diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/_arf_generate.py b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/_arf_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..a9909da2d8b4afb623ea0e6719092f1ec677f8e7 --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/_arf_generate.py @@ -0,0 +1,6 @@ +import pickle +with open("/work/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/arf_model.pkl", "rb") as f: + model = pickle.load(f) +syn = model.forge(n=196045) +syn.to_csv("/work/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/arf-n12-196045-20260330_070603.csv", index=False) +print(f"[ARF] Generated 196045 rows -> /work/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/arf-n12-196045-20260330_070603.csv") diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/_arf_train.py b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/_arf_train.py new file mode 100644 index 0000000000000000000000000000000000000000..ef76754a1f78140a06eeda9c3d9ba40b9b72c0b7 --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/_arf_train.py @@ -0,0 +1,19 @@ +import pickle +import pandas as pd +from arfpy import arf + +df = pd.read_csv("/work/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/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/n12/arf/arf-n12-20260325_102131/arf_model.pkl", "wb") as f: + pickle.dump(model, f) +print(f"[ARF] Model saved -> /work/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/arf_model.pkl") diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/arf-n12-1000-20260325_104228.csv b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/arf-n12-1000-20260325_104228.csv new file mode 100644 index 0000000000000000000000000000000000000000..04347d028e382e862baf96a42fd8b7c1e9d4ba3b --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/arf-n12-1000-20260325_104228.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ebad5cc48c699369c0b8b75e100452a3cb3d5a202877c8a4b6b32e3575492794 +size 35869 diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/arf-n12-196045-20260330_070603.csv b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/arf-n12-196045-20260330_070603.csv new file mode 100644 index 0000000000000000000000000000000000000000..f0907f1a3983e226a3ecf2d84ef0ee6ff2fbbf4c --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/arf-n12-196045-20260330_070603.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a4804fd94f0e40194dad9e98eb74cac820d46b7191d1a68adfe4ec445068d4ba +size 6997915 diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/arf_model.pkl b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/arf_model.pkl new file mode 100644 index 0000000000000000000000000000000000000000..8def8769e10b59e48cd40b3fd7c182cf0e42dfc5 --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/arf_model.pkl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3e9e53933698a6e015a7fff5f17e54409db0fbca57502dec4591fe582be7b3c5 +size 251337775 diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/gen_20260325_104228.log b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/gen_20260325_104228.log new file mode 100644 index 0000000000000000000000000000000000000000..1b3220c32d468624f8db5ca9edae0d4fb15616a1 --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/gen_20260325_104228.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b764891a0d829ca232fd7188dd4929edf539fe1430c9f77553869f17ef24f53b +size 441 diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/gen_20260330_070603.log b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/gen_20260330_070603.log new file mode 100644 index 0000000000000000000000000000000000000000..8ce9074d70c6823a0e16389ae372a8e3cc1cea85 --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/gen_20260330_070603.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:011e50b0bfd962e233a1368fe3248e952621f331b370841dc992f7ff5abe1df3 +size 445 diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/input_snapshot.json b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..3ad2dc8fd64cffbf0eeb6e2a8f69ae298297ffe0 --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n12", + "model": "arf", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-train.csv", + "exists": true, + "size": 2720466, + "sha256": "4c3e44750c769fb56cd6224e07240585091e57a4786f4bbd4b914826fe9eedb2" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-val.csv", + "exists": true, + "size": 340170, + "sha256": "761692b00c3ad9e4f07dd51f386f4d42ab2b68ed91f741cd850981f7f5b58fd5" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-test.csv", + "exists": true, + "size": 340296, + "sha256": "6531e89976491f6fb7d02635a2e934e058c1bb15faaf5debc7052fbe5d0b8b81" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n12/n12-dataset_profile.json", + "exists": true, + "size": 2302, + "sha256": "d4fe8e20de077a2855d2af5dd1e73126e04bf2a0741e28ff80368983f126319b" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n12/n12-dataset_contract_v1.json", + "exists": true, + "size": 2472, + "sha256": "856639afabf103741f49f84eac0546ba3f4f3d2258fa3016263682d164e78a7a" + } + } +} \ No newline at end of file diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/public_gate/normalized_schema_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..de9552b7c09c03f3ffefc32913ed80e6aa0d5dee --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,88 @@ +{ + "dataset_id": "n12", + "target_column": "target", + "task_type": "classification", + "columns": [ + { + "name": "feature_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "74", + "14", + "115", + "130", + "5" + ] + } + }, + { + "name": "feature_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "85", + "5", + "116", + "169", + "4" + ] + } + }, + { + "name": "feature_3", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "123", + "186", + "60", + "221", + "0" + ] + } + }, + { + "name": "target", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 1e-05, + "example_values": [ + "1", + "2" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/public_gate/public_gate_report.json b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/public_gate/public_gate_report.json new file mode 100644 index 0000000000000000000000000000000000000000..956c216ac51e3ac3d437939ae2c2be86873cf48b --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/public_gate/public_gate_report.json @@ -0,0 +1,37 @@ +{ + "dataset_id": "n12", + "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": "target", + "task_type": "classification", + "input_splits": { + "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-train.csv", + "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-val.csv", + "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-test.