Artificial Intelligence

📚 Documentation

DDP optimizations for find_unused_parameters and tuning NCCL parameters are listed here: https://pytorch-lightning.readthedocs.io/en/latest/guides/speed.html#when-using-ddp-plugins-set-find-unused-parameters-false

However, there's another section on the doc which explicitly talks about DDP optimizations here: https://pytorch-lightning.readthedocs.io/en/latest/advanced/ad

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 your feature request related to a problem? Please describe.

Currently, if a user insert failed, client has to retry the whole batch, which incur duplicated entities in the system.
If user define primary key then later on we will support primary key deduplication to solve the problem.
For auto increment p

We support toml as params file. There are a few issues with our current toml parsing:

1. We use toml library, which is not toml 1.0 standard compatible. Also, the library is not being actively maintained.
2. toml dumping does not preserve existing formatting.
3. iterative/dvc#6402

We can try migrating to tomli (which

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 - beginner

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

Metaflow currently supports Py>=3.4 (with limited support for Py2.7) and R>=3.8. The GH tests only test for Py3.7 and R4.1. We should ensure we test on the whole set of permutations.