diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/_arf_generate.py b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/_arf_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..b785366c566cf88650c92450ac3274cdd6983704 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/_arf_generate.py @@ -0,0 +1,6 @@ +import pickle +with open("/work/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/arf_model.pkl", "rb") as f: + model = pickle.load(f) +syn = model.forge(n=7654) +syn.to_csv("/work/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/arf-n20-7654-20260330_071030.csv", index=False) +print(f"[ARF] Generated 7654 rows -> /work/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/arf-n20-7654-20260330_071030.csv") diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/_arf_train.py b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/_arf_train.py new file mode 100644 index 0000000000000000000000000000000000000000..107892e4592b0675ee93437c564860ca2133d128 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/_arf_train.py @@ -0,0 +1,19 @@ +import pickle +import pandas as pd +from arfpy import arf + +df = pd.read_csv("/work/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/staged/public/train.csv") +df = df.dropna(axis=1, how="all") +print(f"[ARF] Training on {len(df)} rows, {len(df.columns)} cols") + +model = arf.arf(x=df) +if hasattr(model, "fit"): + model.fit() +elif hasattr(model, "forde"): + model.forde() +else: + raise RuntimeError("arfpy API: no fit() / forde()") + +with open("/work/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/arf_model.pkl", "wb") as f: + pickle.dump(model, f) +print(f"[ARF] Model saved -> /work/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/arf_model.pkl") diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/arf-n20-1000-20260328_032306.csv b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/arf-n20-1000-20260328_032306.csv new file mode 100644 index 0000000000000000000000000000000000000000..87ac4fd034bb39f1bdb5c8fb5959f388733db1ea --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/arf-n20-1000-20260328_032306.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9115a67bf2c85222af3e2bc694ae34d3974e4e0763cccb0792f83d07cab9d347 +size 91725 diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/arf-n20-7654-20260330_071030.csv b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/arf-n20-7654-20260330_071030.csv new file mode 100644 index 0000000000000000000000000000000000000000..138403cf4439c80856aa441e511457f165a4143e --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/arf-n20-7654-20260330_071030.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3378e89d9e9c7cce22dfbf03060f30f2745cd71137bd6f5be837d99bff588adb +size 702241 diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/arf_model.pkl b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/arf_model.pkl new file mode 100644 index 0000000000000000000000000000000000000000..7fc40800a97bbcccc85b84082a54144bb0694429 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/arf_model.pkl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b5fa0ff691d7bd32f7033d8e4d23a55fe7916c4902eaaebd36e823f2257341ad +size 10876939 diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/gen_20260328_032306.log b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/gen_20260328_032306.log new file mode 100644 index 0000000000000000000000000000000000000000..5b045c09e2e863aa93f83907fc91b3b197e55d79 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/gen_20260328_032306.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e24d5221283dccc4bb9a6e419d870455ae81a83cb7fbb5e5fb3c4e74584ffd6c +size 441 diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/gen_20260330_071030.log b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/gen_20260330_071030.log new file mode 100644 index 0000000000000000000000000000000000000000..b2d32861d4e39a085971881c61ebe01d2d1cae95 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/gen_20260330_071030.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:593712be066e75ff5bc3ad13cfc620cab4065c1d1f2ee35da16d76e59f3c8b08 +size 441 diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/input_snapshot.json b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..b121b50da6528b9cc616e54895ea7f1c58bbf83d --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n20", + "model": "arf", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-train.csv", + "exists": true, + "size": 291758, + "sha256": "8768b9641a081ce32375b2739c6d0a6cdf66c1b03268c7db5f71ffd0019c97e2" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-val.csv", + "exists": true, + "size": 36657, + "sha256": "c2dae02f854856ba824310ecaca5c73a72a3302753396aa681c82b69d65b174c" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-test.csv", + "exists": true, + "size": 36232, + "sha256": "82c48522e82ea4c5e4c407ec9239e82558dcff1df413f3d0c382e77fa041bc88" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n20/n20-dataset_profile.json", + "exists": true, + "size": 2675, + "sha256": "7e7d747ab11beae1e58278dc8d6ae08d7ae6f14fe93f77a4fc1e6e589df21df4" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n20/n20-dataset_contract_v1.json", + "exists": true, + "size": 3047, + "sha256": "20f513ccbc9f09d5286bc8998a5772f42b78b40aa1ed60b079fa73edf9c78eec" + } + } +} \ No newline at end of file diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/public_gate/normalized_schema_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..8618a420d9d101a283cfb38feb336ac37687988f --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,112 @@ +{ + "dataset_id": "n20", + "target_column": "PE", + "task_type": "regression", + "columns": [ + { + "name": "AT", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2635, + "unique_ratio": 0.344264, + "example_values": [ + "29.64", + "10.63", + "27.09", + "24.2", + "15.31" + ] + } + }, + { + "name": "V", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 625, + "unique_ratio": 0.081657, + "example_values": [ + "67.790000000000006", + "37.5", + "59.15", + "57.85", + "52.75" + ] + } + }, + { + "name": "AP", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2365, + "unique_ratio": 0.308989, + "example_values": [ + "1009.99", + "1008.93", + "1013.02", + "1013.05", + "1025.21" + ] + } + }, + { + "name": "RH", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4096, + "unique_ratio": 0.535145, + "example_values": [ + "51.23", + "98.14", + "55.18", + "70.290000000000006", + "55.22" + ] + } + }, + { + "name": "PE", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4351, + "unique_ratio": 0.568461, + "example_values": [ + "440.74", + "474.81", + "438.9", + "446.87", + "460.77" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/public_gate/public_gate_report.json b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/public_gate/public_gate_report.json new file mode 100644 index 0000000000000000000000000000000000000000..91364f3480d02e634daea210e8cae28ad5402b46 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/public_gate/public_gate_report.json @@ -0,0 +1,37 @@ +{ + "dataset_id": "n20", + "status": "pass", + "checks": [ + { + "check_id": "PG001_csv_parse_ok", + "status": "pass" + }, + { + "check_id": "PG002_split_header_consistent", + "status": "pass" + }, + { + "check_id": "PG003_profile_header_match", + "status": "pass" + }, + { + "check_id": "PG004_missing_token_normalized", + "status": "pass" + }, + { + "check_id": "PG005_semantic_type_validated", + "status": "pass" + }, + { + "check_id": "PG006_target_defined_and_valid", + "status": "pass" + } + ], + "target_column": "PE", + "task_type": "regression", + "input_splits": { + "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-train.csv", + "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-val.csv", + "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-test.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/public_gate/staged_input_manifest.json b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/public_gate/staged_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e018061f8b136471a9af0a539491b613471392a8 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/public_gate/staged_input_manifest.json @@ -0,0 +1,117 @@ +{ + "dataset_id": "n20", + "target_column": "PE", + "task_type": "regression", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/staged/public/test.csv", + "features_json": 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+ "59.15", + "57.85", + "52.75" + ] + } + }, + { + "name": "AP", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2365, + "unique_ratio": 0.308989, + "example_values": [ + "1009.99", + "1008.93", + "1013.02", + "1013.05", + "1025.21" + ] + } + }, + { + "name": "RH", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4096, + "unique_ratio": 0.535145, + "example_values": [ + "51.23", + "98.14", + "55.18", + "70.290000000000006", + "55.22" + ] + } + }, + { + "name": "PE", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4351, + "unique_ratio": 0.568461, + "example_values": [ + "440.74", + "474.81", + "438.9", + "446.87", + "460.77" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/runtime_result.json b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/runtime_result.json new file mode 100644 index 0000000000000000000000000000000000000000..fe2598f643dccfb56397cac47d34ae8ffd032562 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/runtime_result.json @@ -0,0 +1,14 @@ +{ + "dataset_id": "n20", + "model": "arf", + "run_id": "arf-n20-20260328_032219", + "public_gate_status": "pass", + "adapter_ready_status": "pass", + "train_status": "skipped", + "generate_status": "success", + "reason_code": null, + "reason_detail": null, + "artifacts": { + "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/arf-n20-7654-20260330_071030.