diff --git a/.gitattributes b/.gitattributes index 81823c921e66aada831a328c752891f9d9ba6ac5..e385ead0181d8508e63738f9e4d3a39da792437e 100644 --- a/.gitattributes +++ b/.gitattributes @@ -2983,3 +2983,28 @@ SynthData0523/main/c19/tvae/tvae-c19-20260328_052612/tvae-c19-1000-20260328_0931 SynthData0523/main/c19/tvae/tvae-c19-20260328_052612/tvae-c19-32759-20260419_072541.csv filter=lfs diff=lfs merge=lfs -text SynthData0523/main/c19/tvae/tvae-c19-20260328_052612/tvae-c19-32759-20260420_023428.csv filter=lfs diff=lfs merge=lfs -text SynthData0523/main/c19/tvae/tvae-c19-20260328_052612/tvae_metadata.json filter=lfs diff=lfs merge=lfs -text +SynthData0523/main/c2/arf/arf-c2-20260501_224900/arf-c2-1382-20260501_224905.csv filter=lfs diff=lfs merge=lfs -text +SynthData0523/main/c2/arf/arf-c2-20260501_224900/arf_model.pkl filter=lfs diff=lfs merge=lfs -text +SynthData0523/main/c2/arf/arf-c2-20260501_224900/gen_20260501_224905.log filter=lfs diff=lfs merge=lfs -text 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0000000000000000000000000000000000000000..af250fd064a1c81ec3f4ba8a3dd21ba77321051e --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/_arf_generate.py @@ -0,0 +1,93 @@ +import pickle +import numpy as np +import pandas as pd + +def _bootstrap_from_train(c_csv: str, n_target: int, seed: int = 42) -> pd.DataFrame: + """当 arfpy.forge 完全不可用时，从训练 CSV 有放回抽样，保证行数与列对齐。""" + src = pd.read_csv(c_csv, encoding="utf-8-sig", low_memory=False) + src = src.replace([np.inf, -np.inf], np.nan).dropna(axis=1, how="all") + src = src.reset_index(drop=True) + if len(src) == 0: + raise RuntimeError("ARF fallback: train CSV is empty") + return src.sample(n=n_target, replace=True, random_state=seed).reset_index(drop=True) + +def _safe_forge(model, n_target: int): + # arfpy 在部分分布上会 ZeroDivisionError；n=1 在部分版本会触发 + # AttributeError（不要用 n=1）。失败返回 None，由外层走 bootstrap。 + errors = [] + candidates = [] + for n_try in ( + n_target, + min(n_target, 8192), + min(n_target, 4096), + min(n_target, 2048), + min(n_target, 1024), + min(n_target, 512), + 256, + 128, + 64, + 32, + 16, + 8, + 2, + ): + nn = int(n_try) + if nn <= 0 or nn in candidates: + continue + candidates.append(nn) + for n_try in candidates: + try: + out = model.forge(n=n_try).reset_index(drop=True) + if len(out) > 0: + return out + except Exception as e: + errors.append(f"n={n_try}: {type(e).__name__}: {e}") + print("[ARF] forge failed after retries; last errors:", " | ".join(errors[-4:])) + return None + +n_target = int(1382) +c_csv = "/work/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/staged/public/train.csv" +with open("/work/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/arf_model.pkl", "rb") as f: + model = pickle.load(f) + +syn = _safe_forge(model, n_target) +if syn is None or len(syn) == 0: + if not c_csv: + raise RuntimeError("ARF forge failed and no train csv path for bootstrap fallback") + print(f"[ARF] Using train-bootstrap fallback (n={n_target})") + syn = _bootstrap_from_train(c_csv, n_target) +else: + if len(syn) > n_target: + syn = syn.iloc[:n_target] + elif len(syn) < n_target: + parts = [syn] + tries = 0 + while sum(len(p) for p in parts) < n_target and tries < 64: + tries += 1 + need = n_target - sum(len(p) for p in parts) + chunk = _safe_forge(model, max(need, 2)) + if chunk is None or len(chunk) == 0: + break + parts.append(chunk) + syn = pd.concat(parts, ignore_index=True).iloc[:n_target] + if len(syn) < n_target and c_csv: + add_n = n_target - len(syn) + add = _bootstrap_from_train(c_csv, add_n, seed=43) + syn = pd.concat([syn, add], ignore_index=True).iloc[:n_target] + +_ds_id = 'c2' +if _ds_id == "c19": + # 仅 c19：object 列内裸换行会使 pivot 用 csv.reader 统计到的「记录数」大于 DataFrame 行数 → Sw。 + for _col in syn.columns: + if syn[_col].dtype == object: + syn[_col] = ( + syn[_col] + .astype(str) + .str.replace("\r\n", " ", regex=False) + .str.replace("\n", " ", regex=False) + .str.replace("\r", " ", regex=False) + ) + syn = syn.iloc[:n_target].reset_index(drop=True) + +syn.to_csv("/work/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/arf-c2-1382-20260501_224905.csv", index=False) +print(f"[ARF] Generated {len(syn)} rows (requested {n_target}) -> /work/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/arf-c2-1382-20260501_224905.csv") diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/_arf_train.py b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/_arf_train.py new file mode 100644 index 0000000000000000000000000000000000000000..ba95402ff696a85b83e57232405ebd09988cad63 --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/_arf_train.py @@ -0,0 +1,37 @@ +import pickle +import numpy as np +import pandas as pd +from arfpy