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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.
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Thank you for submitting a feature request. Before proceeding, please review MLflow's Issue Policy for feature requests and the MLflow Contributing Guide.
**Please fill in this feature request template to ensure a timely and thorough response.
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Is there an existing issue for this?
- I have searched the existing issues
What would you like to be added?
Every time something changes in milvus-io/milvus/tree/master/internal/proto we need to go to all the SDKs and copy the proto files. Ideally, all SDKs should have only one proto source. And this will also help to have a better documentation for people that want to use grpc dire
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
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Currently, when entering epic mode the README is frozen in the last level of the tower. When you're trying to fine-tune the score for a level other than the last one, it would be helpful if we had the README for that level available. The proposal is that when entering epic mode, the README is updated with all levels, one following the other.
Example:
# Starbolt - beginnerFedora & 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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Currently, you can do something like this: Task(Flow/RunID/StepName) and this will not result in an error but then the resulting Task object behaves in a bizarre manner where things like t.data will work but t.data.my_artifact will not for example.
We should validate the format of the pathspec passed in to each object and verify that the following are the only possible cases:
- Metaflo
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Proposed refactor
Deprecate this property:
https://github.com/PyTorchLightning/pytorch-lightning/blob/cf64f3443474a93d23b5afb0417e4a60298006e6/pytorch_lightning/trainer/trainer.py#L1982-L1984
Motivation
This property is redundant with the Strategy's
root_deviceproperty, which generalizes this check.Following https://