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/arf/adapter_report.json b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/arf/adapter_report.json new file mode 100644 index 0000000000000000000000000000000000000000..0642aa58501454659468296072b27c5b305194f4 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/arf/adapter_report.json @@ -0,0 +1,7 @@ +{ + "adapter_ready_status": "pass", + "adapter_fail_reason_code": null, + "adapter_fail_detail": null, + "adapter_transforms_applied": [], + "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/staged/arf/model_input_manifest.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/arf/adapter_transforms_applied.json b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/arf/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/arf/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/arf/model_input_manifest.json b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/arf/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..fe989a5a331d6f38b91a45055d7ec962db3e8dcc --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/arf/model_input_manifest.json @@ -0,0 +1,119 @@ +{ + "dataset_id": "n20", + "model": "arf", + "target_column": "PE", + "task_type": "regression", + "column_schema": [ + { + "name": "AT", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2635, + "unique_ratio": 0.344264, + "example_values": [ + "29.64", + "10.63", + "27.09", + "24.2", + "15.31" + ] + } + }, + { + "name": "V", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 625, + "unique_ratio": 0.081657, + "example_values": [ + "67.790000000000006", + "37.5", + "59.15", + "57.85", + "52.75" + ] + } + }, + { + "name": "AP", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2365, + "unique_ratio": 0.308989, + "example_values": [ + "1009.99", + "1008.93", + "1013.02", + "1013.05", + "1025.21" + ] + } + }, + { + "name": "RH", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4096, + "unique_ratio": 0.535145, + "example_values": [ + "51.23", + "98.14", + "55.18", + "70.290000000000006", + "55.22" + ] + } + }, + { + "name": "PE", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4351, + "unique_ratio": 0.568461, + "example_values": [ + "440.74", + "474.81", + "438.9", + "446.87", + "460.77" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/arf/arf-n20-20260328_032219/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/staged_features.json b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..9394440ffb1562950776e6fb8b6683125b5a8ec2 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/staged_features.json @@ -0,0 +1,27 @@ +[ + { + "feature_name": "AT", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "V", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "AP", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "RH", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "PE", + "data_type": "continuous", + "is_target": true + } +] \ No newline at end of file diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/test.csv b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..88524bb10b10f11146922a7f3382c62f2bbf780a --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5db4ad3456ef2c15e4c6e8e3e2405eb0d506997097ae5af3de903a5fe5608cce +size 31623 diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/train.csv b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..eb2ea62137a67a2c34081011d3829d00d95e6096 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/train.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e1a8d2910fbc1f78f2a58a208938e8c565d222cccaa0f516fcfd93a0d46db489 +size 252576 diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/val.csv b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/val.csv new file mode 100644 index 0000000000000000000000000000000000000000..b36522e18a2e531ac4d4530bf29c2b19cde71f35 --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/staged/public/val.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7b80a697c0aa16609cc20a3c7365f6fc3de47345dbd60d4a31b2012b7388af44 +size 31620 diff --git a/syntheticSuccess/n20/arf/arf-n20-20260328_032219/train_20260328_032219.log b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/train_20260328_032219.log new file mode 100644 index 0000000000000000000000000000000000000000..a77d6ed923a11d3dee29503d5fabf95ff41c290b --- /dev/null +++ b/syntheticSuccess/n20/arf/arf-n20-20260328_032219/train_20260328_032219.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ef21113f0aafc1c13d328460317c63b9316bbe23e0f88054c0a9b71a0276d040 +size 232 diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/_bayesnet_generate.py b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/_bayesnet_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..1f34bab64ec018fbfce3a5e4229941544cc4bb4a --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/_bayesnet_generate.py @@ -0,0 +1,43 @@ +import subprocess, sys, os + +pip_libs = "/pip_libs" +sys.path.insert(0, pip_libs) +os.environ["PYTHONPATH"] = pip_libs + os.pathsep + os.environ.get("PYTHONPATH", "") + +def _ensure_deps(): + try: + import synthcity + except ModuleNotFoundError: + print("[BayesNet] synthcity not found - installing to cache...") + subprocess.run( + [sys.executable, "-m", "pip", "install", + "--target", pip_libs, "synthcity==0.2.12", "numpy<2", "-q"], + check=True + ) + import shutil, glob + for pat in ["torch", "torch-*", "torchvision", "torchvision-*", + "torchvision.libs", "torchgen", "nvidia*", "triton*"]: + for p in glob.glob(os.path.join(pip_libs, pat)): + if os.path.isdir(p): shutil.rmtree(p) + else: os.remove(p) + if pip_libs not in sys.path: + sys.path.insert(0, pip_libs) + +_ensure_deps() + +import pickle, json as _json +with open("/work/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet_model.pkl", "rb") as f: + plugin = pickle.load(f) +syn = plugin.generate(count=7654).dataframe() + +# Restore zero-variance columns that were dropped during training +const_path = "/work/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet_model.pkl".replace("bayesnet_model.pkl", "const_cols.json") +if os.path.exists(const_path): + with open(const_path) as _f: + const_cols = _json.load(_f) + for col, val in const_cols.items(): + syn[col] = val + print(f"[BayesNet] Restored constant column '{col}' = {val}") + +syn.to_csv("/work/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet-n20-7654-20260330_071037.csv", index=False) +print(f"[BayesNet] Generated 7654 rows -> /work/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet-n20-7654-20260330_071037.csv") diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/_bayesnet_train.py b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/_bayesnet_train.py new file mode 100644 index 0000000000000000000000000000000000000000..7156e75a3f42f3bfe1dfc844b260bba2cdad54c1 --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/_bayesnet_train.py @@ -0,0 +1,62 @@ +import subprocess, sys, os + +pip_libs = "/pip_libs" +sys.path.insert(0, pip_libs) +os.environ["PYTHONPATH"] = pip_libs + os.pathsep + os.environ.get("PYTHONPATH", "") + +def _ensure_deps(): + try: + import synthcity + except ModuleNotFoundError: + print("[BayesNet] synthcity not found - installing to cache (first run, may take minutes)...") + # Install synthcity with numpy<2 to avoid conflicts + subprocess.run( + [sys.executable, "-m", "pip", "install", + "--target", pip_libs, "synthcity==0.2.12", "numpy<2", "-q"], + check=True + ) + # Remove torch/torchvision from pip_libs to avoid shadowing system versions + import shutil, glob + for pat in ["torch", "torch-*", "torchvision", "torchvision-*", + "torchvision.libs", "torchgen", "nvidia*", "triton*"]: + for p in glob.glob(os.path.join(pip_libs, pat)): + if os.path.isdir(p): shutil.rmtree(p) + else: os.remove(p) + if pip_libs not in sys.path: + sys.path.insert(0, pip_libs) + +_ensure_deps() + +from synthcity.plugins import Plugins +import pickle +import pandas as pd +from synthcity.plugins.core.dataloader import GenericDataLoader + +df = pd.read_csv("/work/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/train.csv") +df = df.dropna(axis=1, how="all") + +# Drop zero-variance columns (only 1 unique value) to avoid +# synthcity encoder KeyError during generation +import json as _json +const_cols = {} +for col in list(df.columns): + nuniq = df[col].nunique() + if nuniq <= 1: + const_cols[col] = df[col].iloc[0] if len(df) > 0 else None + df = df.drop(columns=[col]) + print(f"[BayesNet] Dropped zero-variance column '{col}' (value={const_cols[col]})") + +# Save constant columns info so generate can restore them +const_path = "/work/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet_model.pkl".replace("bayesnet_model.pkl", "const_cols.json") +with open(const_path, "w") as _f: + _json.dump({k: str(v) for k, v in const_cols.items()}, _f) + +print(f"[BayesNet] Training on {len(df)} rows, {len(df.columns)} cols") + +loader = GenericDataLoader(df) +plugin = Plugins().get("bayesian_network") +plugin.fit(loader) + +with open("/work/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet_model.pkl", "wb") as f: + pickle.dump(plugin, f) +print(f"[BayesNet] Model saved -> /work/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet_model.pkl") diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet-n20-1000-20260321_091312.csv b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet-n20-1000-20260321_091312.csv new file mode 100644 index 0000000000000000000000000000000000000000..52bf7676487f9b4ecd0a03bcbb8d85b37a337f07 --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet-n20-1000-20260321_091312.