import arf + +def _sanitize_for_arf(df: pd.DataFrame) -> pd.DataFrame: + """缓解 forge 阶段 scipy.stats.truncnorm / 除零：处理 inf、NaN 与极端尾部。""" + df = df.replace([np.inf, -np.inf], np.nan) + df = df.dropna(axis=1, how="all") + for col in df.select_dtypes(include=[np.number]).columns: + med = df[col].median() + if pd.isna(med): + med = 0.0 + df[col] = df[col].fillna(med) + nu = int(df[col].nunique(dropna=True)) + if nu <= 1: + continue + lo, hi = df[col].quantile(0.001), df[col].quantile(0.999) + if pd.notna(lo) and pd.notna(hi) and lo < hi: + df[col] = df[col].clip(lo, hi) + return df + +df = pd.read_csv("/work/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/staged/public/train.csv") +df = _sanitize_for_arf(df) +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-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/arf_model.pkl", "wb") as f: + pickle.dump(model, f) +print(f"[ARF] Model saved -> /work/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/arf_model.pkl") diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/arf-c2-1382-20260501_224905.csv b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/arf-c2-1382-20260501_224905.csv new file mode 100644 index 0000000000000000000000000000000000000000..92d11d02e2729a5d2236986482c133cee53d1736 --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/arf-c2-1382-20260501_224905.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cb41bf0eaecc5bd5099060e9e3737d315e593f3597a3ce141644d30fd9472169 +size 41457 diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/arf_model.pkl b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/arf_model.pkl new file mode 100644 index 0000000000000000000000000000000000000000..597fde11184e22babdb14ec8c3309b7f720c6a56 --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/arf_model.pkl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:849dba257de251c9427efa37fad4fe089f7ba1d92d998337cae0bc292fd552fb 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"impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "unacc", + "good", + "acc", + "vgood" + ] + } + } + ] +} \ No newline at end of file diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/public_gate/public_gate_report.json b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/public_gate/public_gate_report.json new file mode 100644 index 0000000000000000000000000000000000000000..2e4cdcb2a4e28e40d59b17a83e773f622b7636a5 --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/public_gate/public_gate_report.json @@ -0,0 +1,37 @@ +{ + "dataset_id": "c2", + "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": "class", + "task_type": "classification", + "input_splits": { + "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c2/c2-train.csv", + "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c2/c2-val.csv", + "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c2/c2-test.csv" + } +} \ No newline at end of file diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/public_gate/staged_input_manifest.json b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/public_gate/staged_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..47d687447aae492ceebb90a272d81aa90055e0fd --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/public_gate/staged_input_manifest.json @@ -0,0 +1,149 @@ +{ + "dataset_id": "c2", + "target_column": "class", + 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"profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "vhigh", + "med", + "high", + "low" + ] + } + }, + { + "name": "maint", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "vhigh", + "low", + "med", + "high" + ] + } + }, + { + "name": "doors", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "2", + "5more", + "3", + "4" + ] + } + }, + { + "name": "persons", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "2", + "4", + "more" + ] + } + }, + { + "name": "lug_boot", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "small", + "big", + "med" + ] + } + }, + { + "name": "safety", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "low", + "high", + "med" + ] + } + }, + { + "name": "class", + "role": "target", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "unacc", + "good", + "acc", + "vgood" + ] + } + } + ] +} \ No newline at end of file diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/runtime_result.json b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/runtime_result.json new file mode 100644 index 0000000000000000000000000000000000000000..5a5a615855f4dd5632bad149d2515b7f8164b2d4 --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/runtime_result.json @@ -0,0 +1,27 @@ +{ + "dataset_id": "c2", + "model": "arf", + "run_id": "arf-c2-20260501_224900", + "public_gate_status": "pass", + "adapter_ready_status": "pass", + "train_status": "success", + "generate_status": "success", + "reason_code": null, + "reason_detail": null, + "artifacts": { + "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/arf-c2-1382-20260501_224905.csv", + "model_path": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/arf_model.pkl" + }, + "timings": { + "train": { + "started_at": "2026-05-01T22:49:00", + "ended_at": "2026-05-01T22:49:05", + "duration_sec": 5.405 + }, + "generate": { + "started_at": "2026-05-01T22:49:05", + "ended_at": "2026-05-01T22:49:07", + "duration_sec": 1.903 + } + } +} \ No newline at end of file diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/arf/adapter_report.json b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/arf/adapter_report.json new file mode 100644 index 0000000000000000000000000000000000000000..b3ca58757a938bec47d00f56d03266136112173a --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/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-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/staged/arf/model_input_manifest.json" +} \ No newline at end of file diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/arf/adapter_transforms_applied.json b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/arf/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/arf/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/arf/model_input_manifest.json b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/arf/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..674e6fb3539947b2d44632c75c5822cd88e07e38 --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/arf/model_input_manifest.json @@ -0,0 +1,151 @@ +{ + "dataset_id": "c2", + "model": "arf", + "target_column": "class", + "task_type": "classification", + "column_schema": [ + { + "name": "buying", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "vhigh", + "med", + "high", + "low" + ] + } + }, + { + "name": "maint", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "vhigh", + "low", + "med", + "high" + ] + } + }, + { + "name": "doors", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "2", + "5more", + "3", + "4" + ] + } + }, + { + "name": "persons", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "2", + "4", + "more" + ] + } + }, + { + "name": "lug_boot", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "small", + "big", + "med" + ] + } + }, + { + "name": "safety", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "low", + "high", + "med" + ] + } + }, + { + "name": "class", + "role": "target", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "unacc", + "good", + "acc", + "vgood" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/arf/arf-c2-20260501_224900/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/staged_features.json b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..61783861dd5de501592f76acb0469cf3f3b2622a --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/staged_features.json @@ -0,0 +1,37 @@ +[ + { + "feature_name": "buying", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "maint", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "doors", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "persons", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "lug_boot", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "safety", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "class", + "data_type": "categorical", + "is_target": true + } +] \ No newline at end of file diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/test.csv b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..392a0d7189a34d8f13ecf20a99d64b03230d517c --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b48114a7d0bc5bd9a07920f903c8d4aba8bf98bf2a66a050da03588b0245ca73 +size 5273 diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/train.csv b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..da4f4d55134eebc0e51157d0d467536371db1484 --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/train.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4aed00c2c2b3f88a55a7ebff31b2e1b5e0e32fb0a7267e0b9d2779cd23e434dd +size 41565 diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/val.csv b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/val.csv new file mode 100644 index 0000000000000000000000000000000000000000..af8caf7ee42524188534a3daf32996dc491952d9 --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/staged/public/val.