Resume SynthData0523 main/m9 batch 1

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SynthData0523/main/m9/arf/arf-m9-20260325_033734/_arf_generate.py

@@ -0,0 +1,6 @@
+import pickle
+with open("/work/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/arf_model.pkl", "rb") as f:
+    model = pickle.load(f)
+syn = model.forge(n=15326)
+syn.to_csv("/work/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/arf-m9-15326-20260330_065743.csv", index=False)
+print(f"[ARF] Generated 15326 rows -> /work/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/arf-m9-15326-20260330_065743.csv")

SynthData0523/main/m9/arf/arf-m9-20260325_033734/_arf_train.py

@@ -0,0 +1,19 @@
+import pickle
+import pandas as pd
+from arfpy import arf
+
+df = pd.read_csv("/work/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/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/m9/arf/arf-m9-20260325_033734/arf_model.pkl", "wb") as f:
+    pickle.dump(model, f)
+print(f"[ARF] Model saved -> /work/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/arf_model.pkl")

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+{
+  "dataset_id": "m9",
+  "model": "arf",
+  "inputs": {
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+}

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+          "11",
+          "84",
+          "29",
+          "46"
+        ]
+      }
+    },
+    {
+      "name": "target",
+      "role": "target",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_ratio": 0.00013,
+        "example_values": [
+          "0.0",
+          "1.0"
+        ]
+      }
+    }
+  ]
+}

SynthData0523/main/m9/arf/arf-m9-20260325_033734/public_gate/public_gate_report.json

@@ -0,0 +1,37 @@
+{
+  "dataset_id": "m9",
+  "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/m9/m9-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m9/m9-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m9/m9-test.csv"
+  }
+}

SynthData0523/main/m9/arf/arf-m9-20260325_033734/public_gate/staged_input_manifest.json

@@ -0,0 +1,296 @@
+{
+  "dataset_id": "m9",
+  "target_column": "target",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/public_gate/public_gate_report.json",
+  "column_schema": [
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+      "name": "enrollee_id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
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+      "impute_strategy": "median",
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+        "unique_ratio": 1.0,
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+          "32011",
+          "32184",
+          "13892"
+        ]
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+    },
+    {
+      "name": "city",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
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+        "unique_ratio": 0.00796,
+        "example_values": [
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+          "city_13",
+          "city_136",
+          "city_114",
+          "city_21"
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+      }
+    },
+    {
+      "name": "city_development_index",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+          "0.9259999999999999",
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+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
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+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
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+        "unique_count": 3,
+        "unique_ratio": 0.000257,
+        "example_values": [
+          "Male",
+          "Female",
+          "Other"
+        ]
+      }
+    },
+    {
+      "name": "relevent_experience",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
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+        "unique_ratio": 0.00013,
+        "example_values": [
+          "No relevent experience",
+          "Has relevent experience"
+        ]
+      }
+    },
+    {
+      "name": "enrolled_university",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
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+        "unique_count": 3,
+        "unique_ratio": 0.0002,
+        "example_values": [
+          "no_enrollment",
+          "Part time course",
+          "Full time course"
+        ]
+      }
+    },
+    {
+      "name": "education_level",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.024403,
+        "unique_count": 5,
+        "unique_ratio": 0.000334,
+        "example_values": [
+          "Primary School",
+          "Masters",
+          "Graduate",
+          "High School",
+          "Phd"
+        ]
+      }
+    },
+    {
+      "name": "major_discipline",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
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+        "unique_count": 6,
+        "unique_ratio": 0.00046,
+        "example_values": [
+          "STEM",
+          "Humanities",
+          "Business Degree",
+          "No Major",
+          "Other"
+        ]
+      }
+    },
+    {
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+      "role": "feature",
+      "semantic_type": "categorical",
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+      "missing_tokens": [],
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+        "unique_ratio": 0.00144,
+        "example_values": [
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+          "13",
+          "3",
+          ">20"
+        ]
+      }
+    },
+    {
+      "name": "company_size",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
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+        "unique_count": 8,
+        "unique_ratio": 0.000759,
+        "example_values": [
+          "50-99",
+          "10000+",
+          "<10",
+          "1000-4999",
+          "100-500"
+        ]
+      }
+    },
+    {
+      "name": "company_type",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
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+        "unique_count": 6,
+        "unique_ratio": 0.000578,
+        "example_values": [
+          "Pvt Ltd",
+          "Early Stage Startup",
+          "Public Sector",
+          "Funded Startup",
+          "NGO"
+        ]
+      }
+    },
+    {
+      "name": "last_new_job",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.022054,
+        "unique_count": 6,
+        "unique_ratio": 0.0004,
+        "example_values": [
+          "never",
+          "1",
+          "2",
+          ">4",
+          "4"
+        ]
+      }
+    },
+    {
+      "name": "training_hours",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 241,
+        "unique_ratio": 0.015725,
+        "example_values": [
+          "25",
+          "11",
+          "84",
+          "29",
+          "46"
+        ]
+      }
+    },
+    {
+      "name": "target",
+      "role": "target",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_count": 2,
+        "unique_ratio": 0.00013,
+        "example_values": [
+          "0.0",
+          "1.0"
+        ]
+      }
+    }
+  ]
+}