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/public_gate/staged_input_manifest.json b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/public_gate/staged_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..54d76e602c0ba1ae7d3c0fbdc8a5536c051fc4b9 --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/public_gate/staged_input_manifest.json @@ -0,0 +1,93 @@ +{ + "dataset_id": "n12", + "target_column": "target", + "task_type": "classification", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/public_gate/public_gate_report.json", + "column_schema": [ + { + "name": "feature_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "74", + "14", + "115", + "130", + "5" + ] + } + }, + { + "name": "feature_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "85", + "5", + "116", + "169", + "4" + ] + } + }, + { + "name": "feature_3", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "123", + "186", + "60", + "221", + "0" + ] + } + }, + { + "name": "target", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 1e-05, + "example_values": [ + "1", + "2" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/runtime_result.json b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/runtime_result.json new file mode 100644 index 0000000000000000000000000000000000000000..2301766071a533cf5acb2386e91042581d7d1f3e --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/runtime_result.json @@ -0,0 +1,14 @@ +{ + "dataset_id": "n12", + "model": "arf", + "run_id": "arf-n12-20260325_102131", + "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/n12/arf/arf-n12-20260325_102131/arf-n12-196045-20260330_070603.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/arf/adapter_report.json b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/arf/adapter_report.json new file mode 100644 index 0000000000000000000000000000000000000000..bbfd257d09cbd570a492bb99501f938464be69da --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/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/n12/arf/arf-n12-20260325_102131/staged/arf/model_input_manifest.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/arf/adapter_transforms_applied.json b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/arf/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/arf/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/arf/model_input_manifest.json b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/arf/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..f675fcb5e150c9e4c5903dd906bb42ead310493d --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/arf/model_input_manifest.json @@ -0,0 +1,95 @@ +{ + "dataset_id": "n12", + "model": "arf", + "target_column": "target", + "task_type": "classification", + "column_schema": [ + { + "name": "feature_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "74", + "14", + "115", + "130", + "5" + ] + } + }, + { + "name": "feature_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "85", + "5", + "116", + "169", + "4" + ] + } + }, + { + "name": "feature_3", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "123", + "186", + "60", + "221", + "0" + ] + } + }, + { + "name": "target", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 1e-05, + "example_values": [ + "1", + "2" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/arf/arf-n12-20260325_102131/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/staged_features.json b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..d439c0620c179a5a439add22d2a218d42f9ca5d4 --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/staged_features.json @@ -0,0 +1,22 @@ +[ + { + "feature_name": "feature_1", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "feature_2", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "feature_3", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "target", + "data_type": "continuous", + "is_target": true + } +] \ No newline at end of file diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/test.csv b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..337e8e477426cd837a2169731ff6ef5025d06f36 --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4972eb2812d325c143ec99492afa470fe047141a9bdf34893ec0133a12b8dc26 +size 315789 diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/train.csv b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..023dad2054b44ff77ffcf6f4554ad423242e80c2 --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/train.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:728fec9c0ec06ca4b292989614be4374c308d9a15b1e0002c3daeb3a68d5d350 +size 2524420 diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/val.csv b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/val.csv new file mode 100644 index 0000000000000000000000000000000000000000..8dc60d3ec85d7e82382b2245a4ce835645e4a714 --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/staged/public/val.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8931c0b2402466ccca41868fc484ab4bc6f627d68422570b20d47d1104922959 +size 315663 diff --git a/syntheticSuccess/n12/arf/arf-n12-20260325_102131/train_20260325_102132.log b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/train_20260325_102132.log new file mode 100644 index 0000000000000000000000000000000000000000..d1a9c06dbdcceeeaaf9a06eec7413d13193e16fc --- /dev/null +++ b/syntheticSuccess/n12/arf/arf-n12-20260325_102131/train_20260325_102132.