Artificial Intelligence

🐛 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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Willingness to contribute

The MLflow Community encourages new feature contributions. Would you or another member of your organization be willing to contribute an implementation of this feature (either as an MLflow Plugin or an enhancement to the MLflow code base)?

• Yes. I can contribute this f

Is there an existing issue for this?

• I have searched the existing issues

Environment

- Milvus version:2.0.2
- Deployment mode(standalone or cluster):standalone
- SDK version(e.g. pymilvus v2.0.0rc2):pymilvus 2.0.2, attu 2.0.5
- OS(Ubuntu or CentOS): CentOS
- CPU/Memory: 
- GPU: 
- Others:

Current Behavior

1. create collection with schema id, vector
   2

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

We currently have read and write capabilities but do not support deleting. We could add a few calls like delete delete_all and some recursive way of deleting.

Yes

When users run our tutorial notebooks, there are quite many convoluted log messages.

For example, there is the log message regarding apex and others:

"INFO - haystack.document_stores.base -  Numba not found, replacing njit() with no-op implementation. Enable it with 'pip install numba'.\n",
"INFO - haystack.modeling.model.optimization -  apex not found, won't use it. See https://nvidia.g