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Describe the bug
Hello, first of all, thank you for making and maintaining Tauri.
So, 've been making a test app using Tauri. but it seems, the CTRL/COMMAND + Z keyboard shortcut ( along with many other keyboard shortcuts ) stops working inside the app.
I also have added a menu like this one: https://github.com/windht/watcher/blob/bd929e555319c3e6c4565a2631b63a04918c03fb/src-tauri/src/m
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Line 35 isFunction is missing, and code sandbox demo is broken.
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为什么取消了维持多巴胺中轴的目标呢?
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Is your feature request related to a problem? Please describe.
Recently noticed how many PHP based projects migrates from Travis-CI to GitHub Actions. I didn't try it yet, but after a quick reading I see that GitHub Actions has Ubuntu environment with preinstalled PHP from 7.4 to 8.1, while Travis CI offers [Bi
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- 目标提升到80%以上
- 如何获取单侧覆盖率:
- 项目根目录下运行
mvn test - 项目根目录下用浏览器打开
target/site/jacoco/index.html即可查看单侧覆盖率,点进去即可查看详细覆盖情况以作出补充
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Jun 16, 2022 - SVG
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scipy.stats.mode
It would be great if you could add the JAX equivalent of scipy.stats.mode, which is currently unavailable.
A use case may be a ML classification task with ensembles, where multiple models give different predictions, and we are interested in finding the most common one.
As an example, consider predictions to be a two-dimensional DeviceArray of predictions, with
shape = (number of model
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expected result:
example.com?param=abc -> will become example.com
example.com/?param=abc -> will stay example.com/
actual result:
example.com?param=abc -> become example.com
example.com/?param=abc -> stays example.com/?param=abc
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1、在使用PPOCRLabel进行图像标注的时候,图像上有很多文字有识别的需求,但有些位置的文字没有识别的需求,那么在进行标注的时候是否还需要对没有识别需求位置的文字进行标注呢?
2、在使用PPOCRLabel进行自动标注后,有些位置的文字被标注上了,但是还额外框住了其他不是文字的图案(软件的文字识别能够识别到正确的文字,但是这种情况出现的次数很多),还是否需要对标注框进行调整,来去除掉非文字的图案?不去除的话是否对最终文字识别网络模型造成影响呢?
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Perhaps we should document this issue in the FAQ? Using pre-commit with Black is pretty common (and it's not always instantly clear it passes all of the files to the hook directly bypassing any file discovery the hook may implement). I'd suggest pre-commit's exclude configurations first, and then black's force-exclude.
_Originally posted by @ichard26 in psf/black#3013
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Currently, there are following warnings when running tests:
test/test_models.py::test_quantized_classification_model[googlenet]
/root/project/torchvision/models/googlenet.py:47: FutureWarning: The default weight initialization of GoogleNet will be changed in future releases of torchvision. If you wish to keep the old behavior (which leads to long initialization times due to scipy/scipy#11
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