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7bc1fb41696be8aa62994b536f132020be7e811b9ef127e1e6dcdaf090dd62bc +size 506 diff --git a/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/_bayesnet_generate.py b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/_bayesnet_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..c84a7846bc3878087c2e09243ab71645df70e6ed --- /dev/null +++ b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/_bayesnet_generate.py @@ -0,0 +1,104 @@ + +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-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/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(196045) +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.to_csv("/work/output-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet-n12-196045-20260422_060234.csv", index=False) +print(f"[BayesNet] Generated {len(final)} rows (requested {num_rows}) -> /work/output-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet-n12-196045-20260422_060234.csv") diff --git a/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/_bayesnet_train.py b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/_bayesnet_train.py new file mode 100644 index 0000000000000000000000000000000000000000..b5c094545fded3124fbe5c43ad29e6679d1e8c4f --- /dev/null +++ b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/_bayesnet_train.py @@ -0,0 +1,118 @@ + +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-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/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-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/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-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/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 +if _n_plan > 35 or _n_samples > 200000: + max_bins = 5 +if _n_plan > 55: + max_bins = 4 +print(f"[BayesNet] max_bins={max_bins} (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": + uniques = sorted(s.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] = s.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) +network.fit(enc) + +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-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet_model.pkl", "wb") as _f: + pickle.dump(bundle, _f) +print(f"[BayesNet] Model saved -> /work/output-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet_model.pkl") diff --git a/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet-n12-196045-20260422_060234.csv b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet-n12-196045-20260422_060234.csv new file mode 100644 index 0000000000000000000000000000000000000000..fa7e6ccdd2ab0b9adb82c92f821ee54b48438f0b --- /dev/null +++ b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet-n12-196045-20260422_060234.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8552d27b2d2ab3e62d36be08e91ec6cec8e6ded2f4f0ea8620267a56bd5520f2 +size 14584062 diff --git a/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet_coltypes.json b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet_coltypes.json new file mode 100644 index 0000000000000000000000000000000000000000..e0bc90cc65faf1a3e75932bf349dc03857fb2d66 --- /dev/null +++ b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet_coltypes.json @@ -0,0 +1,21 @@ +{ + "columns": [ + { + "name": "feature_1", + "type": "continuous" + }, + { + "name": "feature_2", + "type": "continuous" + }, + { + "name": "feature_3", + "type": "continuous" + }, + { + "name": "target", + "type": "continuous" + } + ], + "integer_columns": [] +} \ No newline at end of file diff --git a/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet_model.pkl b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet_model.pkl new file mode 100644 index 0000000000000000000000000000000000000000..0a4cc9eaea2c9ed83dad804c04788f06cca0650a --- /dev/null +++ b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/bayesnet_model.pkl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f6ec8386ff41840ac9208f69b88d7f84b61bb9aeae50fd6ef1c60a6e2ff95674 +size 4766 diff --git a/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/const_cols.json b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/const_cols.json new file mode 100644 index 0000000000000000000000000000000000000000..9e26dfeeb6e641a33dae4961196235bdb965b21b --- /dev/null +++ b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/const_cols.json @@ -0,0 +1 @@ +{} \ No newline at end of file diff --git a/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/gen_20260422_060234.log b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/gen_20260422_060234.log new file mode 100644 index 0000000000000000000000000000000000000000..ebb6cf23bdfcb66fa16f5f832c726e67bbbea02a --- /dev/null +++ b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/gen_20260422_060234.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:7bc1f4eb8d65d32c28f984e2d84f7aa41e44354adc8ba1125cdac27a2d5f4af5 +size 3396 diff --git a/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/input_snapshot.json b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..00e868f0c3c2aa7c602577937ae9237053722452 --- /dev/null +++ b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n12", + "model": "bayesnet", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-train.csv", + "exists": true, + "size": 2720466, + "sha256": "4c3e44750c769fb56cd6224e07240585091e57a4786f4bbd4b914826fe9eedb2" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-val.csv", + "exists": true, + "size": 340170, + "sha256": "761692b00c3ad9e4f07dd51f386f4d42ab2b68ed91f741cd850981f7f5b58fd5" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-test.csv", + "exists": true, + "size": 340296, + "sha256": "6531e89976491f6fb7d02635a2e934e058c1bb15faaf5debc7052fbe5d0b8b81" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n12/n12-dataset_profile.json", + "exists": true, + "size": 2302, + "sha256": "d4fe8e20de077a2855d2af5dd1e73126e04bf2a0741e28ff80368983f126319b" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n12/n12-dataset_contract_v1.json", + "exists": true, + "size": 2472, + "sha256": "856639afabf103741f49f84eac0546ba3f4f3d2258fa3016263682d164e78a7a" + } + } +} \ No newline at end of file diff --git a/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/public_gate/normalized_schema_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..de9552b7c09c03f3ffefc32913ed80e6aa0d5dee --- /dev/null +++ b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,88 @@ +{ + "dataset_id": "n12", + "target_column": "target", + "task_type": "classification", + "columns": [ + { + "name": "feature_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "74", + "14", + "115", + "130", + "5" + ] + } + }, + { + "name": "feature_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "85", + "5", + "116", + "169", + "4" + ] + } + }, + { + "name": "feature_3", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "123", + "186", + "60", + "221", + "0" + ] + } + }, + { + "name": "target", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 1e-05, + "example_values": [ + "1", + "2" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/public_gate/public_gate_report.json b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/public_gate/public_gate_report.json new file mode 100644 index 0000000000000000000000000000000000000000..956c216ac51e3ac3d437939ae2c2be86873cf48b --- /dev/null +++ b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/public_gate/public_gate_report.json @@ -0,0 +1,37 @@ +{ + "dataset_id": "n12", + "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": "target", + "task_type": "classification", + "input_splits": { + "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-train.csv", + "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-val.csv", + "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-test.