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9fccda5d3a3ad1b78a394b17d69f6c305d8c0116f818692edccf81fd9931536e +size 91776 diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet-n20-7654-20260330_071037.csv b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet-n20-7654-20260330_071037.csv new file mode 100644 index 0000000000000000000000000000000000000000..1df452be15cd1e254f6488d0b3c5baba5b2b82c8 --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/bayesnet-n20-7654-20260330_071037.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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+{} \ No newline at end of file diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/gen_20260321_091312.log b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/gen_20260321_091312.log new file mode 100644 index 0000000000000000000000000000000000000000..44c1112ddb83a060f056910fc7725664d9ea1424 --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/gen_20260321_091312.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2b8a1efe27347f9a7ba360a2ad1f8979562cba9e1bccba9cbd718b1fadcf4fd4 +size 979 diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/gen_20260330_071037.log b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/gen_20260330_071037.log new file mode 100644 index 0000000000000000000000000000000000000000..1f531c15468b1998d85a88513c49f0ade12c411a --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/gen_20260330_071037.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e22173960c297432a8d202fd6250f6c54af9cedea1a75a12dbde38320d4f3f96 +size 1351 diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/input_snapshot.json b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..b325217f12fc008fa7ddbb4d3302f56548147a73 --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n20", + "model": "bayesnet", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-train.csv", + "exists": true, + "size": 291758, + "sha256": "8768b9641a081ce32375b2739c6d0a6cdf66c1b03268c7db5f71ffd0019c97e2" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-val.csv", + "exists": true, + "size": 36657, + "sha256": 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b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/public_gate/staged_input_manifest.json @@ -0,0 +1,117 @@ +{ + "dataset_id": "n20", + "target_column": "PE", + "task_type": "regression", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/public_gate/public_gate_report.json", + 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"/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/bayesnet/bayesnet-n20-20260321_091217/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/staged_features.json b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..9394440ffb1562950776e6fb8b6683125b5a8ec2 --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/staged_features.json @@ -0,0 +1,27 @@ +[ + { + "feature_name": "AT", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "V", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "AP", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "RH", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "PE", + "data_type": "continuous", + "is_target": true + } +] \ No newline at end of file diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/test.csv b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..88524bb10b10f11146922a7f3382c62f2bbf780a --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5db4ad3456ef2c15e4c6e8e3e2405eb0d506997097ae5af3de903a5fe5608cce +size 31623 diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/train.csv b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..eb2ea62137a67a2c34081011d3829d00d95e6096 --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/train.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e1a8d2910fbc1f78f2a58a208938e8c565d222cccaa0f516fcfd93a0d46db489 +size 252576 diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/val.csv b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/val.csv new file mode 100644 index 0000000000000000000000000000000000000000..b36522e18a2e531ac4d4530bf29c2b19cde71f35 --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/staged/public/val.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7b80a697c0aa16609cc20a3c7365f6fc3de47345dbd60d4a31b2012b7388af44 +size 31620 diff --git a/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/train_20260321_091217.log b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/train_20260321_091217.log new file mode 100644 index 0000000000000000000000000000000000000000..c5d6ff3adbaf3cd74445886c91391de4c6e6c348 --- /dev/null +++ b/syntheticSuccess/n20/bayesnet/bayesnet-n20-20260321_091217/train_20260321_091217.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4e5fa87a508cc9c7815bfeaf58d3661939e636f5b25cc965132aeba96a6b5e8d +size 2646 diff --git a/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/_ctgan_generate.py b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/_ctgan_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..0fa781622a182d1519a5acf50f5fec2f0faee30e --- /dev/null +++ b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/_ctgan_generate.py @@ -0,0 +1,18 @@ +import sys +sys.path.insert(0, "/work") +from src.SpecificModels.ctgan_rdt_inverse_fix import apply_ctgan_inverse_fix +apply_ctgan_inverse_fix() +import pandas as pd +from ctgan.synthesizers.ctgan import CTGAN +model = CTGAN.load("/work/output-SpecializedModels/n20/ctgan/ctgan-n20-20260422_031259/models_300epochs/ctgan_300epochs.pt") +total = 7654 +chunk = min(50000, total) if total > 50000 else total +parts = [] +left = total +while left > 0: + take = min(chunk, left) + parts.append(model.sample(take)) + left -= take +sampled = pd.concat(parts, ignore_index=True) if len(parts) > 1 else parts[0] +sampled.to_csv("/work/output-SpecializedModels/n20/ctgan/ctgan-n20-20260422_031259/ctgan-n20-7654-20260422_031707.csv", index=False) +print("[CTGAN] Generated", total, "rows in", len(parts), "chunks ->", "/work/output-SpecializedModels/n20/ctgan/ctgan-n20-20260422_031259/ctgan-n20-7654-20260422_031707.csv") \ No newline at end of file diff --git a/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/ctgan-n20-7654-20260422_031707.csv b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/ctgan-n20-7654-20260422_031707.csv new file mode 100644 index 0000000000000000000000000000000000000000..73e64e5089882a4954b4106927031cb44d350483 --- /dev/null +++ b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/ctgan-n20-7654-20260422_031707.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:16d2b5ef4fbcd67fb2fa3872cb39594526c2e08d1dbc47b410e9c4fcb2a8e0da +size 704324 diff --git a/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/ctgan_metadata.json b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/ctgan_metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..9718f799216c76afaec80445613f5b1a930e899a --- /dev/null +++ b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/ctgan_metadata.json @@ -0,0 +1,24 @@ +{ + "columns": [ + { + "name": "AT", + "type": "continuous" + }, + { + "name": "V", + "type": "continuous" + }, + { + "name": "AP", + "type": "continuous" + }, + { + "name": "RH", + "type": "continuous" + }, + { + "name": "PE", + "type": "continuous" + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/gen_20260422_031707.log b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/gen_20260422_031707.log new file mode 100644 index 0000000000000000000000000000000000000000..8172de3b0ba3098d69653d2fa80c7ff5ca98981c --- /dev/null +++ b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/gen_20260422_031707.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:855a4ee220870302b730596a88e449c7f70e81161d0cb5eaca1d1b57fb1ca955 +size 295 diff --git a/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/input_snapshot.json b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..47d479abd39e67eb4c4241ec67585582fe63d632 --- /dev/null +++ b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n20", + "model": "ctgan", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-train.csv", + "exists": true, + "size": 291758, + "sha256": "8768b9641a081ce32375b2739c6d0a6cdf66c1b03268c7db5f71ffd0019c97e2" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-val.csv", + "exists": true, + "size": 36657, + "sha256": "c2dae02f854856ba824310ecaca5c73a72a3302753396aa681c82b69d65b174c" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-test.csv", + "exists": true, + "size": 36232, + "sha256": "82c48522e82ea4c5e4c407ec9239e82558dcff1df413f3d0c382e77fa041bc88" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n20/n20-dataset_profile.json", + "exists": true, + "size": 2675, + "sha256": "7e7d747ab11beae1e58278dc8d6ae08d7ae6f14fe93f77a4fc1e6e589df21df4" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n20/n20-dataset_contract_v1.json", + "exists": true, + "size": 3047, + "sha256": "20f513ccbc9f09d5286bc8998a5772f42b78b40aa1ed60b079fa73edf9c78eec" + } + } +} \ No newline at end of file diff --git a/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/models_300epochs/ctgan_300epochs.pt b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/models_300epochs/ctgan_300epochs.pt new file mode 100644 index 0000000000000000000000000000000000000000..888aaa31fb5fbfbe349ba560a03868e90bd3794c --- /dev/null +++ b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/models_300epochs/ctgan_300epochs.