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DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
As you can see from the Contributors graph here: https://github.com/microsoft/DeepSpeed/graphs/contributors there are plenty of contributors who could carry on in the event this was necessary.
Repository on GitHub, which uses git. git is distributed.
PyTest provided: https://github.com/microsoft/DeepSpeed/blob/239b83a77e952533439104fced9a72456a010a75/.github/workflows/nv-torch-latest-v100.yml#L58
Nightly CI runs for most jobs, and PR triggers are set where relevant.
警告:需要URL,但找不到URL。
The project does not output its own security software so there is no need for these protocols.
The software does not output any code that would need to rely on TLS.
// X-Content-Type-Options was not set to "nosniff".
This is covered by input parsing and validation of inputs, and the fact that the software wraps torch.
We do not have any dynamic code analysis yet - the closest thing we have are the unit tests that perform a variety of tests, but we understand this is not enough. We plan to add this in the near future.
This will not be added in the production builds, but will be added as a new pipeline running nightly or with a similar frequency.
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