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/public_gate/staged_input_manifest.json b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/public_gate/staged_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..56ede973b3d0db1f58f09524ab92fb4c3fd8cea9 --- /dev/null +++ b/syntheticSuccess/n12/bayesnet/bayesnet-n12-20260422_060152/public_gate/staged_input_manifest.json @@ -0,0 +1,93 @@ +{ + "dataset_id": "n12", + "target_column": "target", + "task_type": "classification", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/bayesnet/bayesnet-n12-20260422_060152/public_gate/public_gate_report.json", + "column_schema": [ + { + "name": "feature_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { 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"missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 1e-05, + "example_values": [ + "1", + "2" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/runtime_result.json b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/runtime_result.json new file mode 100644 index 0000000000000000000000000000000000000000..c7284a50d2ef744313f8225f61776e0eba7dce3a --- /dev/null +++ b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/runtime_result.json @@ -0,0 +1,14 @@ +{ + "dataset_id": "n12", + "model": "ctgan", + "run_id": "ctgan-n12-20260328_054309", + "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/n12/ctgan/ctgan-n12-20260328_054309/ctgan-n12-196045-20260330_070542.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/ctgan/adapter_report.json b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/ctgan/adapter_report.json new file mode 100644 index 0000000000000000000000000000000000000000..c9ca92aaa4b14a89c1060eadb6b4e9acae2d8ec8 --- /dev/null +++ b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/ctgan/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/n12/ctgan/ctgan-n12-20260328_054309/staged/ctgan/model_input_manifest.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/ctgan/adapter_transforms_applied.json b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/ctgan/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/ctgan/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/ctgan/model_input_manifest.json b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/ctgan/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e8a4e7d91d2c69064a7fb7d8c97fea22002754d6 --- /dev/null +++ b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/ctgan/model_input_manifest.json @@ -0,0 +1,95 @@ +{ + "dataset_id": "n12", + "model": "ctgan", + "target_column": "target", + "task_type": "classification", + "column_schema": [ + { + "name": "feature_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "74", + "14", + "115", + "130", + "5" + ] + } + }, + { + "name": "feature_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "85", + "5", + "116", + "169", + "4" + ] + } + }, + { + "name": "feature_3", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "123", + "186", + "60", + "221", + "0" + ] + } + }, + { + "name": "target", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 1e-05, + "example_values": [ + "1", + "2" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/ctgan/ctgan-n12-20260328_054309/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/ctgan/ctgan-n12-20260328_054309/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/ctgan/ctgan-n12-20260328_054309/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/ctgan/ctgan-n12-20260328_054309/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/ctgan/ctgan-n12-20260328_054309/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/ctgan/ctgan-n12-20260328_054309/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/staged_features.json b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..d439c0620c179a5a439add22d2a218d42f9ca5d4 --- /dev/null +++ b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/staged_features.json @@ -0,0 +1,22 @@ +[ + { + "feature_name": "feature_1", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "feature_2", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "feature_3", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "target", + "data_type": "continuous", + "is_target": true + } +] \ No newline at end of file diff --git a/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/test.csv b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..337e8e477426cd837a2169731ff6ef5025d06f36 --- /dev/null +++ b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4972eb2812d325c143ec99492afa470fe047141a9bdf34893ec0133a12b8dc26 +size 315789 diff --git a/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/train.csv b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..023dad2054b44ff77ffcf6f4554ad423242e80c2 --- /dev/null +++ b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/train.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:728fec9c0ec06ca4b292989614be4374c308d9a15b1e0002c3daeb3a68d5d350 +size 2524420 diff --git a/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/val.csv b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/val.csv new file mode 100644 index 0000000000000000000000000000000000000000..8dc60d3ec85d7e82382b2245a4ce835645e4a714 --- /dev/null +++ b/syntheticSuccess/n12/ctgan/ctgan-n12-20260328_054309/staged/public/val.