SynthData0523/main/m9/arf/arf-m9-20260325_033734/runtime_result.json

@@ -0,0 +1,14 @@
+{
+  "dataset_id": "m9",
+  "model": "arf",
+  "run_id": "arf-m9-20260325_033734",
+  "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/m9/arf/arf-m9-20260325_033734/arf-m9-15326-20260330_065743.csv"
+  }
+}

SynthData0523/main/m9/arf/arf-m9-20260325_033734/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/m9/arf/arf-m9-20260325_033734/staged/arf/model_input_manifest.json"
+}

SynthData0523/main/m9/arf/arf-m9-20260325_033734/staged/arf/adapter_transforms_applied.json

@@ -0,0 +1 @@
+[]

SynthData0523/main/m9/arf/arf-m9-20260325_033734/staged/arf/model_input_manifest.json

@@ -0,0 +1,298 @@
+{
+  "dataset_id": "m9",
+  "model": "arf",
+  "target_column": "target",
+  "task_type": "classification",
+  "column_schema": [
+    {
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+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
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+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_ratio": 1.0,
+        "example_values": [
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+          "32011",
+          "32184",
+          "13892"
+        ]
+      }
+    },
+    {
+      "name": "city",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 122,
+        "unique_ratio": 0.00796,
+        "example_values": [
+          "city_103",
+          "city_13",
+          "city_136",
+          "city_114",
+          "city_21"
+        ]
+      }
+    },
+    {
+      "name": "city_development_index",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+          "0.897",
+          "0.9259999999999999",
+          "0.624"
+        ]
+      }
+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.238353,
+        "unique_count": 3,
+        "unique_ratio": 0.000257,
+        "example_values": [
+          "Male",
+          "Female",
+          "Other"
+        ]
+      }
+    },
+    {
+      "name": "relevent_experience",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
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+        "unique_ratio": 0.00013,
+        "example_values": [
+          "No relevent experience",
+          "Has relevent experience"
+        ]
+      }
+    },
+    {
+      "name": "enrolled_university",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
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+        "unique_count": 3,
+        "unique_ratio": 0.0002,
+        "example_values": [
+          "no_enrollment",
+          "Part time course",
+          "Full time course"
+        ]
+      }
+    },
+    {
+      "name": "education_level",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.024403,
+        "unique_count": 5,
+        "unique_ratio": 0.000334,
+        "example_values": [
+          "Primary School",
+          "Masters",
+          "Graduate",
+          "High School",
+          "Phd"
+        ]
+      }
+    },
+    {
+      "name": "major_discipline",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.148636,
+        "unique_count": 6,
+        "unique_ratio": 0.00046,
+        "example_values": [
+          "STEM",
+          "Humanities",
+          "Business Degree",
+          "No Major",
+          "Other"
+        ]
+      }
+    },
+    {
+      "name": "experience",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
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+        "example_values": [
+          "5",
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+          "13",
+          "3",
+          ">20"
+        ]
+      }
+    },
+    {
+      "name": "company_size",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
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+        "example_values": [
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+          "1000-4999",
+          "100-500"
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+      }
+    },
+    {
+      "name": "company_type",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
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+        "unique_count": 6,
+        "unique_ratio": 0.000578,
+        "example_values": [
+          "Pvt Ltd",
+          "Early Stage Startup",
+          "Public Sector",
+          "Funded Startup",
+          "NGO"
+        ]
+      }
+    },
+    {
+      "name": "last_new_job",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
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+        "unique_count": 6,
+        "unique_ratio": 0.0004,
+        "example_values": [
+          "never",
+          "1",
+          "2",
+          ">4",
+          "4"
+        ]
+      }
+    },
+    {
+      "name": "training_hours",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
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+        "unique_ratio": 0.015725,
+        "example_values": [
+          "25",
+          "11",
+          "84",
+          "29",
+          "46"
+        ]
+      }
+    },
+    {
+      "name": "target",
+      "role": "target",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_ratio": 0.00013,
+        "example_values": [
+          "0.0",
+          "1.0"
+        ]
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+    }
+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/arf/arf-m9-20260325_033734/public_gate/public_gate_report.json"
+}

