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Merged
ethanglaser merged 4 commits into from
May 13, 2026
Merged

Add prettier json linter for uniformity #211

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a9a7d40
Add prettier json linter for uniformity
ethanglaser May 12, 2026
cca11de
Merge branch 'IntelPython:main' into dev/eglaser-config-linter
ethanglaser May 13, 2026
b61ccfa
linting
ethanglaser May 13, 2026
86cea88
lint again
ethanglaser May 13, 2026
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6 changes: 6 additions & 0 deletions .pre-commit-config.yaml
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Expand Up @@ -23,3 +23,9 @@ repos:
rev: 5.13.2
hooks:
- id: isort
- repo: https://github.com/pre-commit/mirrors-prettier
rev: v3.1.0
hooks:
- id: prettier
args: [--tab-width=4, --print-width=120]
files: ^configs/.*\.json$
6 changes: 3 additions & 3 deletions configs/common/svm.json
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Expand Up @@ -10,7 +10,7 @@
{
"algorithm": {
"library": "cuml",
"estimator_methods": {"inference": "predict"},
"estimator_methods": { "inference": "predict" },
"estimator_params": { "verbose": false, "multiclass_strategy": "ovr" }
},
"data": { "format": "cupy" }
Expand All @@ -27,7 +27,7 @@
{
"algorithm": {
"library": "cuml",
"estimator_methods": {"inference": "predict"},
"estimator_methods": { "inference": "predict" },
"estimator_params": { "multiclass_strategy": "ovr" }
},
"data": { "format": "cupy" }
Expand All @@ -43,7 +43,7 @@
{
"algorithm": {
"library": "cuml",
"estimator_methods": {"inference": "predict"}
"estimator_methods": { "inference": "predict" }
},
"data": { "format": "cupy" }
}
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2 changes: 1 addition & 1 deletion configs/common/xgboost.json
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Expand Up @@ -43,7 +43,7 @@
"algorithm": {
"library": "xgboost",
"estimator": "XGBRegressor",
"estimator_methods": {"inference": "predict"},
"estimator_methods": { "inference": "predict" },
"estimator_params": { "objective": "reg:squarederror" }
}
}
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7 changes: 1 addition & 6 deletions configs/regular/dbscan.json
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Expand Up @@ -35,12 +35,7 @@
]
},
"cuml dbscan": {
"SETS": [
"cuml implementation",
"common dbscan parameters",
"cuml dbscan parameters",
"dbscan datasets"
]
"SETS": ["cuml implementation", "common dbscan parameters", "cuml dbscan parameters", "dbscan datasets"]
}
}
}
8 changes: 1 addition & 7 deletions configs/regular/kmeans.json
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Expand Up @@ -51,7 +51,6 @@
"split_kwargs": { "train_size": 0.2, "test_size": null }
}
}

]
},
"TEMPLATES": {
Expand All @@ -64,12 +63,7 @@
]
},
"cuml kmeans": {
"SETS": [
"cuml implementation",
"common kmeans parameters",
"cuml kmeans parameters",
"kmeans datasets"
]
"SETS": ["cuml implementation", "common kmeans parameters", "cuml kmeans parameters", "kmeans datasets"]
}
}
}
26 changes: 19 additions & 7 deletions configs/regular/knn.json
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Expand Up @@ -18,16 +18,28 @@
"source": "make_classification",
"generation_kwargs": [
{
"n_classes": 5, "n_samples": 400000, "n_features": 4,
"n_redundant": 0, "n_repeated": 0, "n_informative": 4
"n_classes": 5,
"n_samples": 400000,
"n_features": 4,
"n_redundant": 0,
"n_repeated": 0,
"n_informative": 4
},
{
"n_classes": 5, "n_samples": 200000, "n_features": 8,
"n_redundant": 2, "n_repeated": 2, "n_informative": 4
"n_classes": 5,
"n_samples": 200000,
"n_features": 8,
"n_redundant": 2,
"n_repeated": 2,
"n_informative": 4
},
{
"n_classes": 5, "n_samples": 100000, "n_features": 16,