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8931c0b2402466ccca41868fc484ab4bc6f627d68422570b20d47d1104922959 +size 315663 diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/_tabddpm_sample.py b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/_tabddpm_sample.py new file mode 100644 index 0000000000000000000000000000000000000000..f346c7f8f6fb7afdbc8aa3450fc98184dd74a0f3 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/_tabddpm_sample.py @@ -0,0 +1,66 @@ +import os, sys, subprocess, json +import numpy as np +import pandas as pd + +tabddpm_root = "/workspace/tabddpm/code" +assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}" +env = os.environ.copy() +env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", "")) + +# Reuse the compat wrapper (patches collections.Sequence for skorch) +wrapper = os.path.join(tabddpm_root, "_compat_run.py") +if not os.path.exists(wrapper): + with open(wrapper, "w") as f: + f.write( + "import collections, collections.abc\n" + "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping'," + "'MutableSet','Set','Callable','Iterable','Iterator'):\n" + " if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n" + "import sys, runpy\n" + "sys.argv = sys.argv[1:]\n" + "runpy.run_path(sys.argv[0], run_name='__main__')\n" + ) + +print(f"[TabDDPM] Sampling 196045 rows") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/config_sample_20260425_074821.toml", + "--sample"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) + +# 将 .npy 输出转为 CSV（npy 在 TabDDPM 的 parent_dir，即 npy_dir） +info_path = "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/data/info.json" +with open(info_path) as f: + info = json.load(f) + +output_dir = "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/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/n12/tabddpm/tabddpm-n12-20260328_053008/tabddpm-n12-196045-20260425_074821.csv", index=False) + print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/tabddpm-n12-196045-20260425_074821.csv") +else: + print("[TabDDPM] WARNING: No output .npy files found") + sys.exit(1) diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/_tabddpm_train.py b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/_tabddpm_train.py new file mode 100644 index 0000000000000000000000000000000000000000..eed05462c5f6b207cf953072601296f8096ba4f4 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/_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/n12/tabddpm/tabddpm-n12-20260328_053008/config.toml") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/config.toml", + "--train"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print("[TabDDPM] Training complete") diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/config.toml b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/config.toml new file mode 100644 index 0000000000000000000000000000000000000000..7012c61048ebf98b2fe32f6966118246449c3419 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/config.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/output" +real_data_path = "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/data" +model_type = "mlp" +num_numerical_features = 3 +device = "cuda:0" + +[model_params] +d_in = 3 +num_classes = 2 +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/n12/tabddpm/tabddpm-n12-20260328_053008/config_sample_20260424_210951.toml b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/config_sample_20260424_210951.toml new file mode 100644 index 0000000000000000000000000000000000000000..9647a1a92f5773d861aa6126be82120f097dc1fe --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/config_sample_20260424_210951.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/output" +real_data_path = "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/data" +model_type = "mlp" +num_numerical_features = 3 +device = "cuda:0" + +[model_params] +d_in = 3 +num_classes = 2 +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 = 196045 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/config_sample_20260425_032503.toml b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/config_sample_20260425_032503.toml new file mode 100644 index 0000000000000000000000000000000000000000..9647a1a92f5773d861aa6126be82120f097dc1fe --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/config_sample_20260425_032503.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/output" +real_data_path = "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/data" +model_type = "mlp" +num_numerical_features = 3 +device = "cuda:0" + +[model_params] +d_in = 3 +num_classes = 2 +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 = 196045 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/config_sample_20260425_074821.toml b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/config_sample_20260425_074821.toml new file mode 100644 index 0000000000000000000000000000000000000000..9647a1a92f5773d861aa6126be82120f097dc1fe --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/config_sample_20260425_074821.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/output" +real_data_path = "/work/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/data" +model_type = "mlp" +num_numerical_features = 3 +device = "cuda:0" + +[model_params] +d_in = 3 +num_classes = 2 +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 = 196045 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/data/X_num_test.npy b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/data/X_num_test.npy new file mode 100644 index 0000000000000000000000000000000000000000..76a833ad95f1ac9563fd6fa46e86c101399fbaf1 --- /dev/null +++ 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"116", + "169", + "4" + ] + } + }, + { + "name": "feature_3", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "123", + "186", + "60", + "221", + "0" + ] + } + }, + { + "name": "target", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 1e-05, + "example_values": [ + "1", + "2" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/runtime_result.json b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/runtime_result.json new file mode 100644 index 0000000000000000000000000000000000000000..0e5cc1727475850985b7754c6d1ff0d95b246113 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/runtime_result.json @@ -0,0 +1,14 @@ +{ + "dataset_id": "n12", + "model": "tabddpm", + "run_id": "tabddpm-n12-20260328_053008", + "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/n12/tabddpm/tabddpm-n12-20260328_053008/tabddpm-n12-196045-20260425_074821.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/staged_features.json b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..d439c0620c179a5a439add22d2a218d42f9ca5d4 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/staged_features.json @@ -0,0 +1,22 @@ +[ + { + "feature_name": "feature_1", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "feature_2", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "feature_3", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "target", + "data_type": "continuous", + "is_target": true + } +] \ No newline at end of file diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/test.csv b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..337e8e477426cd837a2169731ff6ef5025d06f36 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4972eb2812d325c143ec99492afa470fe047141a9bdf34893ec0133a12b8dc26 +size 315789 diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/train.csv b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..023dad2054b44ff77ffcf6f4554ad423242e80c2 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/train.