diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/_arf_generate.py b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/_arf_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..2bcef371b025df34d7920374e596ebae628bc1a7 --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/_arf_generate.py @@ -0,0 +1,6 @@ +import pickle +with open("/work/output-SpecializedModels/c9/arf/arf-c9-20260321_065512/arf_model.pkl", "rb") as f: + model = pickle.load(f) +syn = model.forge(n=26215) +syn.to_csv("/work/output-SpecializedModels/c9/arf/arf-c9-20260321_065512/arf-c9-26215-20260330_065333.csv", index=False) +print(f"[ARF] Generated 26215 rows -> /work/output-SpecializedModels/c9/arf/arf-c9-20260321_065512/arf-c9-26215-20260330_065333.csv") diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/_arf_train.py b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/_arf_train.py new file mode 100644 index 0000000000000000000000000000000000000000..c22ed961fe8f191431a1a2e1e383c922e61058f9 --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/_arf_train.py @@ -0,0 +1,19 @@ +import pickle +import pandas as pd +from arfpy import arf + +df = pd.read_csv("/work/output-SpecializedModels/c9/arf/arf-c9-20260321_065512/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/c9/arf/arf-c9-20260321_065512/arf_model.pkl", "wb") as f: + pickle.dump(model, f) +print(f"[ARF] Model saved -> /work/output-SpecializedModels/c9/arf/arf-c9-20260321_065512/arf_model.pkl") diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/arf-c9-1000-20260321_070552.csv b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/arf-c9-1000-20260321_070552.csv new file mode 100644 index 0000000000000000000000000000000000000000..ac1c768d65cb3889f015b6a14b27d9af1ad14743 --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/arf-c9-1000-20260321_070552.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7a4fe9c44d6203f4daab39b263e892d9988a6ab6ab18b38d44e02423cc03f5a0 +size 156250 diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/arf-c9-26215-20260330_065333.csv b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/arf-c9-26215-20260330_065333.csv new file mode 100644 index 0000000000000000000000000000000000000000..8727b6101096b2edabfe9a3ca062c54984ac9e45 --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/arf-c9-26215-20260330_065333.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:18255ee8219bfaf4a3d367b14ef3d20c511c46db18e4b1dfed229eee411c2f61 +size 4067087 diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/arf_model.pkl b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/arf_model.pkl new file mode 100644 index 0000000000000000000000000000000000000000..bc4896e9176bc40012127818f55dac81b66f1e91 --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/arf_model.pkl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:de8f121fe0ee026212bf7ce7a20a26a82d4f5bf4b34a37ac938c118264a3a450 +size 118258108 diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/gen_20260321_070552.log b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/gen_20260321_070552.log new file mode 100644 index 0000000000000000000000000000000000000000..e900be6925de09b02136e7da02a8c0c7faddf5b1 --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/gen_20260321_070552.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:931af1acd1c09a0b637f832f1b3dec889d0d4db592ad6e81a88debfa43b6baad +size 438 diff --git 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"/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-train.csv", + "exists": true, + "size": 1656550, + "sha256": "7fe9e4b6e2719c346fd93c7ada4977430d0c593cc5bdae7442a78886f7b71b9e" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-val.csv", + "exists": true, + "size": 207139, + "sha256": "01557a0b4304c4b5435df0909d16016ec0ba4ce2c3b31a8815f813ef1376b0b9" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-test.csv", + "exists": true, + "size": 207206, + "sha256": "6de1346ef61646cbd096588223a049bf26f2b26229ac65b2734fed139f3c06bb" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c9/c9-dataset_profile.json", + "exists": true, + "size": 4540, + "sha256": "536d3ace5469df116ca00b7544ee8af409fc29edb7e85f365e465a91244a564e" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c9/c9-dataset_contract_v1.json", + "exists": true, + "size": 5389, + "sha256": "d63ab9aee52c7f931f14b7ad2c9a601b670ba5cd739494b2c4d2e4005430ea6d" + } + } +} \ No newline at end of file diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/public_gate/normalized_schema_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..7ba372afdc8d9d80b5b9ad0413ddec90a8353e37 --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,214 @@ +{ + "dataset_id": "c9", + "target_column": "ROLE_FAMILY", + "task_type": "regression", + "columns": [ + { + "name": "ACTION", + "role": "feature", + "semantic_type": "boolean", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 7.6e-05, + "example_values": [ + "1", + "0" + ] + } + }, + { + "name": "RESOURCE", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 6690, + "unique_ratio": 0.255197, + "example_values": [ + "44623", + "74192", + "79092", + "4675", + "37639" + ] + } + }, + { + "name": "MGR_ID", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4052, + "unique_ratio": 0.154568, + "example_values": [ + "67326", + "16850", + "5223", + "14952", + "88170" + ] + } + }, + { + "name": "ROLE_ROLLUP_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 126, + "unique_ratio": 0.004806, + "example_values": [ + "117910", + "117961", + "118595", + "118200", + "117978" + ] + } + }, + { + "name": "ROLE_ROLLUP_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 174, + "unique_ratio": 0.006637, + "example_values": [ + "117911", + "118225", + "118596", + "117962", + "118201" + ] + } + }, + { + "name": "ROLE_DEPTNAME", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 442, + "unique_ratio": 0.016861, + "example_values": [ + "117912", + "119092", + "81476", + "119223", + "117941" + ] + } + }, + { + "name": "ROLE_TITLE", + "role": 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+ "19721", + "119095", + "117887", + "118205", + "270488" + ] + } + }, + { + "name": "ROLE_CODE", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 334, + "unique_ratio": 0.012741, + "example_values": [ + "118570", + "122850", + "118055", + "119964", + "117888" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/public_gate/public_gate_report.json b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/public_gate/public_gate_report.json new file mode 100644 index 0000000000000000000000000000000000000000..812ee0cc580ee3523d798fa725ff691876b7f855 --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/public_gate/public_gate_report.json @@ -0,0 +1,37 @@ +{ + "dataset_id": "c9", + "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": "ROLE_FAMILY", + "task_type": "regression", + "input_splits": { + "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-train.csv", + "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-val.csv", + "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-test.