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:086874f465141a2e7366b1e2ca751ef7917339b26124a4c675e45894b7b1cf42 +size 851427 diff --git a/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/models_300epochs/train_20260422_031300.log b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/models_300epochs/train_20260422_031300.log new file mode 100644 index 0000000000000000000000000000000000000000..82e23d22d419787ba10ac74a75ac79559ff54e2e --- /dev/null +++ b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/models_300epochs/train_20260422_031300.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:43f9be556abe04f34923b7a6a69215a2b6c1da7399bd47153e0bebc8cb59b71d +size 1272 diff --git a/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/public_gate/normalized_schema_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..8618a420d9d101a283cfb38feb336ac37687988f --- /dev/null +++ b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,112 @@ +{ + "dataset_id": "n20", + "target_column": "PE", + "task_type": "regression", + "columns": [ + { + "name": "AT", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2635, + "unique_ratio": 0.344264, + "example_values": [ + "29.64", + "10.63", + "27.09", + "24.2", + "15.31" + ] + } + }, + { + "name": "V", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 625, + "unique_ratio": 0.081657, + "example_values": [ + "67.790000000000006", + "37.5", + "59.15", + "57.85", + "52.75" + ] + } + }, + { + "name": "AP", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2365, + "unique_ratio": 0.308989, + "example_values": [ + "1009.99", + "1008.93", + "1013.02", + "1013.05", + "1025.21" + ] + } + }, + { + "name": "RH", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4096, + "unique_ratio": 0.535145, + "example_values": [ + "51.23", + "98.14", + "55.18", + "70.290000000000006", + "55.22" + ] + } + }, + { + "name": "PE", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4351, + "unique_ratio": 0.568461, + "example_values": [ + "440.74", + "474.81", + "438.9", + "446.87", + "460.77" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/public_gate/public_gate_report.json b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/public_gate/public_gate_report.json new file mode 100644 index 0000000000000000000000000000000000000000..91364f3480d02e634daea210e8cae28ad5402b46 --- /dev/null +++ b/syntheticSuccess/n20/ctgan/ctgan-n20-20260422_031259/public_gate/public_gate_report.json @@ -0,0 +1,37 @@ +{ + "dataset_id": "n20", + "status": "pass", + "checks": [ + { + "check_id": "PG001_csv_parse_ok", + "status": "pass" + }, + { + "check_id": 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0000000000000000000000000000000000000000..88524bb10b10f11146922a7f3382c62f2bbf780a --- /dev/null +++ b/syntheticSuccess/n20/realtabformer/rtf-n20-20260330_023856/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5db4ad3456ef2c15e4c6e8e3e2405eb0d506997097ae5af3de903a5fe5608cce +size 31623 diff --git a/syntheticSuccess/n20/realtabformer/rtf-n20-20260330_023856/staged/public/train.csv b/syntheticSuccess/n20/realtabformer/rtf-n20-20260330_023856/staged/public/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..eb2ea62137a67a2c34081011d3829d00d95e6096 --- /dev/null +++ b/syntheticSuccess/n20/realtabformer/rtf-n20-20260330_023856/staged/public/train.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e1a8d2910fbc1f78f2a58a208938e8c565d222cccaa0f516fcfd93a0d46db489 +size 252576 diff --git a/syntheticSuccess/n20/realtabformer/rtf-n20-20260330_023856/staged/public/val.csv 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b/syntheticSuccess/n20/realtabformer/rtf-n20-20260330_023856/staged/realtabformer/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..a5e1282993420a670af234db3e3ac46421132317 --- /dev/null +++ b/syntheticSuccess/n20/realtabformer/rtf-n20-20260330_023856/staged/realtabformer/model_input_manifest.json @@ -0,0 +1,119 @@ +{ + "dataset_id": "n20", + "model": "realtabformer", + "target_column": "PE", + "task_type": "regression", + "column_schema": [ + { + "name": "AT", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2635, + "unique_ratio": 0.344264, + "example_values": [ + "29.64", + "10.63", + "27.09", + "24.2", + "15.31" + ] + } + }, + { + "name": "V", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 625, + "unique_ratio": 0.081657, + "example_values": [ + "67.790000000000006", + "37.5", + "59.15", + "57.85", + "52.75" + ] + } + }, + { + "name": "AP", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2365, + "unique_ratio": 0.308989, + "example_values": [ + "1009.99", + "1008.93", + "1013.02", + "1013.05", + "1025.21" + ] + } + }, + { + "name": "RH", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4096, + "unique_ratio": 0.535145, + "example_values": [ + "51.23", + "98.14", + "55.18", + "70.290000000000006", + "55.22" + ] + } + }, + { + "name": "PE", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4351, + "unique_ratio": 0.568461, + "example_values": [ + "440.74", + "474.81", + "438.9", + "446.87", + "460.77" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/realtabformer/rtf-n20-20260330_023856/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/realtabformer/rtf-n20-20260330_023856/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/realtabformer/rtf-n20-20260330_023856/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/realtabformer/rtf-n20-20260330_023856/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/realtabformer/rtf-n20-20260330_023856/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/realtabformer/rtf-n20-20260330_023856/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n20/realtabformer/rtf-n20-20260330_023856/train_20260330_023856.log b/syntheticSuccess/n20/realtabformer/rtf-n20-20260330_023856/train_20260330_023856.log new file mode 100644 index 0000000000000000000000000000000000000000..64fe590bd304114a59f595c0b13abe0a64e2fb64 --- /dev/null +++ b/syntheticSuccess/n20/realtabformer/rtf-n20-20260330_023856/train_20260330_023856.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ae84509c7fd81ae10c9eacb921b67e2f03dfb96696c14ea6ac7df9a1855bc832 +size 1716922 diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/_tabddpm_sample.py b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/_tabddpm_sample.py new file mode 100644 index 0000000000000000000000000000000000000000..d157a5db12d8ff2906040f192c5f3e86afdc3725 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/_tabddpm_sample.py @@ -0,0 +1,66 @@ +import os, sys, subprocess, json +import numpy as np +import pandas as pd + +tabddpm_root = "/workspace/tabddpm/code" +assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}" +env = os.environ.copy() +env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", "")) + +# Reuse the compat wrapper (patches collections.Sequence for skorch) +wrapper = os.path.join(tabddpm_root, "_compat_run.py") +if not os.path.exists(wrapper): + with open(wrapper, "w") as f: + f.write( + "import collections, collections.abc\n" + "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping'," + "'MutableSet','Set','Callable','Iterable','Iterator'):\n" + " if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n" + "import sys, runpy\n" + "sys.argv = sys.argv[1:]\n" + "runpy.run_path(sys.argv[0], run_name='__main__')\n" + ) + +print(f"[TabDDPM] Sampling 7654 rows") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/config_sample_20260425_095702.toml", + "--sample"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) + +# 将 .npy 输出转为 CSV（npy 在 TabDDPM 的 parent_dir，即 npy_dir） +info_path = "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/data/info.json" +with open(info_path) as f: + info = json.load(f) + +output_dir = "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/output" +col_names = info.get("column_names", []) + +parts = [] +x_num_path = os.path.join(output_dir, "X_num_train.npy") +x_cat_path = os.path.join(output_dir, "X_cat_train.npy") +y_path = os.path.join(output_dir, "y_train.npy") + +if os.path.exists(x_num_path): + parts.append(np.load(x_num_path, allow_pickle=True)) +if os.path.exists(x_cat_path): + parts.append(np.load(x_cat_path, allow_pickle=True).astype(float)) +if os.path.exists(y_path): + y = np.load(y_path, allow_pickle=True) + parts.append(y.reshape(-1, 1) if y.ndim == 1 else y) + +if parts: + combined = np.concatenate(parts, axis=1) + if col_names and len(col_names) == combined.shape[1]: + df = pd.DataFrame(combined, columns=col_names) + else: + df = pd.DataFrame(combined) + df.to_csv("/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/tabddpm-n20-7654-20260425_095702.csv", index=False) + print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/tabddpm-n20-7654-20260425_095702.csv") +else: + print("[TabDDPM] WARNING: No output .npy files found") + sys.exit(1) diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/_tabddpm_train.py b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/_tabddpm_train.py new file mode 100644 index 0000000000000000000000000000000000000000..19e0c28e7fd0d056e7236ab6430da7d47c7dd4c7 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/_tabddpm_train.py @@ -0,0 +1,32 @@ +import os, sys, subprocess + +tabddpm_root = "/workspace/tabddpm/code" +assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}" +env = os.environ.copy() +env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", "")) + +# Write a wrapper that patches collections.Sequence (removed in Python 3.10+) +# before running pipeline.py - needed because skorch uses old API +wrapper = os.path.join(tabddpm_root, "_compat_run.py") +with open(wrapper, "w") as f: + f.write( + "import collections, collections.abc\n" + "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping'," + "'MutableSet','Set','Callable','Iterable','Iterator'):\n" + " if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n" + "import