"n_redundant": 6, "n_repeated": 6, "n_informative": 4
"n_classes": 5,
"n_samples": 100000,
"n_features": 16,
"n_redundant": 6,
"n_repeated": 6,
"n_informative": 4
}
],
"split_kwargs": { "train_size": 0.5, "test_size": 0.5 }
Expand All @@ -48,7 +60,7 @@
},
{
"source": "make_regression",
"generation_kwargs":[
"generation_kwargs": [
{ "n_samples": 400000, "n_features": 4, "noise": 1.0 },
{ "n_samples": 200000, "n_features": 8, "noise": 1.5 },
{ "n_samples": 100000, "n_features": 16, "noise": 2.0 }
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25 changes: 4 additions & 21 deletions configs/regular/lightgbm.json
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@@ -1,32 +1,15 @@
{
"INCLUDE": [
"../common/lightgbm.json",
"xgboost_binary.json",
"xgboost_multi.json",
"xgboost_regression.json"
],
"INCLUDE": ["../common/lightgbm.json", "xgboost_binary.json", "xgboost_multi.json", "xgboost_regression.json"],
"PARAMETERS_SETS": {},
"TEMPLATES": {
"lightgbm binary classification": {
"SETS": [
"lightgbm binary classification",
"lightgbm implementations",
"gbt binary classification data"
]
"SETS": ["lightgbm binary classification", "lightgbm implementations", "gbt binary classification data"]
},
"lightgbm multi classification": {
"SETS": [
"lightgbm multi classification",
"lightgbm implementations",
"gbt multi classification data"
]
"SETS": ["lightgbm multi classification", "lightgbm implementations", "gbt multi classification data"]
},
"lightgbm regression": {
"SETS": [
"lightgbm regression",
"lightgbm implementations",
"gbt regression data"
]
"SETS": ["lightgbm regression", "lightgbm implementations", "gbt regression data"]
}
}
}
58 changes: 18 additions & 40 deletions configs/regular/linear_model.json
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Expand Up @@ -8,16 +8,22 @@
"split_kwargs": { "train_size": 0.2, "test_size": 0.8 },
"generation_kwargs": [
{
"n_samples": 5000000, "n_features": 50,
"n_informative": 5, "noise": 20.0
"n_samples": 5000000,
"n_features": 50,
"n_informative": 5,
"noise": 20.0
},
{
"n_samples": 500000, "n_features": 400,
"n_informative": 5, "noise": 40.0
"n_samples": 500000,
"n_features": 400,
"n_informative": 5,
"noise": 40.0
},
{
"n_samples": 100000, "n_features": 2000,
"n_informative": 5, "noise": 60.0
"n_samples": 100000,
"n_features": 2000,
"n_informative": 5,
"noise": 60.0
}
]
}
Expand Down Expand Up @@ -55,50 +61,22 @@
]
},
"sklearn lasso": {
"SETS": [
"sklearn-ex[cpu] implementations",
"common lasso parameters",
"regression datasets"
]
"SETS": ["sklearn-ex[cpu] implementations", "common lasso parameters", "regression datasets"]
},
"sklearn elasticnet": {
"SETS": [
"sklearn-ex[cpu] implementations",
"common elasticnet parameters",
"regression datasets"
]
"SETS": ["sklearn-ex[cpu] implementations", "common elasticnet parameters", "regression datasets"]
},
"cuml linear": {
"SETS": [
"cuml implementation",
"common linear parameters",
"cuml L2 parameters",
"regression datasets"
]
"SETS": ["cuml implementation", "common linear parameters", "cuml L2 parameters", "regression datasets"]
},
"cuml ridge": {
"SETS": [
"cuml implementation",
"common ridge parameters",
"cuml L2 parameters",
"regression datasets"
]
"SETS": ["cuml implementation", "common ridge parameters", "cuml L2 parameters", "regression datasets"]
},
"cuml lasso": {
"SETS": [
"cuml implementation",
"common lasso parameters",
"cuml L1 parameters",
"regression datasets"
]
"SETS": ["cuml implementation", "common lasso parameters", "cuml L1 parameters", "regression datasets"]
},
"cuml elasticnet": {
"SETS": [
"cuml implementation",
"common elasticnet parameters",
"cuml L1 parameters",
"regression datasets"
]