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/public_gate/staged_input_manifest.json b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/public_gate/staged_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..30ef5c3551df76a79cb22aee9f007934c39c59aa --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/public_gate/staged_input_manifest.json @@ -0,0 +1,219 @@ +{ + "dataset_id": "c9", + "target_column": "ROLE_FAMILY", + "task_type": "regression", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/arf/arf-c9-20260321_065512/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/arf/arf-c9-20260321_065512/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/arf/arf-c9-20260321_065512/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/arf/arf-c9-20260321_065512/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/arf/arf-c9-20260321_065512/public_gate/public_gate_report.json", + "column_schema": [ + { + "name": "ACTION", + "role": "feature", + "semantic_type": "boolean", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 7.6e-05, + "example_values": [ + "1", + "0" + ] + } + }, + { + "name": "RESOURCE", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 6690, + "unique_ratio": 0.255197, + "example_values": [ + "44623", + "74192", + "79092", + "4675", + "37639" + ] + } + }, + { + "name": "MGR_ID", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": 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"semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 442, + "unique_ratio": 0.016861, + "example_values": [ + "117912", + "119092", + "81476", + "119223", + "117941" + ] + } + }, + { + "name": "ROLE_TITLE", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 334, + "unique_ratio": 0.012741, + "example_values": [ + "118568", + "122849", + "118054", + "119962", + "117885" + ] + } + }, + { + "name": "ROLE_FAMILY_DESC", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2205, + "unique_ratio": 0.084112, + "example_values": [ + "198040", + "119094", + "120238", + "168365", + "117913" + ] + } + }, + { + "name": "ROLE_FAMILY", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 67, + "unique_ratio": 0.002556, + "example_values": [ + "19721", + "119095", + "117887", + "118205", + "270488" + ] + } + }, + { + "name": "ROLE_CODE", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 334, + "unique_ratio": 0.012741, + "example_values": [ + "118570", + "122850", + "118055", + "119964", + "117888" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/runtime_result.json b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/runtime_result.json new file mode 100644 index 0000000000000000000000000000000000000000..2b9065e2183e6c614628a3b69d33c4d68a95bc2a --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/runtime_result.json @@ -0,0 +1,14 @@ +{ + "dataset_id": "c9", + "model": "arf", + "run_id": "arf-c9-20260321_065512", + "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/c9/arf/arf-c9-20260321_065512/arf-c9-26215-20260330_065333.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/arf/adapter_report.json b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/arf/adapter_report.json new file mode 100644 index 0000000000000000000000000000000000000000..d75144fa123dbd807ed030d7e59289b2842a8cea --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/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/c9/arf/arf-c9-20260321_065512/staged/arf/model_input_manifest.json" +} \ No newline at end of file diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/arf/adapter_transforms_applied.json b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/arf/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/arf/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/arf/model_input_manifest.json 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file diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/public/staged_features.json b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..064e282246cf4cc51cf3ff555412bcc338835074 --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/public/staged_features.json @@ -0,0 +1,52 @@ +[ + { + "feature_name": "ACTION", + "data_type": "binary", + "is_target": false + }, + { + "feature_name": "RESOURCE", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "MGR_ID", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_ROLLUP_1", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_ROLLUP_2", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_DEPTNAME", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_TITLE", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_FAMILY_DESC", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_FAMILY", + "data_type": "continuous", + "is_target": true + }, + { + "feature_name": "ROLE_CODE", + "data_type": "continuous", + "is_target": false + } +] \ No newline at end of file diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/public/test.csv b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..b75a5d8c2fcb2f79081b7dbe7668099098496842 --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0af6e0312230bd2e171907bf4a9604e4b600e6335c3e4b4842b1f60c8e7260c7 +size 203927 diff --git a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/staged/public/train.csv 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a/syntheticSuccess/c9/arf/arf-c9-20260321_065512/train_20260321_065512.log b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/train_20260321_065512.log new file mode 100644 index 0000000000000000000000000000000000000000..854c98a5b26383cc5dbcb3fcf7c4d7bff4a5e474 --- /dev/null +++ b/syntheticSuccess/c9/arf/arf-c9-20260321_065512/train_20260321_065512.