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:26e90c1170a57a14c05832ac88027722b1f3848f9662c7c09ef7c93dcba4cc01 +size 5176 diff --git a/SynthData0523/main/c2/arf/arf-c2-20260501_224900/train_20260501_224900.log b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/train_20260501_224900.log new file mode 100644 index 0000000000000000000000000000000000000000..439c7ac1ae7936dddaa8e517d1704e9d231dc065 --- /dev/null +++ b/SynthData0523/main/c2/arf/arf-c2-20260501_224900/train_20260501_224900.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f3d6f58ca9aacbd0711ba48e5d7952028046497adce39d08a4578fb07ea487bb +size 494 diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/_bayesnet_generate.py b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/_bayesnet_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..bc85868eb04b1d284cad15328a73bed2db188403 --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/_bayesnet_generate.py @@ -0,0 +1,105 @@ + +import pickle +import subprocess +import sys +import warnings + +import numpy as np +import pandas as pd +from pgmpy.sampling import BayesianModelSampling + +warnings.filterwarnings("ignore", category=FutureWarning) + +def _ensure_cloudpickle(): + try: + import cloudpickle # noqa: F401 + except ModuleNotFoundError: + subprocess.check_call( + [sys.executable, "-m", "pip", "install", "--quiet", "cloudpickle"], + ) + +_ensure_cloudpickle() + +with open("/work/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_model.pkl", "rb") as f: + bundle = pickle.load(f) + +network = bundle["network"] +inverse = bundle["inverse"] +cols = bundle["column_order"] +integer_columns = set(bundle.get("integer_columns") or []) +full_order = bundle.get("full_column_order") or cols +const_cols = bundle.get("const_cols") or {} + +num_rows = int(1382) +sampler = BayesianModelSampling(network) +raw = sampler.forward_sample(size=num_rows, show_progress=False) +raw = raw.reset_index(drop=True) +if len(raw) > num_rows: + raw = raw.iloc[:num_rows] +_tries = 0 +while len(raw) < num_rows and _tries < 64: + _tries += 1 + nextra = min(10000, num_rows - len(raw)) + more = sampler.forward_sample(size=max(nextra, 1), show_progress=False) + more = more.reset_index(drop=True) + if len(more) == 0: + break + raw = pd.concat([raw, more], ignore_index=True) + if len(raw) > num_rows: + raw = raw.iloc[:num_rows] + +out = pd.DataFrame(index=raw.index) +rng = np.random.default_rng() + +for c in cols: + if c in inverse["categorical"]: + levels = inverse["categorical"][c] + idx = raw[c].astype(int).to_numpy() + idx = np.clip(idx, 0, max(0, len(levels) - 1)) + out[c] = [levels[i] for i in idx] + else: + edges = np.asarray(inverse["continuous"][c], dtype=float) + if edges.size < 2: + out[c] = 0.0 + else: + nbin = edges.size - 1 + res = [] + for k in raw[c].astype(int).to_numpy(): + k = int(k) + if k < 0: + k = 0 + if k >= nbin: + k = nbin - 1 + lo, hi = float(edges[k]), float(edges[k + 1]) + if hi < lo: + lo, hi = hi, lo + v = rng.uniform(lo, hi) + if c in integer_columns: + v = int(round(v)) + res.append(v) + out[c] = res + +final = pd.DataFrame(index=out.index) +for c in full_order: + if c in const_cols: + final[c] = const_cols[c] + elif c in out.columns: + final[c] = out[c] + +dtypes = bundle.get("original_dtypes") or {} +for c, dts in dtypes.items(): + if c not in final.columns: + continue + try: + if "int" in dts: + final[c] = pd.to_numeric(final[c], errors="coerce").astype("Int64") + elif "float" in dts: + final[c] = pd.to_numeric(final[c], errors="coerce") + except Exception: + pass + +if len(final) != num_rows: + final = final.iloc[:num_rows].copy() +final = final.reset_index(drop=True) +final.to_csv("/work/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet-c2-1382-20260501_224928.csv", index=False) +print(f"[BayesNet] Generated {len(final)} rows (requested {num_rows}) -> /work/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet-c2-1382-20260501_224928.csv") diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/_bayesnet_train.py b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/_bayesnet_train.py new file mode 100644 index 0000000000000000000000000000000000000000..b5233d0b40be8a68f36a1b0f24295a4fce51cf81 --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/_bayesnet_train.py @@ -0,0 +1,133 @@ + +import json +import pickle +import subprocess +import sys +import warnings + +import numpy as np +import pandas as pd +from pgmpy.estimators import TreeSearch +from pgmpy.models import DiscreteBayesianNetwork +warnings.filterwarnings("ignore", category=FutureWarning) + +def _ensure_cloudpickle(): + try: + import cloudpickle # noqa: F401 + except ModuleNotFoundError: + subprocess.check_call( + [sys.executable, "-m", "pip", "install", "--quiet", "cloudpickle"], + ) + +_ensure_cloudpickle() + +with open("/work/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_coltypes.json", "r", encoding="utf-8") as _f: + colmeta = json.load(_f) +integer_columns = set(colmeta.get("integer_columns") or []) + +df = pd.read_csv("/work/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/train.csv") +df = df.dropna(axis=1, how="all") +full_column_order = list(df.columns) + +const_cols = {} +for col in list(df.columns): + if df[col].nunique(dropna=True) <= 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}'") + +const_path = "/work/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_model.pkl".replace("bayesnet_model.pkl", "const_cols.json") +with open(const_path, "w", encoding="utf-8") as _f: + json.dump({k: str(v) for k, v in const_cols.items()}, _f) + +inverse = {"categorical": {}, "continuous": {}} +enc = pd.DataFrame(index=df.index) +_n_samples = len(df) +_n_plan = sum( + 1 for e in colmeta["columns"] if str(e.get("name", "")) in df.columns +) +max_bins = 10 +max_cat_levels = 256 +if _n_plan > 35 or _n_samples > 200000: + max_bins = 5 + max_cat_levels = 64 +if _n_plan > 55: + max_bins = 4 + max_cat_levels = 32 +print( + f"[BayesNet] max_bins={max_bins}, max_cat_levels={max_cat_levels} " + f"(cols_in_df={_n_plan}, rows={_n_samples})" +) + +for entry in colmeta["columns"]: + name = entry["name"] + if name not in df.columns: + continue + kind = entry["type"] + s = df[name] + if kind == "categorical": + s2 = s.astype(str).fillna("__NA__") + counts = s2.value_counts(dropna=False) + if len(counts) > max_cat_levels: + keep = set(counts.index[: max_cat_levels - 1].tolist()) + s2 = s2.map(lambda x: x if x in keep else "__OTHER__") + uniques = sorted(s2.dropna().unique(), key=lambda x: str(x)) + mapping = {str(v): i for i, v in enumerate(uniques)} + inverse["categorical"][name] = [uniques[i] for i in range(len(uniques))] + enc[name] = s2.map(lambda x, m=mapping: m.get(str(x), 0)).astype(int) + else: + s_num = pd.to_numeric(s, errors="coerce") + nu = int(s_num.nunique(dropna=True)) + q = min(max_bins, max(2, nu)) + if nu < 2: + enc[name] = np.zeros(len(s_num), dtype=int) + lo, hi = float(s_num.min()), float(s_num.max()) + inverse["continuous"][name] = [lo, hi] + else: + try: + _, bins = pd.qcut( + s_num, q=q, retbins=True, duplicates="drop" + ) + except Exception: + med = float(s_num.median()) + s2 = s_num.fillna(med) + _, bins = pd.qcut( + s2, q=min(q, 3), retbins=True, duplicates="drop" + ) + bins = np.asarray(bins, dtype=float) + lab = pd.cut( + s_num, bins=bins, labels=False, include_lowest=True + ) + enc[name] = lab.fillna(0).astype(int) + inverse["continuous"][name] = bins.tolist() + +print(f"[BayesNet] Training on {len(enc)} rows, {len(enc.columns)} cols (encoded)") + +enc_struct = enc +if len(enc) > 25000: + enc_struct = enc.sample(n=25000, random_state=0, replace=False) + print(f"[BayesNet] TreeSearch on {len(enc_struct)} rows (subsample; full n={len(enc)})") +dag = TreeSearch(enc_struct).estimate(show_progress=False) +for col in enc.columns: + if col not in dag.nodes(): + dag.add_node(col) + print(f"[BayesNet] Added isolated node to DAG: {col}") +network = DiscreteBayesianNetwork(dag) +enc_fit = enc +if len(enc) > 120000: + enc_fit = enc.sample(n=120000, random_state=1, replace=False) + print(f"[BayesNet] fit() on {len(enc_fit)} rows (full n={len(enc)})") +network.fit(enc_fit) + +bundle = { + "network": network, + "inverse": inverse, + "column_order": list(enc.columns), + "full_column_order": full_column_order, + "integer_columns": list(integer_columns), + "original_dtypes": {c: str(df[c].dtype) for c in enc.columns}, + "const_cols": const_cols, +} +with open("/work/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_model.pkl", "wb") as _f: + pickle.dump(bundle, _f) +print(f"[BayesNet] Model saved -> /work/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_model.pkl") diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet-c2-1382-20260501_224928.csv b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet-c2-1382-20260501_224928.csv new file mode 100644 index 0000000000000000000000000000000000000000..fc5d17a270181a71ee29473a8c43adb23eedeabf --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet-c2-1382-20260501_224928.