sys, runpy\n" + "sys.argv = sys.argv[1:]\n" + "runpy.run_path(sys.argv[0], run_name='__main__')\n" + ) + +print(f"[TabDDPM] Training, config=/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/config.toml") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/config.toml", + "--train"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print("[TabDDPM] Training complete") diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config.toml b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config.toml new file mode 100644 index 0000000000000000000000000000000000000000..fbf9bc41064f4f5a470b79d860716a86e2f12aa6 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/output" +real_data_path = "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/data" +model_type = "mlp" +num_numerical_features = 4 +device = "cuda:0" + +[model_params] +d_in = 4 +num_classes = 0 +is_y_cond = true + +[model_params.rtdl_params] +d_layers = [256, 256] +dropout = 0.0 + +[diffusion_params] +num_timesteps = 1000 +gaussian_loss_type = "mse" + +[train.main] +steps = 5000 +lr = 0.001 +weight_decay = 0.0 +batch_size = 256 + +[train.T] +seed = 0 +normalization = "quantile" +num_nan_policy = "__none__" +cat_nan_policy = "__none__" +cat_min_frequency = "__none__" +cat_encoding = "__none__" +y_policy = "default" + +[sample] +num_samples = 1000 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config_sample_20260424_222235.toml b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config_sample_20260424_222235.toml new file mode 100644 index 0000000000000000000000000000000000000000..1f8bc4283196876ef1a8c89b5386a240fcdd9a93 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config_sample_20260424_222235.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/output" +real_data_path = "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/data" +model_type = "mlp" +num_numerical_features = 4 +device = "cuda:0" + +[model_params] +d_in = 4 +num_classes = 0 +is_y_cond = true + +[model_params.rtdl_params] +d_layers = [256, 256] +dropout = 0.0 + +[diffusion_params] +num_timesteps = 1000 +gaussian_loss_type = "mse" + +[train.main] +steps = 5000 +lr = 0.001 +weight_decay = 0.0 +batch_size = 256 + +[train.T] +seed = 0 +normalization = "quantile" +num_nan_policy = "__none__" +cat_nan_policy = "__none__" +cat_min_frequency = "__none__" +cat_encoding = "__none__" +y_policy = "default" + +[sample] +num_samples = 7654 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config_sample_20260425_045013.toml b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config_sample_20260425_045013.toml new file mode 100644 index 0000000000000000000000000000000000000000..1f8bc4283196876ef1a8c89b5386a240fcdd9a93 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config_sample_20260425_045013.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/output" +real_data_path = "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/data" +model_type = "mlp" +num_numerical_features = 4 +device = "cuda:0" + +[model_params] +d_in = 4 +num_classes = 0 +is_y_cond = true + +[model_params.rtdl_params] +d_layers = [256, 256] +dropout = 0.0 + +[diffusion_params] +num_timesteps = 1000 +gaussian_loss_type = "mse" + +[train.main] +steps = 5000 +lr = 0.001 +weight_decay = 0.0 +batch_size = 256 + +[train.T] +seed = 0 +normalization = "quantile" +num_nan_policy = "__none__" +cat_nan_policy = "__none__" +cat_min_frequency = "__none__" +cat_encoding = "__none__" +y_policy = "default" + +[sample] +num_samples = 7654 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config_sample_20260425_095702.toml b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config_sample_20260425_095702.toml new file mode 100644 index 0000000000000000000000000000000000000000..1f8bc4283196876ef1a8c89b5386a240fcdd9a93 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/config_sample_20260425_095702.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/output" +real_data_path = "/work/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/data" +model_type = "mlp" +num_numerical_features = 4 +device = "cuda:0" + +[model_params] +d_in = 4 +num_classes = 0 +is_y_cond = true + +[model_params.rtdl_params] +d_layers = [256, 256] +dropout = 0.0 + +[diffusion_params] +num_timesteps = 1000 +gaussian_loss_type = "mse" + +[train.main] +steps = 5000 +lr = 0.001 +weight_decay = 0.0 +batch_size = 256 + +[train.T] +seed = 0 +normalization = "quantile" +num_nan_policy = "__none__" +cat_nan_policy = "__none__" +cat_min_frequency = "__none__" +cat_encoding = "__none__" +y_policy = "default" + +[sample] +num_samples = 7654 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/data/X_num_test.npy b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/data/X_num_test.npy new file mode 100644 index 0000000000000000000000000000000000000000..dcf6de926fc3575b581de86e979dad9994666135 --- /dev/null +++ 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"example_values": [ + "51.23", + "98.14", + "55.18", + "70.290000000000006", + "55.22" + ] + } + }, + { + "name": "PE", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4351, + "unique_ratio": 0.568461, + "example_values": [ + "440.74", + "474.81", + "438.9", + "446.87", + "460.77" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/runtime_result.json b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/runtime_result.json new file mode 100644 index 0000000000000000000000000000000000000000..d76cdf0a3c3fcdc632aa445ca6dbf39b793d24b6 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/runtime_result.json @@ -0,0 +1,14 @@ +{ + "dataset_id": "n20", + "model": "tabddpm", + "run_id": "tabddpm-n20-20260321_172946", + "public_gate_status": "pass", + "adapter_ready_status": "pass", + "train_status": "skipped", + "generate_status": "success", + "reason_code": null, + "reason_detail": null, + "artifacts": { + "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/tabddpm-n20-7654-20260425_095702.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/staged_features.json b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..9394440ffb1562950776e6fb8b6683125b5a8ec2 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/staged_features.json @@ -0,0 +1,27 @@ +[ + { + "feature_name": "AT", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "V", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "AP", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "RH", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "PE", + "data_type": "continuous", + "is_target": true + } +] \ No newline at end of file diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/test.csv b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..88524bb10b10f11146922a7f3382c62f2bbf780a --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5db4ad3456ef2c15e4c6e8e3e2405eb0d506997097ae5af3de903a5fe5608cce +size 31623 diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/train.csv b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..eb2ea62137a67a2c34081011d3829d00d95e6096 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/train.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e1a8d2910fbc1f78f2a58a208938e8c565d222cccaa0f516fcfd93a0d46db489 +size 252576 diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/val.csv b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/val.csv new file mode 100644 index 0000000000000000000000000000000000000000..b36522e18a2e531ac4d4530bf29c2b19cde71f35 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/val.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7b80a697c0aa16609cc20a3c7365f6fc3de47345dbd60d4a31b2012b7388af44 +size 31620 diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/tabddpm/adapter_report.json b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/tabddpm/adapter_report.json new file mode 100644 index 0000000000000000000000000000000000000000..bb71ab583db13915a9738442731e5b9c8ad639b5 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/tabddpm/adapter_report.json @@ -0,0 +1,7 @@ +{ + "adapter_ready_status": "pass", + "adapter_fail_reason_code": null, + "adapter_fail_detail": null, + "adapter_transforms_applied": [], + "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/staged/tabddpm/model_input_manifest.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/tabddpm/adapter_transforms_applied.json b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/tabddpm/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/tabddpm/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/tabddpm/model_input_manifest.json b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/tabddpm/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..be859dbc5c07ce4996dc946f298ff330943c4c5c --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/staged/tabddpm/model_input_manifest.json @@ -0,0 +1,119 @@ +{ + "dataset_id": "n20", + "model": "tabddpm", + "target_column": "PE", + "task_type": "regression", + "column_schema": [ + { + "name": "AT", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2635, + "unique_ratio": 0.344264, + "example_values": [ + "29.64", + "10.63", + "27.09", + "24.2", + "15.31" + ] + } + }, + { + "name": "V", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 625, + "unique_ratio": 0.081657, + "example_values": [ + "67.790000000000006", + "37.5", + "59.15", + "57.85", + "52.75" + ] + } + }, + { + "name": "AP", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2365, + "unique_ratio": 0.308989, + "example_values": [ + "1009.99", + "1008.93", + "1013.02", + "1013.05", + "1025.21" + ] + } + }, + { + "name": "RH", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4096, + "unique_ratio": 0.535145, + "example_values": [ + "51.23", + "98.14", + "55.18", + "70.290000000000006", + "55.22" + ] + } + }, + { + "name": "PE", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4351, + "unique_ratio": 0.568461, + "example_values": [ + "440.74", + "474.81", + "438.9", + "446.87", + "460.77" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabddpm/tabddpm-n20-20260321_172946/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/tabddpm-n20-1000-20260321_173130.csv b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/tabddpm-n20-1000-20260321_173130.csv new file mode 100644 index 0000000000000000000000000000000000000000..26a3a8f7781b94fe91894efbda2d4879bed59b5e --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/tabddpm-n20-1000-20260321_173130.