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:62bb76e362bf6d6444ebc0606d095e7d9a426dd7c70644ff86a101fb81c96570 +size 350 diff --git a/syntheticSuccess/c9/bayesnet/bayesnet-c9-20260321_062102/_bayesnet_generate.py b/syntheticSuccess/c9/bayesnet/bayesnet-c9-20260321_062102/_bayesnet_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..16f6a4ece5503160eab702231bb776d10e06c026 --- /dev/null +++ b/syntheticSuccess/c9/bayesnet/bayesnet-c9-20260321_062102/_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/c9/bayesnet/bayesnet-c9-20260321_062102/bayesnet_model.pkl", "rb") as f: + plugin = pickle.load(f) +syn = plugin.generate(count=26215).dataframe() + +# Restore zero-variance columns that were dropped during training +const_path = "/work/output-SpecializedModels/c9/bayesnet/bayesnet-c9-20260321_062102/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/c9/bayesnet/bayesnet-c9-20260321_062102/bayesnet-c9-26215-20260330_065334.csv", index=False) +print(f"[BayesNet] Generated 26215 rows -> /work/output-SpecializedModels/c9/bayesnet/bayesnet-c9-20260321_062102/bayesnet-c9-26215-20260330_065334.csv") diff --git a/syntheticSuccess/c9/bayesnet/bayesnet-c9-20260321_062102/_bayesnet_train.py b/syntheticSuccess/c9/bayesnet/bayesnet-c9-20260321_062102/_bayesnet_train.py new file mode 100644 index 0000000000000000000000000000000000000000..7703ea3d3908eb2a7ad41395a60a8a4d3011c2cf --- /dev/null +++ b/syntheticSuccess/c9/bayesnet/bayesnet-c9-20260321_062102/_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/c9/bayesnet/bayesnet-c9-20260321_062102/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/c9/bayesnet/bayesnet-c9-20260321_062102/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/c9/bayesnet/bayesnet-c9-20260321_062102/bayesnet_model.pkl", "wb") as f: + pickle.dump(plugin, f) +print(f"[BayesNet] Model saved -> /work/output-SpecializedModels/c9/bayesnet/bayesnet-c9-20260321_062102/bayesnet_model.pkl") diff --git a/syntheticSuccess/c9/bayesnet/bayesnet-c9-20260321_062102/bayesnet-c9-1000-20260321_062232.csv b/syntheticSuccess/c9/bayesnet/bayesnet-c9-20260321_062102/bayesnet-c9-1000-20260321_062232.csv new file mode 100644 index 0000000000000000000000000000000000000000..5b83260afa1ca30fb7d611e60771b1d987f28967 --- /dev/null +++ b/syntheticSuccess/c9/bayesnet/bayesnet-c9-20260321_062102/bayesnet-c9-1000-20260321_062232.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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"/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/realtabformer/rtf-c9-20260328_165229/staged/realtabformer/model_input_manifest.json" +} \ No newline at end of file diff --git a/syntheticSuccess/c9/realtabformer/rtf-c9-20260328_165229/staged/realtabformer/adapter_transforms_applied.json b/syntheticSuccess/c9/realtabformer/rtf-c9-20260328_165229/staged/realtabformer/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/c9/realtabformer/rtf-c9-20260328_165229/staged/realtabformer/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/c9/realtabformer/rtf-c9-20260328_165229/staged/realtabformer/model_input_manifest.json b/syntheticSuccess/c9/realtabformer/rtf-c9-20260328_165229/staged/realtabformer/model_input_manifest.json new file mode 100644 index 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], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/realtabformer/rtf-c9-20260328_165229/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/realtabformer/rtf-c9-20260328_165229/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/realtabformer/rtf-c9-20260328_165229/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/realtabformer/rtf-c9-20260328_165229/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/realtabformer/rtf-c9-20260328_165229/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/realtabformer/rtf-c9-20260328_165229/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/c9/realtabformer/rtf-c9-20260328_165229/train_20260328_165230.log b/syntheticSuccess/c9/realtabformer/rtf-c9-20260328_165229/train_20260328_165230.log new file mode 100644 index 0000000000000000000000000000000000000000..3b400229066dae3477268307223ca4bf6f52ab51 --- /dev/null +++ b/syntheticSuccess/c9/realtabformer/rtf-c9-20260328_165229/train_20260328_165230.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0afe523df3798052097a99adc8bee317bdf87cb888db54b565af5a1c7db4cd4c +size 5959300 diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/_tabddpm_sample.py b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/_tabddpm_sample.py new file mode 100644 index 0000000000000000000000000000000000000000..7be9c0cf59731e52f79894a9dac1988c0a7e607d --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/_tabddpm_sample.py @@ -0,0 +1,67 @@ +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 26215 rows") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506/config_sample_20260422_212735.toml", + "--sample"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) + +# 将 .npy 输出转为 CSV +work_dir = "/work/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506" +info_path = os.path.join(work_dir, "data", "info.json") +with open(info_path) as f: + info = json.load(f) + +output_dir = os.path.join(work_dir, "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/c9/tabddpm/tabddpm-c9-20260422_212506/tabddpm-c9-26215-20260422_212735.csv", index=False) + print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506/tabddpm-c9-26215-20260422_212735.csv") +else: + print("[TabDDPM] WARNING: No output .npy files found") + sys.exit(1) diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/_tabddpm_train.py b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/_tabddpm_train.py new file mode 100644 index 0000000000000000000000000000000000000000..35c3949a832da2f0020c5c77df8872e7bfa6d713 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/_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/c9/tabddpm/tabddpm-c9-20260422_212506/config.toml") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506/config.toml", + "--train"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print("[TabDDPM] Training complete") diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/config.toml b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/config.toml new file mode 100644 index 0000000000000000000000000000000000000000..5105d3cbfe2207c256b91f935f76d4b9312d4acb --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/config.