34 lines
1.2 KiB
Plaintext
34 lines
1.2 KiB
Plaintext
# MLflow Project — формат воспроизводимых экспериментов
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# ========================================================
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# Запуск:
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# mlflow run . -P n_estimators=100 -P max_depth=8
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# mlflow run . -P n_estimators=200 -P max_depth=12 --experiment-name digits_project
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#
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# MLflow автоматически:
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# 1. Создаст изолированное окружение из conda.yaml (или requirements.txt)
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# 2. Запустит entry point с указанными параметрами
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# 3. Логирует всё в MLflow tracking
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name: mlflow-practice
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python_env: python_env.yaml
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entry_points:
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main:
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parameters:
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n_estimators: {type: int, default: 100}
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max_depth: {type: int, default: 8}
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command: "python src/train_simple.py --n-estimators {n_estimators} --max-depth {max_depth}"
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gpu:
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parameters:
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epochs: {type: int, default: 10}
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batch_size: {type: int, default: 256}
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lr: {type: float, default: 0.001}
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command: "python src/train_gpu.py --epochs {epochs} --batch-size {batch_size} --lr {lr}"
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sweep:
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parameters:
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max_combos: {type: int, default: 20}
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command: "python src/hyperparam_sweep.py --max-combos {max_combos}"
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