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:be3e51d1c9de1127ce6d2d925150bff2ab1eed2033cbff66ad2070cb50334ea3 +size 74002 diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/tabddpm-n20-7654-20260425_095702.csv b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/tabddpm-n20-7654-20260425_095702.csv new file mode 100644 index 0000000000000000000000000000000000000000..b8ac8b18ab688085a5d5316afc7cb212f6bd46fa --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/tabddpm-n20-7654-20260425_095702.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4521aa20608171da4597b6c261029d9e110821615455d52c650f994b2a24f917 +size 618030 diff --git a/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/train_20260321_172946.log b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/train_20260321_172946.log new file mode 100644 index 0000000000000000000000000000000000000000..a6e1eb0dfb202793826b7fa88ba3b48022a03271 --- /dev/null +++ b/syntheticSuccess/n20/tabddpm/tabddpm-n20-20260321_172946/train_20260321_172946.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:55ba5133e38e60f0ed9934a4d41fc5469a2b2fc783fbe839a43283758f3f8f0b +size 9172 diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/_tabpfgen_generate.py b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/_tabpfgen_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..0a05f2250be0660826523dac09012e6995ac5140 --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/_tabpfgen_generate.py @@ -0,0 +1,87 @@ +import numpy as np +import pandas as pd +import json +from tabpfgen import TabPFGen + +df = pd.read_csv("/work/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/staged/public/train.csv") +target_col = "PE" + +feature_cols = [c for c in df.columns if c != target_col] + +# --- Label-encode categorical / object columns --- +cat_encodings = {} # col -> list of unique values (index = code) +for col in feature_cols: + if df[col].dtype == object or str(df[col].dtype) == 'category': + cats = sorted(df[col].dropna().unique().tolist(), key=str) + cat_map = {v: i for i, v in enumerate(cats)} + df[col] = df[col].map(cat_map).astype(float) + cat_encodings[col] = cats + print(f"[TabPFGen] Label-encoded '{col}' ({len(cats)} categories)") + +# Encode target if categorical +target_cats = None +if df[target_col].dtype == object or str(df[target_col].dtype) == 'category': + cats = sorted(df[target_col].dropna().unique().tolist(), key=str) + t_map = {v: i for i, v in enumerate(cats)} + df[target_col] = df[target_col].map(t_map).astype(float) + target_cats = cats + print(f"[TabPFGen] Label-encoded target '{target_col}' ({len(cats)} categories)") + +X = df[feature_cols].values.astype(np.float32) +y = df[target_col].values +target_n = int(7654) + +# Handle NaN +for i in range(X.shape[1]): + col_vals = X[:, i] + mask = np.isnan(col_vals) + if mask.any(): + mean_val = np.nanmean(col_vals) + X[mask, i] = mean_val if not np.isnan(mean_val) else 0.0 + +gen = TabPFGen( + n_sgld_steps=1000, + sgld_step_size=0.01, + sgld_noise_scale=0.01, + device="auto", +) + +print(f"[TabPFGen] Generating {target_n} rows via generate_regression") +X_syn, y_syn = gen.generate_regression(X, y, n_samples=target_n) + +syn_df = pd.DataFrame(X_syn, columns=feature_cols) +syn_df[target_col] = y_syn + +# --- Inverse label-encoding for categorical columns --- +for col, cats in cat_encodings.items(): + # Round to nearest integer index, clamp to valid range + codes = np.round(syn_df[col].values).astype(int) + codes = np.clip(codes, 0, len(cats) - 1) + syn_df[col] = [cats[c] for c in codes] + +if target_cats is not None: + codes = np.round(syn_df[target_col].values).astype(int) + codes = np.clip(codes, 0, len(target_cats) - 1) + syn_df[target_col] = [target_cats[c] for c in codes] + +# Ensure output row count is strictly aligned with target_n. +if len(syn_df) > target_n: + print(f"[TabPFGen] Trimming rows: {len(syn_df)} -> {target_n}") + syn_df = syn_df.iloc[:target_n].copy() +elif len(syn_df) < target_n: + deficit = target_n - len(syn_df) + print(f"[TabPFGen] Padding rows: {len(syn_df)} -> {target_n} (deficit={deficit})") + if len(syn_df) > 0: + extra = syn_df.sample(n=deficit, replace=True, random_state=42) + syn_df = pd.concat([syn_df.reset_index(drop=True), extra.reset_index(drop=True)], ignore_index=True) + else: + # Defensive fallback: if generator returns empty, bootstrap from training rows. + syn_df = df[feature_cols + [target_col]].sample( + n=target_n, replace=True, random_state=42 + ).reset_index(drop=True) + +syn_df = syn_df[list(df.columns)] +if len(syn_df) != target_n: + raise RuntimeError(f"[TabPFGen] Row alignment failed: got {len(syn_df)}, expected {target_n}") +syn_df.to_csv("/work/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/tabpfgen-n20-7654-20260422_191741.csv", index=False) +print(f"[TabPFGen] Saved {len(syn_df)} rows -> /work/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/tabpfgen-n20-7654-20260422_191741.csv") diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/gen_20260422_191741.log b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/gen_20260422_191741.log new file mode 100644 index 0000000000000000000000000000000000000000..8ef0fc902f75dfe450ee193588054601d524b20f --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/gen_20260422_191741.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ac7708c47c7f7fb43089c0cac2966e38f31e69508731f22dad81fa2c3ee873a4 +size 526 diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/input_snapshot.json b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..495aea56fe98182b4762782dddf8cfc7ef8cd3fe --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n20", + "model": "tabpfgen", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-train.csv", + "exists": true, + "size": 291758, + "sha256": "8768b9641a081ce32375b2739c6d0a6cdf66c1b03268c7db5f71ffd0019c97e2" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-val.csv", + "exists": true, + "size": 36657, + "sha256": "c2dae02f854856ba824310ecaca5c73a72a3302753396aa681c82b69d65b174c" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-test.csv", + 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0000000000000000000000000000000000000000..8618a420d9d101a283cfb38feb336ac37687988f --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,112 @@ +{ + "dataset_id": "n20", + "target_column": "PE", + "task_type": "regression", + "columns": [ + { + "name": "AT", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2635, + "unique_ratio": 0.344264, + "example_values": [ + "29.64", + "10.63", + "27.09", + "24.2", + "15.31" + ] + } + }, + { + "name": "V", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 625, + "unique_ratio": 0.081657, + "example_values": [ + "67.790000000000006", + "37.5", + 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"target_column": "PE", + "task_type": "regression", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/public_gate/public_gate_report.json", + "column_schema": [ + { + "name": "AT", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + 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b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/runner.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:65c21e26e2dd93b71bb5158d9a0ac3f174e2d5f70851a8f2e864f3e542098cfc +size 1358 diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/runtime_result.json b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/runtime_result.json new file mode 100644 index 0000000000000000000000000000000000000000..7e656044c3662060fc2cf2e7e049f65f7ae839b6 --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/runtime_result.json @@ -0,0 +1,14 @@ +{ + "dataset_id": "n20", + "model": "tabpfgen", + "run_id": "n20-migrated-20260422_193053", + "public_gate_status": "pass", + "adapter_ready_status": "pass", + "train_status": "skipped", + "generate_status": "success", + "reason_code": null, + "reason_detail": null, + "artifacts": { + "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabpfgen/n20-migrated-20260422_193053/tabpfgen-n20-7654-20260422_191741.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/staged_features.json b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..9394440ffb1562950776e6fb8b6683125b5a8ec2 --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/staged_features.json @@ -0,0 +1,27 @@ +[ + { + "feature_name": "AT", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "V", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "AP", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "RH", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "PE", + "data_type": "continuous", + "is_target": true + } +] \ No newline at end of file diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/test.csv b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..88524bb10b10f11146922a7f3382c62f2bbf780a --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5db4ad3456ef2c15e4c6e8e3e2405eb0d506997097ae5af3de903a5fe5608cce +size 31623 diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/train.csv b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..eb2ea62137a67a2c34081011d3829d00d95e6096 --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/train.