Configs

Overview

Use the configs layer when you want reproducible experiment specifications for benchmark runs, smoke tests, and hazard-specific model comparisons.

What This Page Covers

  • pyhazards.configs dataclasses and YAML loading helpers

  • hazard-scoped smoke configs under pyhazards/configs/<hazard>/

  • the shared structure for benchmark, dataset, model, and report settings

Typical Usage

from pyhazards.configs import load_experiment_config

config = load_experiment_config("pyhazards/configs/flood/hydrographnet_smoke.yaml")
print(config.benchmark.hazard_task)
print(config.model.name)

Config Layout

Each experiment config contains four sections:

  • benchmark: which evaluator to run and which hazard task to score

  • dataset: which registered dataset to load and with which parameters

  • model: which registered model to build and with which parameters

  • report: where to write JSON, Markdown, or CSV outputs

Next step: pair this page with Benchmarks when you want to match configs to implemented evaluation paths, and with Reports when you want to export benchmark outputs.