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506/output" +real_data_path = "/work/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506/data" +model_type = "mlp" +num_numerical_features = 8 +device = "cuda:0" + +[model_params] +d_in = 9 +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/c9/tabddpm/tabddpm-c9-20260422_212506/config_sample_20260422_212735.toml b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/config_sample_20260422_212735.toml new file mode 100644 index 0000000000000000000000000000000000000000..8e3d33fc2d9f3f7c9f3c4462011b97e0f2876a65 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/config_sample_20260422_212735.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506/output" +real_data_path = "/work/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506/data" +model_type = "mlp" +num_numerical_features = 8 +device = "cuda:0" + +[model_params] +d_in = 9 +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 = 26215 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/data/X_cat_train.npy b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/data/X_cat_train.npy new file mode 100644 index 0000000000000000000000000000000000000000..f0ec67badf0b2e80017aaf0dea889cbf3cfe1aa0 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/data/X_cat_train.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7d76b75f989b3dc29e9c1776971bfcfe6782477af9b30d143474c2e7c6d296c5 +size 209848 diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/data/X_num_train.npy b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/data/X_num_train.npy new file mode 100644 index 0000000000000000000000000000000000000000..24431e7de42e064269a838b520596da288413946 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/data/X_num_train.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4a6bc53b6dfcd4e17d7f1d3c01d3897f13d7871d3734a5514501dca11a68ad6b +size 839008 diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/data/info.json b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/data/info.json new file mode 100644 index 0000000000000000000000000000000000000000..0e4bff8b9bdff38a0bc7c56fd688382ce110cb75 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/data/info.json @@ -0,0 +1,35 @@ +{ + "name": "benchmark_dataset", + "task_type": "regression", + "n_num_features": 8, + "n_cat_features": 1, + "train_size": 26215, + "num_col_idx": [ + 0, + 1, + 2, + 3, + 4, + 5, + 6, + 7 + ], + "cat_col_idx": [ + 8 + ], + "target_col_idx": [ + 9 + ], + "column_names": [ + "RESOURCE", + "MGR_ID", + "ROLE_ROLLUP_1", + "ROLE_ROLLUP_2", + "ROLE_DEPTNAME", + "ROLE_TITLE", + "ROLE_FAMILY_DESC", + "ROLE_CODE", + "ACTION", + "ROLE_FAMILY" + ] +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/data/y_train.npy b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/data/y_train.npy new file mode 100644 index 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b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..f853d8d8fdb51c5055ed5ab99460ca3d76ed7274 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "c9", + "model": "tabddpm", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-train.csv", + "exists": true, + "size": 1656550, + "sha256": "7fe9e4b6e2719c346fd93c7ada4977430d0c593cc5bdae7442a78886f7b71b9e" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-val.csv", + "exists": true, + "size": 207139, + "sha256": "01557a0b4304c4b5435df0909d16016ec0ba4ce2c3b31a8815f813ef1376b0b9" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-test.csv", + "exists": true, + "size": 207206, + "sha256": "6de1346ef61646cbd096588223a049bf26f2b26229ac65b2734fed139f3c06bb" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c9/c9-dataset_profile.json", + "exists": true, + "size": 4540, + "sha256": "536d3ace5469df116ca00b7544ee8af409fc29edb7e85f365e465a91244a564e" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c9/c9-dataset_contract_v1.json", + "exists": true, + "size": 5389, + "sha256": "d63ab9aee52c7f931f14b7ad2c9a601b670ba5cd739494b2c4d2e4005430ea6d" + } + } +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/X_cat_train.npy b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/X_cat_train.npy new file mode 100644 index 0000000000000000000000000000000000000000..3d94b61030d43c5b23367e79dcf3a8a48b09fa73 --- /dev/null +++ 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b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/config.toml new file mode 100644 index 0000000000000000000000000000000000000000..8e3d33fc2d9f3f7c9f3c4462011b97e0f2876a65 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/config.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506/output" +real_data_path = "/work/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506/data" +model_type = "mlp" +num_numerical_features = 8 +device = "cuda:0" + +[model_params] +d_in = 9 +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 = 26215 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/info.json b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/info.json new file mode 100644 index 0000000000000000000000000000000000000000..0e4bff8b9bdff38a0bc7c56fd688382ce110cb75 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/info.json @@ -0,0 +1,35 @@ +{ + "name": "benchmark_dataset", + "task_type": "regression", + "n_num_features": 8, + "n_cat_features": 1, + "train_size": 26215, + "num_col_idx": [ + 0, + 1, + 2, + 3, + 4, + 5, + 6, + 7 + ], + "cat_col_idx": [ + 8 + ], + "target_col_idx": [ + 9 + ], + "column_names": [ + "RESOURCE", + "MGR_ID", + "ROLE_ROLLUP_1", + "ROLE_ROLLUP_2", + "ROLE_DEPTNAME", + "ROLE_TITLE", + "ROLE_FAMILY_DESC", + "ROLE_CODE", + "ACTION", + "ROLE_FAMILY" + ] +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/loss.csv b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/loss.csv new file mode 100644 index 0000000000000000000000000000000000000000..6e9df1ce88c0c1d84153bc78b88ddf8dd6ebe139 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/loss.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4686160a7a8db048a490f6de7490b20990ef277f0f2a1cd3e1f96ba0bd3a474c +size 1470 diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/model.pt b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/model.pt new file mode 100644 index 0000000000000000000000000000000000000000..681bb6c5b902b2541778952987ff56d1f5c56ef9 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/output/model.