Type-Safe ML Configs with Hydra + Pydantic (Step by Step)
A practical, reproducible pattern for managing ML configurations: Hydra for composition & overrides, Pydantic for validation & type safety.
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A practical, reproducible pattern for managing ML configurations: Hydra for composition & overrides, Pydantic for validation & type safety.
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Today, I will demonstrate how we can use the PyTorch's Dataset and DataLoaders class to feed data into PyTorch models. If you are not familiar with Dataset classes, please take a look at my previous article here. I recommend you to go through the art...

Soooo. I was working on tuning a model for my college research thesis. I was already using YAML files to control parameters such as learning rates, dropout rates, so on. But, I also wanted to tune the model while changing the number of layers and neu...