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:728fec9c0ec06ca4b292989614be4374c308d9a15b1e0002c3daeb3a68d5d350 +size 2524420 diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/val.csv b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/val.csv new file mode 100644 index 0000000000000000000000000000000000000000..8dc60d3ec85d7e82382b2245a4ce835645e4a714 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/val.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8931c0b2402466ccca41868fc484ab4bc6f627d68422570b20d47d1104922959 +size 315663 diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/tabddpm/adapter_report.json b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/tabddpm/adapter_report.json new file mode 100644 index 0000000000000000000000000000000000000000..87bdfd467041591b57f05933fcfae480a0b83ac0 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/tabddpm/adapter_report.json @@ -0,0 +1,7 @@ +{ + "adapter_ready_status": "pass", + "adapter_fail_reason_code": null, + "adapter_fail_detail": null, + "adapter_transforms_applied": [], + "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/staged/tabddpm/model_input_manifest.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/tabddpm/adapter_transforms_applied.json b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/tabddpm/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/tabddpm/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/tabddpm/model_input_manifest.json b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/tabddpm/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..4851e71200d7ec088eb14ee973753272e51ca699 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/staged/tabddpm/model_input_manifest.json @@ -0,0 +1,95 @@ +{ + "dataset_id": "n12", + "model": "tabddpm", + "target_column": "target", + "task_type": "classification", + "column_schema": [ + { + "name": "feature_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "74", + "14", + "115", + "130", + "5" + ] + } + }, + { + "name": "feature_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "85", + "5", + "116", + "169", + "4" + ] + } + }, + { + "name": "feature_3", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + 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"/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabddpm/tabddpm-n12-20260328_053008/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/tabddpm-n12-1000-20260328_053401.csv b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/tabddpm-n12-1000-20260328_053401.csv new file mode 100644 index 0000000000000000000000000000000000000000..a91eac22bbe128a79049ba505de077db36111ae2 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/tabddpm-n12-1000-20260328_053401.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:842e936f06bece9f0591e4f6ed42b577224461bb09a0f7114504a047bab37142 +size 29809 diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/tabddpm-n12-196045-20260425_074821.csv b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/tabddpm-n12-196045-20260425_074821.csv new file mode 100644 index 0000000000000000000000000000000000000000..8b5aa395c90d046b8262d8560e0dbc22ffe58247 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/tabddpm-n12-196045-20260425_074821.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:87c0212a8589b500b7ea734ea4fb05e4c2576eaebbb5ab7437c72a465e7cf412 +size 5886720 diff --git a/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/train_20260328_053012.log b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/train_20260328_053012.log new file mode 100644 index 0000000000000000000000000000000000000000..390ac8ab044ef7dc7cdd96ab9fbfd86f563cf5b1 --- /dev/null +++ b/syntheticSuccess/n12/tabddpm/tabddpm-n12-20260328_053008/train_20260328_053012.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fd4ce96c2b2cbaef608f94ad2f5a54dde5f960ff0fb511f0b3d0a85b5c2678f7 +size 1120 diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/_tabpfgen_generate.py b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/_tabpfgen_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..0c31568539c2fda5ac12df48e8ca2af38009c14a --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/_tabpfgen_generate.py @@ -0,0 +1,68 @@ +import numpy as np +import pandas as pd +import json +from tabpfgen import TabPFGen + +df = pd.read_csv("/work/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/train.csv") +target_col = "target" + +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 + +# 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 1000 rows via generate_regression") +X_syn, y_syn = gen.generate_regression(X, y, n_samples=1000) + +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] + +syn_df = syn_df[list(df.columns)] +syn_df.to_csv("/work/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/tabpfgen-n12-1000-20260321_065426.csv", index=False) +print(f"[TabPFGen] Saved {len(syn_df)} rows -> /work/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/tabpfgen-n12-1000-20260321_065426.csv") diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/gen_20260321_065426.log b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/gen_20260321_065426.log new file mode 100644 index 0000000000000000000000000000000000000000..d7c726c4d6987057bc9f8d801093c45fa0ea4e24 --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/gen_20260321_065426.