Artificial Intelligence

🐛 Bug

tuner.scale_batch_size finds the suitable batch size and update the batch size of the model AND datamodule.
For the model, tuner.scale_batch_size updates the batch size in the model regardless of model.batch_size and model.hparams.batch_size.

However, for the datamodule, tuner.scale_batch_size updates datamodule.batch_size only, and keep datamodule.hparams.batch_size

We recently deprecated --no-conda flag, but our examples still use it. They should be updated to use --env-manager=local instead.

https://github.com/mlflow/mlflow/blame/master/examples/pytorch/AxHyperOptimizationPTL/README.md#L26

mlflow run . --no-conda

The code above needs be fixed to the following:

mlflow run . --env-manager=local

Is there an existing issue for this?

• I have searched the existing issues

What would you like to be added?

When a user reports a bug in an issue, in addition to "Environment", "Current Behavior", "Expected Behavior", and "Steps To Reproduce", a "Milvus log" needs to be added to the issue template.

![image](https://user-images.githubusercontent.com/53512883/162382819-86855bd6-7f6

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.