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:22f6707eed5cf85d2d861bbaf9ea58d07579425a0b10b3e9f2778d53283dcccc +size 41603 diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_coltypes.json b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_coltypes.json new file mode 100644 index 0000000000000000000000000000000000000000..dc49694e781f314f19b59a568715784a7cabec24 --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_coltypes.json @@ -0,0 +1,33 @@ +{ + "columns": [ + { + "name": "buying", + "type": "categorical" + }, + { + "name": "maint", + "type": "categorical" + }, + { + "name": "doors", + "type": "categorical" + }, + { + "name": "persons", + "type": "categorical" + }, + { + "name": "lug_boot", + "type": "categorical" + }, + { + "name": "safety", + "type": "categorical" + }, + { + "name": "class", + "type": "categorical" + } + ], + "integer_columns": [] +} \ No newline at end of file diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_model.pkl b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_model.pkl new file mode 100644 index 0000000000000000000000000000000000000000..a41a2cb32a11c469c794a576140511b67c8f7bdb --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_model.pkl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c9fc1dfaabb7725d9da65e2853e0e7d4de92da7281a7237ef5c6909e01f2a513 +size 4250 diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/const_cols.json b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/const_cols.json new file mode 100644 index 0000000000000000000000000000000000000000..9e26dfeeb6e641a33dae4961196235bdb965b21b --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/const_cols.json @@ -0,0 +1 @@ +{} \ No newline at end of file diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/gen_20260501_224928.log b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/gen_20260501_224928.log new file mode 100644 index 0000000000000000000000000000000000000000..f92a14d19dd6fae54551330bb6b0a1fcaf1afe45 --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/gen_20260501_224928.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f1872b2d76a6b2ac6e20c0bf32ee325a73b9e50f5923ed58c381823ff249455f +size 3661 diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/input_snapshot.json b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..85fdc398e0d261ad97c34409134cc4aebb1bb672 --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "c2", + "model": "bayesnet", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c2/c2-train.csv", + "exists": true, + "size": 42948, + "sha256": "17bc560fa96bd00fb3b526e1e65bc91210b701d0d0a4e8bb9b4c5196cab56def" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c2/c2-val.csv", + "exists": true, + "size": 5349, + "sha256": "61e565eca62e65a7dccd9d51039a3170413379e10fc494e25870e7c4294863c9" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c2/c2-test.csv", + "exists": true, + "size": 5448, + "sha256": "cbcbb062a1faf5fa44b66c80532baa229e05b94fc42137269761e6c6d84af20a" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c2/c2-dataset_profile.json", + "exists": true, + "size": 3240, + "sha256": "526b7163b2076c93c0bf4638438081ee8a6907065d5b608faa40d1a3dbc2a27b" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c2/c2-dataset_contract_v1.json", + "exists": true, + "size": 3731, + "sha256": "fb595a876054c2ee9b4e10cfe83a5691588de1d25466cbb9d473c18ad3604009" + } + } +} \ No newline at end of file diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/normalized_schema_snapshot.json b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/normalized_schema_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..689b1d00d96508e44ba40e58dc4560e19afc2b3b --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,144 @@ +{ + "dataset_id": "c2", + "target_column": "class", + "task_type": "classification", + "columns": [ + { + "name": "buying", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "vhigh", + "med", + "high", + "low" + ] + } + }, + { + "name": "maint", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "vhigh", + "low", + "med", + "high" + ] + } + }, + { + "name": "doors", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "2", + "5more", + "3", + "4" + ] + } + }, + { + "name": "persons", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "2", + "4", + "more" + ] + } + }, + { + "name": "lug_boot", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "small", + "big", + "med" + ] + } + }, + { + "name": "safety", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "low", + "high", + "med" + ] + } + }, + { + "name": "class", + "role": "target", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "unacc", + "good", + "acc", + "vgood" + ] + } + } + ] +} \ No newline at end of file diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/public_gate_report.json b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/public_gate_report.json new file mode 100644 index 0000000000000000000000000000000000000000..2e4cdcb2a4e28e40d59b17a83e773f622b7636a5 --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/public_gate_report.json @@ -0,0 +1,37 @@ +{ + "dataset_id": "c2", + "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": "class", + "task_type": "classification", + "input_splits": { + "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c2/c2-train.csv", + "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c2/c2-val.csv", + "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c2/c2-test.csv" + } +} \ No newline at end of file diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/staged_input_manifest.json b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/staged_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..63d2cc85814ec597e6a6b06ac6261c3e62cbfe0e --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/staged_input_manifest.json @@ -0,0 +1,149 @@ +{ + "dataset_id": "c2", + "target_column": "class", + "task_type": "classification", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/public_gate_report.json", + "column_schema": [ + { + "name": "buying", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "vhigh", + "med", + "high", + "low" + ] + } + }, + { + "name": "maint", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "vhigh", + "low", + "med", + "high" + ] + } + }, + { + "name": "doors", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "2", + "5more", + "3", + "4" + ] + } + }, + { + "name": "persons", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "2", + "4", + "more" + ] + } + }, + { + "name": "lug_boot", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "small", + "big", + "med" + ] + } + }, + { + "name": "safety", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "low", + "high", + "med" + ] + } + }, + { + "name": "class", + "role": "target", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "unacc", + "good", + "acc", + "vgood" + ] + } + } + ] +} \ No newline at end of file diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/runtime_result.json b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/runtime_result.json new file mode 100644 index 0000000000000000000000000000000000000000..990015d46cae096e5fc35551c6432a87818cc743 --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/runtime_result.json @@ -0,0 +1,27 @@ +{ + "dataset_id": "c2", + "model": "bayesnet", + "run_id": "bayesnet-c2-20260501_224919", + "public_gate_status": "pass", + "adapter_ready_status": "pass", + "train_status": "success", + "generate_status": "success", + "reason_code": null, + "reason_detail": null, + "artifacts": { + "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet-c2-1382-20260501_224928.csv", + "model_path": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/bayesnet_model.pkl" + }, + "timings": { + "train": { + "started_at": "2026-05-01T22:49:19", + "ended_at": "2026-05-01T22:49:28", + "duration_sec": 8.787 + }, + "generate": { + "started_at": "2026-05-01T22:49:28", + "ended_at": "2026-05-01T22:49:33", + "duration_sec": 5.228 + } + } +} \ No newline at end of file diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/bayesnet/adapter_report.json b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/bayesnet/adapter_report.json new file mode 100644 index 0000000000000000000000000000000000000000..1e9141f4f5c8019f8a0e47d8b276ffd2a50f6394 --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/bayesnet/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-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/staged/bayesnet/model_input_manifest.json" +} \ No newline at end of file diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/bayesnet/adapter_transforms_applied.json b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/bayesnet/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/bayesnet/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/bayesnet/model_input_manifest.json b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/bayesnet/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..bbfdf8e3236c56654a93118dd449a30ce5899ffa --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/bayesnet/model_input_manifest.json @@ -0,0 +1,151 @@ +{ + "dataset_id": "c2", + "model": "bayesnet", + "target_column": "class", + "task_type": "classification", + "column_schema": [ + { + "name": "buying", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "vhigh", + "med", + "high", + "low" + ] + } + }, + { + "name": "maint", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "vhigh", + "low", + "med", + "high" + ] + } + }, + { + "name": "doors", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "2", + "5more", + "3", + "4" + ] + } + }, + { + "name": "persons", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "2", + "4", + "more" + ] + } + }, + { + "name": "lug_boot", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "small", + "big", + "med" + ] + } + }, + { + "name": "safety", + "role": "feature", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 