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d6dda71fbc899b271927469c3c4c43e4d12965e664e25cc3741ba1f0b030f70c +size 1132 diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/input_snapshot.json b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..4732f4f65ac1d249b66663b01ecf02d025cf56c2 --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n12", + "model": "tabpfgen", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-train.csv", + "exists": true, + "size": 2720466, + "sha256": "4c3e44750c769fb56cd6224e07240585091e57a4786f4bbd4b914826fe9eedb2" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-val.csv", + "exists": true, + "size": 340170, + "sha256": "761692b00c3ad9e4f07dd51f386f4d42ab2b68ed91f741cd850981f7f5b58fd5" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-test.csv", + "exists": true, + "size": 340296, + "sha256": "6531e89976491f6fb7d02635a2e934e058c1bb15faaf5debc7052fbe5d0b8b81" + }, + "profile_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n12/n12-dataset_profile.json", + "exists": true, + "size": 2302, + "sha256": "d4fe8e20de077a2855d2af5dd1e73126e04bf2a0741e28ff80368983f126319b" + }, + "contract_json": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n12/n12-dataset_contract_v1.json", + "exists": true, + "size": 2472, + "sha256": "856639afabf103741f49f84eac0546ba3f4f3d2258fa3016263682d164e78a7a" + } + } +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/public_gate/normalized_schema_snapshot.json b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/public_gate/normalized_schema_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..de9552b7c09c03f3ffefc32913ed80e6aa0d5dee --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/public_gate/normalized_schema_snapshot.json @@ -0,0 +1,88 @@ +{ + "dataset_id": "n12", + "target_column": "target", + "task_type": "classification", + "columns": [ + { + "name": "feature_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "74", + "14", + "115", + "130", + "5" + ] + } + }, + { + "name": "feature_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "85", + "5", + "116", + "169", + "4" + ] + } + }, + { + "name": "feature_3", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "123", + "186", + "60", + "221", + "0" + ] + } + }, + { + "name": "target", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 1e-05, + "example_values": [ + "1", + "2" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/public_gate/public_gate_report.json b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/public_gate/public_gate_report.json new file mode 100644 index 0000000000000000000000000000000000000000..956c216ac51e3ac3d437939ae2c2be86873cf48b --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/public_gate/public_gate_report.json @@ -0,0 +1,37 @@ +{ + "dataset_id": "n12", + "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": "target", + "task_type": "classification", + "input_splits": { + "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-train.csv", + "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-val.csv", + "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-test.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/public_gate/staged_input_manifest.json b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/public_gate/staged_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..26e91f0f97d16d12fbb8fc7fe31b753d24ee8c84 --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/public_gate/staged_input_manifest.json @@ -0,0 +1,93 @@ +{ + "dataset_id": "n12", + "target_column": "target", + "task_type": "classification", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/test.csv", + 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"example_values": [ + "85", + "5", + "116", + "169", + "4" + ] + } + }, + { + "name": "feature_3", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "123", + "186", + "60", + "221", + "0" + ] + } + }, + { + "name": "target", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 1e-05, + "example_values": [ + "1", + "2" + ] + } + } + ] +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/runtime_result.json b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/runtime_result.json new file mode 100644 index 0000000000000000000000000000000000000000..0e8f7580c722335d746b78631f1330c8d7423a6d --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/runtime_result.json @@ -0,0 +1,15 @@ +{ + "dataset_id": "n12", + "model": "tabpfgen", + "run_id": "tabpfgen-n12-20260321_065425", + "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-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/tabpfgen-n12-1000-20260321_065426.csv", + "model_path": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/staged_features.json b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/staged_features.json new file mode 100644 index 0000000000000000000000000000000000000000..d439c0620c179a5a439add22d2a218d42f9ca5d4 --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/staged_features.json @@ -0,0 +1,22 @@ +[ + { + "feature_name": "feature_1", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "feature_2", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "feature_3", + "data_type": "continuous", + "is_target": false + }, + { + "feature_name": "target", + "data_type": "continuous", + "is_target": true + } +] \ No newline at end of file diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/test.csv b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..337e8e477426cd837a2169731ff6ef5025d06f36 --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4972eb2812d325c143ec99492afa470fe047141a9bdf34893ec0133a12b8dc26 +size 315789 diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/train.csv b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/train.csv new file mode 100644 index 0000000000000000000000000000000000000000..023dad2054b44ff77ffcf6f4554ad423242e80c2 --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/train.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:728fec9c0ec06ca4b292989614be4374c308d9a15b1e0002c3daeb3a68d5d350 +size 2524420 diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/val.csv b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/val.csv new file mode 100644 index 0000000000000000000000000000000000000000..8dc60d3ec85d7e82382b2245a4ce835645e4a714 --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/val.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:8931c0b2402466ccca41868fc484ab4bc6f627d68422570b20d47d1104922959 +size 315663 diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/tabpfgen/adapter_report.json b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/tabpfgen/adapter_report.json new file mode 100644 index 0000000000000000000000000000000000000000..3098aeff345e7cd61ccfbcb6acd36bba86353f5c --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/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/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/tabpfgen/model_input_manifest.