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Artificial Intelligence
The branch of computer science dealing with the reproduction, or mimicking of human-level intelligence, self-awareness, knowledge, conscience, and thought in computer programs.
Here are 12,288 public repositories matching this topic...
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文本中如果有数字读不出来
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🐛 Bug
Trainer profilers are typehinted with the deprecated BaseProfiler instead of Profiler. This means that you cannot use class_path initialization of profilers with LightningCLI.
Error message:
- "pytorch_lightning.profiler.PyTorchProfiler" is not a subclass of <class 'pytorch_lightning.profiler.base.BaseProfiler'>
- Expected a <class 'str'> but got "{'class_path':
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Fix infered_model_type to inferred_model_type.
Is there an existing issue for this?
- I have searched the existing issues
What would you like to be added?
Current chunk manager didn't accept ctx for timeout and tracing control.
such as:
Read(ctx, Context, filePath string) ([]byte, error)
Why is this needed?
No response
Anything else?
No response
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We support toml as params file. There are a few issues with our current toml parsing:
- We use
tomllibrary, which is not toml 1.0 standard compatible. Also, the library is not being actively maintained. tomldumping does not preserve existing formatting.- iterative/dvc#6402
We can try migrating to tomli (which
Fedora & apt-get
Specs
- Leon version: latest
- OS (or browser) version: Fedora 30
- Node.js version: 10.16.3
- Complete "npm run check" output:
➡ Here is the diagnosis about your current setup
✔ Run
✔ Run modules
✔ Reply you by texting
❗ Amazon Polly text-to-speech
❗ Google Cloud text-to-speech
❗ Watson text-to-speech
❗ Offline text-to-speech
❗ Google Cloud speech-to-text
❗ Watson spee
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Interpret
Yes
TikaConverter requires tika to be running, which can be achieved by executing docker run -p 9998:9998 apache/tika:1.24.1. However, to simplify the usage of TikaConverter for users, it would be nice to have a method to launch the docker container from within Haystack. As an example, for our document stores, we have launch methods, such as [launch_es()](https://github.com/deepset-ai/haystack
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2019/12/02 和Yi Wang沟通交流考虑SQLFLOW可以支持如下的特性
一、基础功能:好用的工具需要一个更加简易友好的界面,让业务开发/分析更加简单
1)设计分析类工具,提供自动联想输入、快速语法、常见语义错误,提升用户体验
应用场景:提供IDE的自动联想功能,提高开发效率;语法和基本语义提前检查,避免提交到后台,执行较长时间后报错
2)大数据量时时间较长,建议提供任务(job)管理、允许用户了解数据执行的状态、监控进度、提供动态调试、watch能力,方便用户感知和调优
应用场景:耗时任务可以快速了解整体进度,提供一些中间的过程信息、耗时等,方便用户进行调优,优化开发
3) 安全权限、用户管理、
应用场景:增加新的数据分析人员、用户权