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5f333d52c014cbd9a1fb5bb5353430153a0ca918ac2dc7637d8139924e2e9feb +size 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sha256:37fbbf0bdf79fe232c9efdfe85001e4b1e3595f35e5e3cc96f164d0ef8452e3b +size 209848 diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/public_gate/normalized_schema_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..7ba372afdc8d9d80b5b9ad0413ddec90a8353e37 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,214 @@ +{ + "dataset_id": "c9", + "target_column": "ROLE_FAMILY", + "task_type": "regression", + "columns": [ + { + "name": "ACTION", + "role": "feature", + "semantic_type": "boolean", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 7.6e-05, + "example_values": [ + "1", + "0" + ] + } + }, + { + "name": "RESOURCE", + "role": 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"117961", + "118595", + "118200", + "117978" + ] + } + }, + { + "name": "ROLE_ROLLUP_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 174, + "unique_ratio": 0.006637, + "example_values": [ + "117911", + "118225", + "118596", + "117962", + "118201" + ] + } + }, + { + "name": "ROLE_DEPTNAME", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 442, + "unique_ratio": 0.016861, + "example_values": [ + "117912", + "119092", + "81476", + "119223", + "117941" + ] + } + }, + { + "name": "ROLE_TITLE", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + 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"features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/tabddpm/tabddpm-c9-20260422_212506/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/tabddpm-c9-26215-20260422_212735.csv b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/tabddpm-c9-26215-20260422_212735.csv new file mode 100644 index 0000000000000000000000000000000000000000..d26f79d4842a8082c8c6d98df99c1cb82dcae88e --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/tabddpm-c9-26215-20260422_212735.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:44c6ba4d2fa21c02db3dd0d19622868ce764816a09e0230fce4d5205de9996d7 +size 1860610 diff --git a/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/train_20260422_212507.log b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/train_20260422_212507.log new file mode 100644 index 0000000000000000000000000000000000000000..bbd290196f8117db196224cde60a5c4bd002b095 --- /dev/null +++ b/syntheticSuccess/c9/tabddpm/tabddpm-c9-20260422_212506/train_20260422_212507.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:186c55c87d6036622c9dd7faa4abb86774587b439834ca9b9d80af1091a77683 +size 8869 diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/_tabpfgen_generate.py b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/_tabpfgen_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..84fd3db3609ea1e153350e5eca9b839ad6487ffd --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-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/c9/staged/public/train.csv") +target_col = "ROLE_FAMILY" + +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(26215) + +# 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/c9/tabpfgen-c9-26215-20260422_191741.csv", index=False) +print(f"[TabPFGen] Saved {len(syn_df)} rows -> /work/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c9/tabpfgen-c9-26215-20260422_191741.csv") diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/gen_20260422_191741.log b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/gen_20260422_191741.log new file mode 100644 index 0000000000000000000000000000000000000000..a74f7cd073c8873a7a349bc823c16e99c96770bd --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/gen_20260422_191741.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dbdc6e320af7f6504608624bd6af4d875a79e1c7ddbd151493ea8fc0603e9bfc +size 529 diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/input_snapshot.json b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..49986820ad5d7c4aeafdcd6c8196c6abff98dca6 --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "c9", + "model": "tabpfgen", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-train.csv", + "exists": true, + "size": 1656550, + "sha256": "7fe9e4b6e2719c346fd93c7ada4977430d0c593cc5bdae7442a78886f7b71b9e" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-val.csv", + "exists": true, + "size": 207139, + "sha256": "01557a0b4304c4b5435df0909d16016ec0ba4ce2c3b31a8815f813ef1376b0b9" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-test.csv", + "exists": true, + "size": 207206, + "sha256": "6de1346ef61646cbd096588223a049bf26f2b26229ac65b2734fed139f3c06bb" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c9/c9-dataset_profile.json", + "exists": true, + "size": 4540, + "sha256": "536d3ace5469df116ca00b7544ee8af409fc29edb7e85f365e465a91244a564e" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c9/c9-dataset_contract_v1.json", + "exists": true, + "size": 5389, + "sha256": "d63ab9aee52c7f931f14b7ad2c9a601b670ba5cd739494b2c4d2e4005430ea6d" + } + } +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/public_gate/normalized_schema_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..7ba372afdc8d9d80b5b9ad0413ddec90a8353e37 --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,214 @@ +{ + "dataset_id": "c9", + "target_column": "ROLE_FAMILY", + "task_type": "regression", + "columns": [ + { + "name": "ACTION", + "role": "feature", + "semantic_type": "boolean", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 7.6e-05, + "example_values": [ + "1", + "0" + ] + } + }, + { + "name": "RESOURCE", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 6690, + "unique_ratio": 0.255197, + "example_values": [ + "44623", + "74192", + "79092", + "4675", + "37639" + ] + } + }, + { + "name": "MGR_ID", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4052, + "unique_ratio": 0.154568, + "example_values": [ + "67326", + "16850", + "5223", + "14952", + "88170" + ] + } + }, + { + "name": "ROLE_ROLLUP_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 126, + "unique_ratio": 0.004806, + "example_values": [ + "117910", + "117961", + "118595", + "118200", + "117978" + ] + } + }, + { + "name": "ROLE_ROLLUP_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 174, + "unique_ratio": 0.006637, + "example_values": [ + "117911", + "118225", + "118596", + "117962", + "118201" + ] + } + }, + { + "name": "ROLE_DEPTNAME", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 442, + "unique_ratio": 0.016861, + "example_values": [ + "117912", + "119092", + "81476", + "119223", + "117941" + ] + } + }, + { + "name": "ROLE_TITLE", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 334, + "unique_ratio": 0.012741, + "example_values": [ + "118568", + "122849", + "118054", + "119962", + "117885" + ] + } + }, + { + "name": "ROLE_FAMILY_DESC", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 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b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/public_gate/public_gate_report.json new file mode 100644 index 0000000000000000000000000000000000000000..812ee0cc580ee3523d798fa725ff691876b7f855 --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/public_gate/public_gate_report.json @@ -0,0 +1,37 @@ +{ + "dataset_id": "c9", + "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": "ROLE_FAMILY", + "task_type": "regression", + "input_splits": { + "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-train.csv", + "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-val.csv", + "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-test.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/public_gate/staged_input_manifest.json b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/public_gate/staged_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..95641be9c7b91220e5d43c1eb9541ddd3a6a3bab --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/public_gate/staged_input_manifest.json @@ -0,0 +1,219 @@ +{ + "dataset_id": "c9", + "target_column": "ROLE_FAMILY", + "task_type": "regression", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c9/staged/public/train.csv", + "val_csv": 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+ "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 6690, + "unique_ratio": 0.255197, + "example_values": [ + "44623", + "74192", + "79092", + "4675", + "37639" + ] + } + }, + { + "name": "MGR_ID", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 4052, + "unique_ratio": 0.154568, + "example_values": [ + "67326", + "16850", + "5223", + "14952", + "88170" + ] + } + }, + { + "name": "ROLE_ROLLUP_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 126, + "unique_ratio": 0.004806, + "example_values": [ + "117910", + "117961", + "118595", + "118200", + "117978" + ] + } + }, + { + "name": "ROLE_ROLLUP_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 174, + "unique_ratio": 0.006637, + "example_values": [ + "117911", + "118225", + "118596", + "117962", + "118201" + ] + } + }, + { + "name": "ROLE_DEPTNAME", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 442, + "unique_ratio": 0.016861, + "example_values": [ + "117912", + "119092", + "81476", + "119223", + "117941" + ] + } + }, + { + "name": "ROLE_TITLE", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 334, 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"parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 334, + "unique_ratio": 0.012741, + "example_values": [ + "118570", + "122850", + "118055", + "119964", + "117888" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/runner.log b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/runner.log new file mode 100644 index 0000000000000000000000000000000000000000..fe7e1987886b2a9f5f0dec9cec1a690e1c00707d --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/runner.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2a2e21574d070acd948713d7311f85132c825d2e613a5768c866118c738bbaab +size 1359 diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/runtime_result.json b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/runtime_result.json new file mode 100644 index 0000000000000000000000000000000000000000..7efa77e39371e1a795eb5cca1869825e5d9a8077 --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/runtime_result.json @@ -0,0 +1,14 @@ +{ + "dataset_id": "c9", + "model": "tabpfgen", + "run_id": "c9-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/c9/tabpfgen/c9-migrated-20260422_193053/tabpfgen-c9-26215-20260422_191741.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/public/staged_features.json b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..064e282246cf4cc51cf3ff555412bcc338835074 --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/public/staged_features.json @@ -0,0 +1,52 @@ +[ + { + "feature_name": "ACTION", + "data_type": "binary", + "is_target": false + }, + { + "feature_name": "RESOURCE", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "MGR_ID", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_ROLLUP_1", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_ROLLUP_2", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_DEPTNAME", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_TITLE", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_FAMILY_DESC", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "ROLE_FAMILY", + "data_type": "continuous", + "is_target": true + }, + { + "feature_name": "ROLE_CODE", + "data_type": "continuous", + "is_target": false + } +] \ No newline at end of file diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/public/test.csv b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..b75a5d8c2fcb2f79081b7dbe7668099098496842 --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:0af6e0312230bd2e171907bf4a9604e4b600e6335c3e4b4842b1f60c8e7260c7 +size 203927 diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/public/train.csv b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/public/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..581832d2d577538d2b98026d4705fa0495b803b7 --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/public/train.csv @@ -0,0 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+++ b/syntheticSuccess/c9/tabpfgen/c9-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/c9/staged/tabpfgen/model_input_manifest.json" +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/tabpfgen/adapter_transforms_applied.json b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/tabpfgen/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/tabpfgen/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/tabpfgen/model_input_manifest.json b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/tabpfgen/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..df2a7b3608c21cc9b802235eec218d8ce5e9af78 --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/staged/tabpfgen/model_input_manifest.json @@ -0,0 +1,221 @@ +{ + "dataset_id": "c9", + "model": "tabpfgen", + "target_column": "ROLE_FAMILY", + "task_type": "regression", + "column_schema": [ + { + "name": "ACTION", + "role": "feature", + "semantic_type": "boolean", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "mode", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 7.6e-05, + "example_values": [ + "1", + "0" + ] + } + }, + { + "name": "RESOURCE", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + 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"impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 334, + "unique_ratio": 0.012741, + "example_values": [ + "118570", + "122850", + "118055", + "119964", + "117888" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c9/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c9/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c9/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c9/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c9/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c9/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/tabpfgen-c9-26215-20260422_191741.csv b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/tabpfgen-c9-26215-20260422_191741.csv new file mode 100644 index 0000000000000000000000000000000000000000..399c78668a6b4e6ed60f1fbcea97ad3fecbf7087 --- /dev/null +++ b/syntheticSuccess/c9/tabpfgen/c9-migrated-20260422_193053/tabpfgen-c9-26215-20260422_191741.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4addee3c8363696da8c81a0519cf6fa269a180bfd6113a191f97782475c15d6e +size 2849877 diff --git a/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/_tabsyn_sample.py b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/_tabsyn_sample.py new file mode 100644 index 0000000000000000000000000000000000000000..d8603cf023852c46a355a89ab08a4f0b23441065 --- /dev/null +++ b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/_tabsyn_sample.py @@ -0,0 +1,39 @@ +import os, sys, subprocess + +work_dir = "/work/output-SpecializedModels/c9/tabsyn/tabsyn-c9-20260420_233446" +dataname = "tabsyn_c9" +output_csv = "/work/output-SpecializedModels/c9/tabsyn/tabsyn-c9-20260420_233446/tabsyn-c9-26215-20260421_005001.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 26215 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/c9/tabsyn/tabsyn-c9-20260420_233446/_tabsyn_train.py b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/_tabsyn_train.py new file mode 100644 index 0000000000000000000000000000000000000000..f4c5213eff8c0fb1101f21e2f0bfaf84408d6ed1 --- /dev/null +++ b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/_tabsyn_train.py @@ -0,0 +1,62 @@ +import os, sys, subprocess + +work_dir = "/work/output-SpecializedModels/c9/tabsyn/tabsyn-c9-20260420_233446" +dataname = "tabsyn_c9" +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") +_te = None +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/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_cat_test.npy b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_cat_test.npy new file mode 100644 index 0000000000000000000000000000000000000000..23fa02f121132f3d12e3307f1e8418e92cc74902 --- /dev/null +++ b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_cat_test.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f4806578182f915d61917361708a4e1938fec8edfcf7da4ab44dd663d31eea03 +size 26352 diff --git a/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_cat_train.npy b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_cat_train.npy new file mode 100644 index 0000000000000000000000000000000000000000..095892aac58d4c469257deaec5808755dd0683ff --- /dev/null +++ b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_cat_train.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1b94e86372b14e60e0b69ab2d78ae87ba27f327d6851047c84a76b18ad32cad5 +size 236056 diff --git a/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_num_test.npy b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_num_test.npy new file mode 100644 index 0000000000000000000000000000000000000000..952fc2549a5139cf4327c36e8b5de413b64ba620 --- /dev/null +++ b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_num_test.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4429f0d335d4329172f9c047ea82fc7abf310e9b6f3a5df0644de5253f6851b9 +size 105024 diff --git a/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_num_train.npy b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_num_train.npy new file mode 100644 index 0000000000000000000000000000000000000000..faad6909fbb7a0786a7443da04281d89abc3eeae --- /dev/null +++ b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/data/tabsyn_c9/X_num_train.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:aaced143d7ea359728f66acd91370eb127f0a2e9e1c5593687842030a7c818bb +size 943840 diff 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"/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/tabsyn/tabsyn-c9-20260420_233446/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/tabsyn/tabsyn-c9-20260420_233446/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/tabsyn/tabsyn-c9-20260420_233446/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/tabsyn/tabsyn-c9-20260420_233446/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/tabsyn/tabsyn-c9-20260420_233446/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c9/tabsyn/tabsyn-c9-20260420_233446/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/synthetic/tabsyn_c9/real.csv b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/synthetic/tabsyn_c9/real.csv new file mode 100644 index 0000000000000000000000000000000000000000..7091f6100ece09bb7d975403123559615930c9d0 --- /dev/null +++ b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/synthetic/tabsyn_c9/real.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f03702afb4bac08768d4f0d85a7fe61f9dcf77f7c69bce143c43560afc4ca4cc +size 1834081 diff --git a/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/synthetic/tabsyn_c9/test.csv b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/synthetic/tabsyn_c9/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..790952364d17365a50dd52465134e49053c33aab --- /dev/null +++ b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/synthetic/tabsyn_c9/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ad285a89dccb63f02c42547c417108a41d1d038ce7442dcf649814a642178fc4 +size 203927 diff --git a/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/tabsyn-c9-26215-20260421_005001.csv b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/tabsyn-c9-26215-20260421_005001.csv new file mode 100644 index 0000000000000000000000000000000000000000..aa7a92dda7ed84e1ab5116a27109deacd06d3490 --- /dev/null +++ b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/tabsyn-c9-26215-20260421_005001.