"SETS": ["cuml implementation", "common elasticnet parameters", "cuml L1 parameters", "regression datasets"]
}
}
}
19 changes: 7 additions & 12 deletions configs/regular/logreg.json
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Expand Up @@ -45,41 +45,41 @@
"test_size": 0.95
}
},
"algorithm": {"estimator_params": {"C": 1e-6}}
"algorithm": { "estimator_params": { "C": 1e-6 } }
},
{
"data": { "dataset": "mnist", "split_kwargs": { "train_size": 10000, "test_size": null } },
"algorithm": {"estimator_params": {"C": 1e-8}}
"algorithm": { "estimator_params": { "C": 1e-8 } }
},
{
"data": {
"dataset": "susy",
"split_kwargs": { "train_size": 0.1, "test_size": null }
},
"algorithm": { "estimator_params": {"C": 1e-2} }
"algorithm": { "estimator_params": { "C": 1e-2 } }
},
{
"data": {
"dataset": "hepmass",
"split_kwargs": { "train_size": 0.1, "test_size": null }
},
"algorithm": { "estimator_params": {"C": 1e-5} }
"algorithm": { "estimator_params": { "C": 1e-5 } }
},
{
"data": {
"dataset": "cifar",
"split_kwargs": { "train_size": 0.1, "test_size": null },
"preprocessing_kwargs": { "normalize": "mean" }
},
"algorithm": { "estimator_params": {"C": 1e-9} }
"algorithm": { "estimator_params": { "C": 1e-9 } }
},
{
"data": {
"dataset": "gisette",
"split_kwargs": { "train_size": 2000, "test_size": null },
"preprocessing_kwargs": { "normalize": "standard" }
},
"algorithm": { "estimator_params": {"C": 1e1} }
"algorithm": { "estimator_params": { "C": 1e1 } }
}
]
},
Expand All @@ -93,12 +93,7 @@
]
},
"cuml logreg": {
"SETS": [
"cuml implementation",
"common logreg parameters",
"cuml logreg parameters",
"logreg datasets"
]
"SETS": ["cuml implementation", "common logreg parameters", "cuml logreg parameters", "logreg datasets"]
}
}
}
13 changes: 2 additions & 11 deletions configs/regular/pca.json
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Expand Up @@ -28,19 +28,10 @@
},
"TEMPLATES": {
"sklearn pca": {
"SETS": [
"sklearn-ex[cpu,gpu] implementations",
"pca parameters",
"pca datasets"
]
"SETS": ["sklearn-ex[cpu,gpu] implementations", "pca parameters", "pca datasets"]
},
"cuml pca": {
"SETS": [
"cuml implementation",
"pca parameters",
"cuml pca parameters",
"pca datasets"
]
"SETS": ["cuml implementation", "pca parameters", "cuml pca parameters", "pca datasets"]
}
}
}
20 changes: 5 additions & 15 deletions configs/regular/svm.json
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Expand Up @@ -3,7 +3,7 @@
"PARAMETERS_SETS": {
"svc binary datasets": [
{
"data": { "dataset": "a9a", "split_kwargs": { "train_size": 5000, "test_size": null } },
"data": { "dataset": "a9a", "split_kwargs": { "train_size": 5000, "test_size": null } },
"algorithm": { "estimator_params": { "C": 1.0, "kernel": "linear" } }
},
{
Expand Down Expand Up @@ -63,7 +63,7 @@
],
"nusvc datasets": [
{
"data": { "dataset": "a9a", "split_kwargs": { "train_size": 5000, "test_size": null } },
"data": { "dataset": "a9a", "split_kwargs": { "train_size": 5000, "test_size": null } },
"algorithm": { "estimator_params": { "nu": 0.1, "kernel": ["poly", "rbf"] } }
},
{
Expand Down Expand Up @@ -121,17 +121,12 @@
"multi svc implementations",
"common svm parameters",
"svm clsf parameters",
"svc parameters",
"svc parameters",
"svc multiclass datasets"
]
},
"svr": {
"SETS": [
"svr implementations",
"common svm parameters",
"svr parameters",
"svr datasets"
]
"SETS": ["svr implementations", "common svm parameters", "svr parameters", "svr datasets"]
},
"nusvc": {
"SETS": [
Expand All @@ -143,12 +138,7 @@
]
},
"nusvr": {
"SETS": [
"nusvm implementations",
"common svm parameters",
"nusvr parameters",
"nusvr datasets"
]
"SETS": ["nusvm implementations", "common svm parameters", "nusvr parameters", "nusvr datasets"]
}
}
}
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