一个关于Chrome浏览器的警告信息，提示某个网站（http://baidu.com/）设置的cookie缺少了`SameSite`属性，未来的Chrome浏览器只会发送带有`SameSite=None`和`Secure`属性的cookie请求。你可以通过浏览器开发工具中的Application>Storage>Cookies来查看cookie的详细信息，也可以在https://www.chromestatus.com/feature/5088147346030592和https://www.chromestatus.com/feature/5633521622188032中了解更多信息。

相关问题

cef A cookie associated with a cross-site resource

`cef`是指Chromium Embedded Framework，是一个嵌入式的Web浏览器控件，可以嵌入到本地应用程序中。而"A cookie associated with a cross-site resource"则表示某个cookie与跨站点资源相关联，可能会出现跨站点请求伪造（CSRF）的风险。这个警告信息也与Chrome浏览器的警告类似，建议设置`SameSite=None`和`Secure`属性来防止CSRF攻击。

Intel MKL FATAL ERROR: Cannot load /opt/anaconda3/lib/python3.10/site-packages/mkl/../../../libmkl_rt.so.1

The error message you encountered indicates that there is an issue loading the Intel Math Kernel Library (MKL) dynamic library file `libmkl_rt.so.1` in your Python environment. This error can occur due to various reasons, such as incorrect installation or configuration issues.

Here are a few steps you can try to resolve the issue:

1. Check MKL Installation: Ensure that Intel MKL is properly installed on your system. You can visit the official Intel website and follow the instructions to download and install the MKL library for your operating system.

2. Verify Library Path: Confirm that the library path specified in the error message (`/opt/anaconda3/lib/python3.10/site-packages/mkl/../../../libmkl_rt.so.1`) is correct. It should point to the location of the `libmkl_rt.so.1` file on your system. Make sure the file exists at that location.

3. Update LD_LIBRARY_PATH: Set the `LD_LIBRARY_PATH` environment variable to include the directory where the `libmkl_rt.so.1` file is located. You can do this by running the following command before executing your Python script:

   export LD_LIBRARY_PATH=/path/to/mkl:$LD_LIBRARY_PATH

Replace `/path/to/mkl` with the actual directory path containing the `libmkl_rt.so.1` file.

4. Conda Environment Activation: If you are using Anaconda or Miniconda, try activating your conda environment before running the Python script. This ensures that the correct MKL libraries associated with your environment are loaded.

5. Reinstall Libraries: If the above steps do not resolve the issue, you can try reinstalling the relevant libraries, including NumPy, MKL, and any other packages that depend on them. You can use the following commands:

   conda uninstall numpy mkl
   conda install numpy mkl

This will uninstall and then reinstall the NumPy and MKL libraries using conda.

If the issue still persists after trying these steps, it would be helpful to provide more information about your system configuration, the specific steps you followed during the installation, and any additional error messages or traceback information you received.