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ec26f720bb9f4bb9d606434649ad7dc1d6f51e5c083b8d1517683f7f4fc5f7fa +size 2501609 diff --git a/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/train_20260420_233447.log b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/train_20260420_233447.log new file mode 100644 index 0000000000000000000000000000000000000000..768afdad54c6fca1e528253d4b90c007fd957d28 --- /dev/null +++ b/syntheticSuccess/c9/tabsyn/tabsyn-c9-20260420_233446/train_20260420_233447.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:631a4c392a91d017cb64d6a994690b9cce5cb5295a578593e27fabbf8ed6b398 +size 2929396 diff --git a/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/_tvae_generate.py b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/_tvae_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..9a76b331a1931cce847be2de87ae0c006e5bc91e --- /dev/null +++ b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/_tvae_generate.py @@ -0,0 +1,5 @@ +from ctgan.synthesizers.tvae import TVAE +model = TVAE.load("/work/output-SpecializedModels/c9/tvae/tvae-c9-20260321_071540/models_300epochs/tvae_300epochs.pt") +samples = model.sample(26215) +samples.to_csv("/work/output-SpecializedModels/c9/tvae/tvae-c9-20260321_071540/tvae-c9-26215-20260330_065330.csv", index=False) +print(f"[TVAE] Generated 26215 rows -> /work/output-SpecializedModels/c9/tvae/tvae-c9-20260321_071540/tvae-c9-26215-20260330_065330.csv") diff --git a/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/_tvae_train.py b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/_tvae_train.py new file mode 100644 index 0000000000000000000000000000000000000000..a10500dd03b0831b345a5c5d08162f87f72a443e --- /dev/null +++ b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/_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/c9/tvae/tvae-c9-20260321_071540/staged/public/train.csv" +meta_path = "/work/output-SpecializedModels/c9/tvae/tvae-c9-20260321_071540/tvae_metadata.json" +save_path = "/work/output-SpecializedModels/c9/tvae/tvae-c9-20260321_071540/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/c9/tvae/tvae-c9-20260321_071540/gen_20260321_072347.log b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/gen_20260321_072347.log new file mode 100644 index 0000000000000000000000000000000000000000..5a6cfbee6814c9beeda36cc1e0fb860a30a44176 --- /dev/null +++ b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/gen_20260321_072347.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:480c10a55d835b38212f2f7a35004370a0b30b78ef13fde89db2728ce82f7999 +size 126 diff --git a/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/gen_20260330_065330.log b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/gen_20260330_065330.log new file mode 100644 index 0000000000000000000000000000000000000000..94a2a346217ced309b8d39fd0b168bd6c436ac45 --- /dev/null +++ b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/gen_20260330_065330.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:9b17259b47f831775b733733cee0d0c8b4c6b04d7dc053b523a2435554a47d4c +size 128 diff --git a/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/input_snapshot.json b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..4b840191e9b8313d6f1e3b98f6b741e51fa15753 --- /dev/null +++ b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "c9", + "model": "tvae", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-train.csv", + "exists": true, + "size": 1656550, + "sha256": "7fe9e4b6e2719c346fd93c7ada4977430d0c593cc5bdae7442a78886f7b71b9e" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-val.csv", + "exists": true, + "size": 207139, + "sha256": "01557a0b4304c4b5435df0909d16016ec0ba4ce2c3b31a8815f813ef1376b0b9" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c9/c9-test.csv", + "exists": true, + "size": 207206, + "sha256": "6de1346ef61646cbd096588223a049bf26f2b26229ac65b2734fed139f3c06bb" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c9/c9-dataset_profile.json", + "exists": true, + "size": 4540, + "sha256": "536d3ace5469df116ca00b7544ee8af409fc29edb7e85f365e465a91244a564e" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c9/c9-dataset_contract_v1.json", + "exists": true, + "size": 5389, + "sha256": "d63ab9aee52c7f931f14b7ad2c9a601b670ba5cd739494b2c4d2e4005430ea6d" + } + } +} \ No newline at end of file diff --git a/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/models_300epochs/train_20260321_071540.log b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/models_300epochs/train_20260321_071540.log new file mode 100644 index 0000000000000000000000000000000000000000..2792d5e9a037c8cccfb86f72dfd7aa9029955b5f --- /dev/null +++ b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/models_300epochs/train_20260321_071540.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2b273316ed594f5dc5499b9c59c077390a8f9ac80cf1f66b7d1f2aed080d6325 +size 171 diff --git a/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/models_300epochs/tvae_300epochs.pt b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/models_300epochs/tvae_300epochs.pt new file mode 100644 index 0000000000000000000000000000000000000000..4140f34182a75d09ee541ea309ed7411b9fee83b --- /dev/null +++ b/syntheticSuccess/c9/tvae/tvae-c9-20260321_071540/models_300epochs/tvae_300epochs.pt @@ -0,0 +1,3 @@ +version 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"example_values": [ + "117910", + "117961", + "118595", + "118200", + "117978" + ] + } + }, + { + "name": "ROLE_ROLLUP_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 174, + "unique_ratio": 0.006637, + "example_values": [ + "117911", + "118225", + "118596", + "117962", + "118201" + ] + } + }, + { + "name": "ROLE_DEPTNAME", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 442, + "unique_ratio": 0.016861, + "example_values": [ + "117912", + "119092", + "81476", + "119223", + "117941" + ] + } + }, + { + "name": "ROLE_TITLE", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + 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