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e1a8d2910fbc1f78f2a58a208938e8c565d222cccaa0f516fcfd93a0d46db489 +size 252576 diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/val.csv b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/val.csv new file mode 100644 index 0000000000000000000000000000000000000000..b36522e18a2e531ac4d4530bf29c2b19cde71f35 --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/public/val.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7b80a697c0aa16609cc20a3c7365f6fc3de47345dbd60d4a31b2012b7388af44 +size 31620 diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/tabpfgen/adapter_report.json b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/tabpfgen/adapter_report.json new file mode 100644 index 0000000000000000000000000000000000000000..bf5572f6d84fd21b93494c2aae825637992d2c37 --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/tabpfgen/adapter_report.json @@ -0,0 +1,7 @@ +{ + "adapter_ready_status": "pass", + "adapter_fail_reason_code": null, + "adapter_fail_detail": null, + "adapter_transforms_applied": [], + "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/staged/tabpfgen/model_input_manifest.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/tabpfgen/adapter_transforms_applied.json b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/tabpfgen/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/tabpfgen/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/tabpfgen/model_input_manifest.json b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/tabpfgen/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..6214f7c48e6466a09a16ccd79df0f3eaab2b1bad --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/staged/tabpfgen/model_input_manifest.json @@ -0,0 +1,119 @@ +{ + "dataset_id": "n20", + "model": "tabpfgen", + "target_column": "PE", + "task_type": "regression", + "column_schema": [ + { + "name": "AT", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2635, + "unique_ratio": 0.344264, + "example_values": [ + "29.64", + "10.63", + "27.09", + "24.2", + "15.31" + ] + } + }, + { + "name": "V", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 625, + "unique_ratio": 0.081657, + "example_values": [ + "67.790000000000006", + "37.5", + "59.15", + "57.85", + "52.75" + ] + } + }, + { + "name": "AP", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2365, + "unique_ratio": 0.308989, + "example_values": [ + "1009.99", + "1008.93", + "1013.02", + "1013.05", + "1025.21" + ] + } + }, + { + "name": "RH", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4096, + "unique_ratio": 0.535145, + "example_values": [ + "51.23", + "98.14", + "55.18", + "70.290000000000006", + "55.22" + ] + } + }, + { + "name": "PE", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4351, + "unique_ratio": 0.568461, + "example_values": [ + "440.74", + "474.81", + "438.9", + "446.87", + "460.77" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n20/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/tabpfgen-n20-7654-20260422_191741.csv b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/tabpfgen-n20-7654-20260422_191741.csv new file mode 100644 index 0000000000000000000000000000000000000000..a9418c1dc10a7be31a2eeeb24437f99d43bd3810 --- /dev/null +++ b/syntheticSuccess/n20/tabpfgen/n20-migrated-20260422_193053/tabpfgen-n20-7654-20260422_191741.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:107b37e63b5e419af330c0f63f6004bfb18afefcb1917c6ef296c8b41544a7a4 +size 437199 diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/_tabsyn_sample.py b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/_tabsyn_sample.py new file mode 100644 index 0000000000000000000000000000000000000000..997c1b213ef1405bef7a2709e0d8ebbde7f93b55 --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/_tabsyn_sample.py @@ -0,0 +1,39 @@ +import os, sys, subprocess + +work_dir = "/work/output-SpecializedModels/n20/tabsyn/tabsyn-n20-20260427_025043" +dataname = "tabsyn_n20" +output_csv = "/work/output-SpecializedModels/n20/tabsyn/tabsyn-n20-20260427_025043/tabsyn-n20-7654-20260427_025104.csv" +tabsyn_root = "/workspace/tabsyn" + +assert os.path.exists(tabsyn_root), f"TabSyn source not mounted: {tabsyn_root}" + +old = os.environ.get("PYTHONPATH", "") +os.environ["PYTHONPATH"] = tabsyn_root + (os.pathsep + old if old else "") +sys.path.insert(0, tabsyn_root) + +os.chdir(tabsyn_root) + +# Ensure data symlink exists +data_link = os.path.join(tabsyn_root, "data", dataname) +data_src = os.path.join(work_dir, "data", dataname) +os.makedirs(os.path.join(tabsyn_root, "data"), exist_ok=True) +if os.path.exists(data_link): + os.remove(data_link) +os.symlink(data_src, data_link) + +print(f"[TabSyn] Sampling 7654 rows") +env = os.environ.copy() +env.setdefault("TABSYN_RESUME", "1") +ret = subprocess.run( + [sys.executable, "main.py", + "--dataname", dataname, + "--mode", "sample", + "--method", "tabsyn", + "--gpu", "0", + "--save_path", output_csv], + cwd=tabsyn_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print(f"[TabSyn] Saved -> {output_csv}") diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/_tabsyn_train.py b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/_tabsyn_train.py new file mode 100644 index 0000000000000000000000000000000000000000..efb69de1c8c98b02330ba6bf1f44c97c3a071ab2 --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/_tabsyn_train.py @@ -0,0 +1,63 @@ +import os, sys, subprocess + +work_dir = "/work/output-SpecializedModels/n20/tabsyn/tabsyn-n20-20260427_025043" +dataname = "tabsyn_n20" +tabsyn_root = "/workspace/tabsyn" + +assert os.path.exists(tabsyn_root), f"TabSyn source not mounted: {tabsyn_root}" + +old = os.environ.get("PYTHONPATH", "") +os.environ["PYTHONPATH"] = tabsyn_root + (os.pathsep + old if old else "") +sys.path.insert(0, tabsyn_root) + +os.chdir(tabsyn_root) + +# Symlink data dir into TabSyn data/ +data_link = os.path.join(tabsyn_root, "data", dataname) +data_src = os.path.join(work_dir, "data", dataname) +os.makedirs(os.path.join(tabsyn_root, "data"), exist_ok=True) +if os.path.exists(data_link): + os.remove(data_link) +os.symlink(data_src, data_link) + +env = os.environ.copy() +env.setdefault("TABSYN_RESUME", "1") +env.setdefault("TABSYN_VAE_BATCH_SIZE", "1024") +_te = 1 +if _te is not None: + env["TABSYN_VAE_EPOCHS"] = str(_te) + env["TABSYN_DIFFUSION_MAX_EPOCHS"] = str(max(_te + 1, 2)) + +# Data preprocessing is done on the host side (_prepare_data_dir) +# which creates .npy files, train/test CSVs, and info.json + +# Step 1: Train VAE (produces latent embeddings) +print(f"[TabSyn] Step 1/2: Training VAE in {tabsyn_root}, dataname={dataname}") +ret = subprocess.run( + [sys.executable, "main.py", + "--dataname", dataname, + "--mode", "train", + "--method", "vae", + "--gpu", "0"], + cwd=tabsyn_root, + env=env +) +if ret.returncode != 0: + print("[TabSyn] VAE training failed") + sys.exit(ret.returncode) + +# Step 2: Train diffusion model on latent space +print(f"[TabSyn] Step 2/2: Training diffusion model") +ret = subprocess.run( + [sys.executable, "main.py", + "--dataname", dataname, + "--mode", "train", + "--method", "tabsyn", + "--gpu", "0"], + cwd=tabsyn_root, + env=env +) +if ret.returncode != 0: + print("[TabSyn] Diffusion training failed") + sys.exit(ret.returncode) +print("[TabSyn] Training complete (VAE + Diffusion)") diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/data/tabsyn_n20/X_cat_test.npy b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/data/tabsyn_n20/X_cat_test.npy new file mode 100644 index 0000000000000000000000000000000000000000..425db9e4e753d49b111758ab37714b9ea0f844dc --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/data/tabsyn_n20/X_cat_test.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:32d26c38e7e13a438a3d45b8e9ebd0c40bdc79bc74599b4f39491a3661ca9ac3 +size 128 diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/data/tabsyn_n20/X_cat_train.npy b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/data/tabsyn_n20/X_cat_train.npy new file mode 100644 index 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--git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/data/tabsyn_n20/test.csv b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/data/tabsyn_n20/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..eb2ea62137a67a2c34081011d3829d00d95e6096 --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/data/tabsyn_n20/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e1a8d2910fbc1f78f2a58a208938e8c565d222cccaa0f516fcfd93a0d46db489 +size 252576 diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/data/tabsyn_n20/train.csv b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/data/tabsyn_n20/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..eb2ea62137a67a2c34081011d3829d00d95e6096 --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/data/tabsyn_n20/train.