dvc.lock

schema: '2.0'
stages:
  load_data:
    cmd: rye run python src/hydra_dvc_practice/load_data.py
    deps:
    - path: src/hydra_dvc_practice/load_data.py
      hash: md5
      md5: 615eaf5882f5bc269938140317c166d3
      size: 1205
    params:
      params.yaml:
        paths:
          root_dir: /Users/masato/Projects/hydra-dvc-practice
          data_dir: /Users/masato/Projects/hydra-dvc-practice/data
          model_dir: /Users/masato/Projects/hydra-dvc-practice/data
        seed: 42
        target: target
        test_size: 0.2
    outs:
    - path: data/test.csv
      hash: md5
      md5: ac4a4f354095b5460a14885092b38a87
      size: 24647
    - path: data/train.csv
      hash: md5
      md5: 917798806c663e0530df6c3c0935d1ba
      size: 97230
  preprocess:
    cmd: rye run python src/hydra_dvc_practice/preprocess.py
    deps:
    - path: data/test.csv
      hash: md5
      md5: ac4a4f354095b5460a14885092b38a87
      size: 24647
    - path: data/train.csv
      hash: md5
      md5: 917798806c663e0530df6c3c0935d1ba
      size: 97230
    - path: src/hydra_dvc_practice/preprocess.py
      hash: md5
      md5: e54f10e62dfe0159a19ca334a6ef76ec
      size: 1494
    params:
      params.yaml:
        scaler:
          _target_: sklearn.preprocessing.StandardScaler
    outs:
    - path: data/test_scaled.csv
      hash: md5
      md5: 604030ade380161bb68a14341096521e
      size: 68205
    - path: data/train_scaled.csv
      hash: md5
      md5: ccfc37b667b60e661314dc2114f1e081
      size: 271019
  train:
    cmd: rye run python src/hydra_dvc_practice/train.py
    deps:
    - path: data/test_scaled.csv
      hash: md5
      md5: 604030ade380161bb68a14341096521e
      size: 68205
    - path: data/train_scaled.csv
      hash: md5
      md5: ccfc37b667b60e661314dc2114f1e081
      size: 271019
    - path: src/hydra_dvc_practice/train.py
      hash: md5
      md5: 21427cd4d3418df6fe0057cf910852eb
      size: 907
    params:
      params.yaml:
        model:
          _target_: sklearn.ensemble.RandomForestClassifier
          n_estimators: 100
          random_state: 42
    outs:
    - path: data/model.pkl
      hash: md5
      md5: ba084273631b3dfaed4f420a87dbea5b
      size: 326265
    - path: data/model_params.json
      hash: md5
      md5: 9d4e320b49303bf00d3f22564bf57432
      size: 413
  eval:
    cmd: rye run python src/hydra_dvc_practice/eval.py
    deps:
    - path: data/model.pkl
      hash: md5
      md5: ba084273631b3dfaed4f420a87dbea5b
      size: 326265
    - path: src/hydra_dvc_practice/eval.py
      hash: md5
      md5: 472a2b94f4d2bfabd532c7c0e7528301
      size: 1407
    outs:
    - path: data/evaluation_results.json
      hash: md5
      md5: f8b133ba46a8b8956177e0d4eaa81ae8
      size: 120
    - path: data/test_predictions.csv
      hash: md5
      md5: 47209c52c23fa51026e25fa409d59e4c
      size: 67357