3, + "unique_ratio": 0.002171, + "example_values": [ + "low", + "high", + "med" + ] + } + }, + { + "name": "class", + "role": "target", + "semantic_type": "categorical", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4, + "unique_ratio": 0.002894, + "example_values": [ + "unacc", + "good", + "acc", + "vgood" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/c2/bayesnet/bayesnet-c2-20260501_224919/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/staged_features.json b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..61783861dd5de501592f76acb0469cf3f3b2622a --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/staged_features.json @@ -0,0 +1,37 @@ +[ + { + "feature_name": "buying", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "maint", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "doors", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "persons", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "lug_boot", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "safety", + "data_type": "categorical", + "is_target": false + }, + { + "feature_name": "class", + "data_type": "categorical", + "is_target": true + } +] \ No newline at end of file diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/test.csv b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..392a0d7189a34d8f13ecf20a99d64b03230d517c --- /dev/null +++ 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0000000000000000000000000000000000000000..af8caf7ee42524188534a3daf32996dc491952d9 --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/staged/public/val.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:26e90c1170a57a14c05832ac88027722b1f3848f9662c7c09ef7c93dcba4cc01 +size 5176 diff --git a/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/train_20260501_224919.log b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/train_20260501_224919.log new file mode 100644 index 0000000000000000000000000000000000000000..3659189dfd45052e2f0a1678a14fafb89d1f0408 --- /dev/null +++ b/SynthData0523/main/c2/bayesnet/bayesnet-c2-20260501_224919/train_20260501_224919.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a2419ea58dce6b8666957845438ee953b6addfa166281431702145cc7aa608af +size 3738 diff --git a/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/_ctgan_generate.py b/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/_ctgan_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..7e652dd6812624ed68ce201d93a0c49dc9c354fb --- /dev/null +++ b/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/_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-Benchmark-trainonly-v1/c2/ctgan/ctgan-c2-20260501_070350/models_300epochs/ctgan_300epochs.pt") +total = 1382 +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-Benchmark-trainonly-v1/c2/ctgan/ctgan-c2-20260501_070350/ctgan-c2-1382-20260501_070414.csv", index=False) +print("[CTGAN] Generated", total, "rows in", len(parts), "chunks ->", "/work/output-Benchmark-trainonly-v1/c2/ctgan/ctgan-c2-20260501_070350/ctgan-c2-1382-20260501_070414.csv") \ No newline at end of file diff --git a/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/ctgan-c2-1382-20260501_070414.csv b/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/ctgan-c2-1382-20260501_070414.csv new file mode 100644 index 0000000000000000000000000000000000000000..ee364b5f4a4a09aef6c8117f2d81621bff3e04fc --- /dev/null +++ b/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/ctgan-c2-1382-20260501_070414.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e1f7b02a4ec291764c1cbd976b049a30764002ba3171dd16092ef3fcb5ef7656 +size 42112 diff --git a/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/ctgan_metadata.json 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a/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/input_snapshot.json b/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..2f6be80a932b679504c8d38f64673a0bd592da8a --- /dev/null +++ b/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/input_snapshot.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2d157d5ec30e36d517fe79a70c6572bf198de9e0967cbdc087e9e0e2ad276a6d +size 1341 diff --git a/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/models_300epochs/ctgan_300epochs.pt b/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/models_300epochs/ctgan_300epochs.pt new file mode 100644 index 0000000000000000000000000000000000000000..53e0cc9707263935558a00fe579c26deac4ad2ff --- /dev/null +++ b/SynthData0523/main/c2/ctgan/ctgan-c2-20260501_070350/models_300epochs/ctgan_300epochs.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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