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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}, + { + "feature_name": "V", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "AP", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "RH", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "PE", + "data_type": "continuous", + "is_target": true + } +] \ No newline at end of file diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/staged/public/test.csv b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..88524bb10b10f11146922a7f3382c62f2bbf780a --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5db4ad3456ef2c15e4c6e8e3e2405eb0d506997097ae5af3de903a5fe5608cce +size 31623 diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/staged/public/train.csv 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index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/staged/tabsyn/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/staged/tabsyn/model_input_manifest.json b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/staged/tabsyn/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..6dbe886791faf2aaa213b3d22b2c6d633e1c6565 --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/staged/tabsyn/model_input_manifest.json @@ -0,0 +1,119 @@ +{ + "dataset_id": "n20", + "model": "tabsyn", + "target_column": "PE", + "task_type": "regression", + "column_schema": [ + { + "name": "AT", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + 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"/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabsyn/tabsyn-n20-20260427_025043/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabsyn/tabsyn-n20-20260427_025043/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabsyn/tabsyn-n20-20260427_025043/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n20/tabsyn/tabsyn-n20-20260427_025043/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/synthetic/tabsyn_n20/real.csv b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/synthetic/tabsyn_n20/real.csv new file mode 100644 index 0000000000000000000000000000000000000000..eb2ea62137a67a2c34081011d3829d00d95e6096 --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/synthetic/tabsyn_n20/real.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e1a8d2910fbc1f78f2a58a208938e8c565d222cccaa0f516fcfd93a0d46db489 +size 252576 diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/synthetic/tabsyn_n20/test.csv b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/synthetic/tabsyn_n20/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..eb2ea62137a67a2c34081011d3829d00d95e6096 --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/synthetic/tabsyn_n20/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e1a8d2910fbc1f78f2a58a208938e8c565d222cccaa0f516fcfd93a0d46db489 +size 252576 diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/tabsyn-n20-7654-20260427_025104.csv b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/tabsyn-n20-7654-20260427_025104.csv new file mode 100644 index 0000000000000000000000000000000000000000..1268a5473e1512b858a17fc938dba6d9b1c08883 --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/tabsyn-n20-7654-20260427_025104.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dbbf560c2d982397c7c8d219e97990262b4e4932e25bbf4c908f439852b0a5d2 +size 370268 diff --git a/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/train_20260427_025043.log b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/train_20260427_025043.log new file mode 100644 index 0000000000000000000000000000000000000000..67105782b2c81155280fe37d2cebd8329fbeaafa --- /dev/null +++ b/syntheticSuccess/n20/tabsyn/tabsyn-n20-20260427_025043/train_20260427_025043.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:47907a18e76748873c412faa733266c6b43fbcf30a32a5c448672f16b7d44ad2 +size 3125 diff --git a/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/_tvae_generate.py b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/_tvae_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..334417c718a60d665c90113e00180ea498857996 --- /dev/null +++ b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/_tvae_generate.py @@ -0,0 +1,21 @@ +import os, sys +sys.path.insert(0, "/work") +from src.SpecificModels.ctgan_rdt_inverse_fix import apply_ctgan_inverse_fix +apply_ctgan_inverse_fix() +import pandas as pd +from ctgan.synthesizers.tvae import TVAE +os.environ.setdefault("LOKY_MAX_CPU_COUNT", "8") +os.environ.setdefault("OPENBLAS_NUM_THREADS", "8") +os.environ.setdefault("MKL_NUM_THREADS", "8") +model = TVAE.load("/work/output-SpecializedModels/n20/tvae/tvae-n20-20260328_054850/models_300epochs/tvae_300epochs.pt") +total = 7654 +chunk = min(50000, total) if total > 50000 else total +parts = [] +left = total +while left > 0: + take = min(chunk, left) + parts.append(model.sample(take)) + left -= take +samples = pd.concat(parts, ignore_index=True) if len(parts) > 1 else parts[0] +samples.to_csv("/work/output-SpecializedModels/n20/tvae/tvae-n20-20260328_054850/tvae-n20-7654-20260423_040345.csv", index=False) +print(f"[TVAE] Generated {total} rows (chunks={len(parts)}) -> /work/output-SpecializedModels/n20/tvae/tvae-n20-20260328_054850/tvae-n20-7654-20260423_040345.csv") diff --git a/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/_tvae_train.py b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/_tvae_train.py new file mode 100644 index 0000000000000000000000000000000000000000..a683ee11aac45b9aa960fdccdff55451a2220a07 --- /dev/null +++ b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/_tvae_train.py @@ -0,0 +1,16 @@ +import json, sys +import pandas as pd +from ctgan.data import read_csv +from ctgan.synthesizers.tvae import TVAE + +csv_path = "/work/output-SpecializedModels/n20/tvae/tvae-n20-20260328_054850/staged/public/train.csv" +meta_path = "/work/output-SpecializedModels/n20/tvae/tvae-n20-20260328_054850/tvae_metadata.json" +save_path = "/work/output-SpecializedModels/n20/tvae/tvae-n20-20260328_054850/models_300epochs/tvae_300epochs.pt" +epochs = 300 + +data, discrete_columns = read_csv(csv_path, meta_path, header=True, discrete=None) +print(f"[TVAE] Training on {len(data)} rows, {len(data.columns)} cols, epochs={epochs}") +model = TVAE(epochs=epochs, batch_size=500) +model.fit(data, discrete_columns) +model.save(save_path) +print(f"[TVAE] Model saved -> {save_path}") diff --git a/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/gen_20260328_055255.log b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/gen_20260328_055255.log new file mode 100644 index 0000000000000000000000000000000000000000..d70bbfefd255b82a7314af9e1e92c176c4e4a6e9 --- /dev/null +++ b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/gen_20260328_055255.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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https://git-lfs.github.com/spec/v1 +oid sha256:20ab0f01330ff8c23cb888a86740e0b0d97362b90951f7b6c90fbbe108377cf9 +size 542 diff --git a/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/input_snapshot.json b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..4f87e960764e5bbffe32e8b2f91fc5df5c018742 --- /dev/null +++ b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n20", + "model": "tvae", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-train.csv", + "exists": true, + "size": 291758, + "sha256": "8768b9641a081ce32375b2739c6d0a6cdf66c1b03268c7db5f71ffd0019c97e2" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-val.csv", + "exists": true, + "size": 36657, + "sha256": "c2dae02f854856ba824310ecaca5c73a72a3302753396aa681c82b69d65b174c" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n20/n20-test.csv", + "exists": true, + "size": 36232, + "sha256": "82c48522e82ea4c5e4c407ec9239e82558dcff1df413f3d0c382e77fa041bc88" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n20/n20-dataset_profile.json", + "exists": true, + "size": 2675, + "sha256": "7e7d747ab11beae1e58278dc8d6ae08d7ae6f14fe93f77a4fc1e6e589df21df4" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n20/n20-dataset_contract_v1.json", + "exists": true, + "size": 3047, + "sha256": "20f513ccbc9f09d5286bc8998a5772f42b78b40aa1ed60b079fa73edf9c78eec" + } + } +} \ No newline at end of file diff --git a/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/models_300epochs/train_20260328_054850.log b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/models_300epochs/train_20260328_054850.log new file mode 100644 index 0000000000000000000000000000000000000000..df4b7ea7956cd253ccdbe76589e6e8ead7f29bf2 --- /dev/null +++ b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/models_300epochs/train_20260328_054850.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e5aaeab29cbdf838004382a70b877b12ff3713a1f8f13ecf0b7918b9d2fdac10 +size 171 diff --git a/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/models_300epochs/tvae_300epochs.pt b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/models_300epochs/tvae_300epochs.pt new file mode 100644 index 0000000000000000000000000000000000000000..202ec7d207c46a043202e4e29b45f0e1778c31b5 --- /dev/null +++ b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/models_300epochs/tvae_300epochs.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d377656a20e5a3c33a5da0ccc71c846bfa423f39be547f658452bd85ec12590b +size 456748 diff --git a/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/public_gate/normalized_schema_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..8618a420d9d101a283cfb38feb336ac37687988f --- /dev/null +++ b/syntheticSuccess/n20/tvae/tvae-n20-20260328_054850/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,112 @@ +{ + "dataset_id": "n20", + "target_column": "PE", + "task_type": "regression", + "columns": [ + { + "name": "AT", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2635, + "unique_ratio": 0.344264, + "example_values": [ + "29.64", + "10.63", + "27.09", + "24.2", + "15.31" + ] + } + }, + { + "name": "V", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": 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