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/tabpfgen/adapter_transforms_applied.json b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/tabpfgen/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/tabpfgen/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/tabpfgen/model_input_manifest.json b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/tabpfgen/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..5a61303a93d9540e004b3cc633f540eedc656e7b --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/tabpfgen/model_input_manifest.json @@ -0,0 +1,95 @@ +{ + "dataset_id": "n12", + "model": "tabpfgen", + "target_column": "target", + "task_type": "classification", + "column_schema": [ + { + "name": "feature_1", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "74", + "14", + "115", + "130", + "5" + ] + } + }, + { + "name": "feature_2", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "85", + "5", + "116", + "169", + "4" + ] + } + }, + { + "name": "feature_3", + "role": "feature", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 256, + "unique_ratio": 0.001306, + "example_values": [ + "123", + "186", + "60", + "221", + "0" + ] + } + }, + { + "name": "target", + "role": "target", + "semantic_type": "numeric", + "nullable": false, + "missing_tokens": [], + "parse_format": null, + "impute_strategy": "median", + "profile_stats": { + "missing_rate": 0.0, + "unique_count": 2, + "unique_ratio": 1e-05, + "example_values": [ + "1", + "2" + ] + } + } + ], + "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/public_gate/staged_input_manifest.json", + "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/train.csv", + "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/val.csv", + "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/test.csv", + "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/tabpfgen-n12-1000-20260321_065426.csv b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/tabpfgen-n12-1000-20260321_065426.csv new file mode 100644 index 0000000000000000000000000000000000000000..2428c1947e61c4bff0f228e02c5ce62ad57cb721 --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/tabpfgen-n12-1000-20260321_065426.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6b025a2c434297aa0f94cda2548c446f5cecbf709454788220a8a8c080711e4a +size 47818 diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/tabpfgen_meta.json b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/tabpfgen_meta.json new file mode 100644 index 0000000000000000000000000000000000000000..31184ca3ddcd56a707d24c8a9001764cb09b3ebd --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/tabpfgen_meta.json @@ -0,0 +1,8 @@ +{ + "csv_path": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/train.csv", + "json_path": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n12/tabpfgen/tabpfgen-n12-20260321_065425/staged/public/staged_features.json", + "target_col": "target", + "is_classification": false, + "n_rows": 196045, + "n_cols": 4 +} \ No newline at end of file diff --git a/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/train_20260321_065426.log b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/train_20260321_065426.log new file mode 100644 index 0000000000000000000000000000000000000000..26dad92d067a57ad7475527efefd158c7184f97f --- /dev/null +++ b/syntheticSuccess/n12/tabpfgen/tabpfgen-n12-20260321_065425/train_20260321_065426.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:85a180550423cd9fd3bf9f015bda0b92878ed4cb55b4f59fd9cb649d76f7c2f6 +size 188 diff --git a/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/_tvae_generate.py b/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/_tvae_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..318eee9608f9f4ba2bf7d898150ef078398be1d2 --- /dev/null +++ b/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/_tvae_generate.py @@ -0,0 +1,5 @@ +from ctgan.synthesizers.tvae import TVAE +model = TVAE.load("/work/output-SpecializedModels/n12/tvae/tvae-n12-20260320_072508/models_300epochs/tvae_300epochs.pt") +samples = model.sample(196045) +samples.to_csv("/work/output-SpecializedModels/n12/tvae/tvae-n12-20260320_072508/tvae-n12-196045-20260330_070555.csv", index=False) +print(f"[TVAE] Generated 196045 rows -> /work/output-SpecializedModels/n12/tvae/tvae-n12-20260320_072508/tvae-n12-196045-20260330_070555.csv") diff --git a/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/_tvae_train.py b/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/_tvae_train.py new file mode 100644 index 0000000000000000000000000000000000000000..6fb7d0fcb258ac29c5c2f9b9ba37404a2050292c --- /dev/null +++ b/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/_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/DatasetNew/n12/n12-train.csv" +meta_path = "/work/output-SpecializedModels/n12/tvae/tvae-n12-20260320_072508/tvae_metadata.json" +save_path = "/work/output-SpecializedModels/n12/tvae/tvae-n12-20260320_072508/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/n12/tvae/tvae-n12-20260320_072508/gen_20260320_080436.log b/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/gen_20260320_080436.log new file mode 100644 index 0000000000000000000000000000000000000000..fb5b4bcab489170a194de03ead0606cf0a4550b9 --- /dev/null +++ b/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/gen_20260320_080436.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ce80e9a5a844a5b1ac12f51f89cd42f02e03d3d89ac0ddbd7446502151de74d5 +size 129 diff --git a/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/gen_20260330_070555.log b/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/gen_20260330_070555.log new file mode 100644 index 0000000000000000000000000000000000000000..97bc879e654f6a4857c84891301c0c6ff8b3c50b --- /dev/null +++ b/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/gen_20260330_070555.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1bb262b6bab299c6f86f3dbd11de4468dd078e72f2026036e2344a5ad86bf539 +size 133 diff --git a/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/input_snapshot.json b/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..3e4e533e55d6f62020dc2f0bc98b6e33824bf160 --- /dev/null +++ b/syntheticSuccess/n12/tvae/tvae-n12-20260320_072508/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n12", + "model": "tvae", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-train.csv", + "exists": true, + "size": 2720466, + "sha256": "4c3e44750c769fb56cd6224e07240585091e57a4786f4bbd4b914826fe9eedb2" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-val.csv", + "exists": true, + "size": 340170, + "sha256": "761692b00c3ad9e4f07dd51f386f4d42ab2b68ed91f741cd850981f7f5b58fd5" + }, + "test_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n12/n12-test.csv", + "exists": true, + "size": 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