SynthData0523/main/m9/arf/arf-m9-20260325_033734/staged/public/staged_features.json

@@ -0,0 +1,72 @@
+[
+  {
+    "feature_name": "enrollee_id",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "city",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "city_development_index",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "gender",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "relevent_experience",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "enrolled_university",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "education_level",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "major_discipline",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "experience",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "company_size",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "company_type",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "last_new_job",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "training_hours",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "target",
+    "data_type": "continuous",
+    "is_target": true
+  }
+]

SynthData0523/main/m9/arf/arf-m9-20260325_033734/staged/public/test.csv

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+size 193961

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+size 1544257

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+size 193818

SynthData0523/main/m9/arf/arf-m9-20260325_033734/train_20260325_033735.log

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+size 350

SynthData0523/main/m9/bayesnet/bayesnet-m9-20260321_080130/_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/m9/bayesnet/bayesnet-m9-20260321_080130/bayesnet_model.pkl", "rb") as f:
+    plugin = pickle.load(f)
+syn = plugin.generate(count=15326).dataframe()
+
+# Restore zero-variance columns that were dropped during training
+const_path = "/work/output-SpecializedModels/m9/bayesnet/bayesnet-m9-20260321_080130/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/m9/bayesnet/bayesnet-m9-20260321_080130/bayesnet-m9-15326-20260330_065816.csv", index=False)
+print(f"[BayesNet] Generated 15326 rows -> /work/output-SpecializedModels/m9/bayesnet/bayesnet-m9-20260321_080130/bayesnet-m9-15326-20260330_065816.csv")

SynthData0523/main/m9/bayesnet/bayesnet-m9-20260321_080130/_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/m9/bayesnet/bayesnet-m9-20260321_080130/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/m9/bayesnet/bayesnet-m9-20260321_080130/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/m9/bayesnet/bayesnet-m9-20260321_080130/bayesnet_model.pkl", "wb") as f:
+    pickle.dump(plugin, f)
+print(f"[BayesNet] Model saved -> /work/output-SpecializedModels/m9/bayesnet/bayesnet-m9-20260321_080130/bayesnet_model.pkl")

SynthData0523/main/m9/bayesnet/bayesnet-m9-20260321_080130/bayesnet-m9-1000-20260321_080228.csv

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+size 113674

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+size 1740134

SynthData0523/main/m9/bayesnet/bayesnet-m9-20260321_080130/bayesnet_model.pkl

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+size 136828888

SynthData0523/main/m9/bayesnet/bayesnet-m9-20260321_080130/const_cols.json

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+{}

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SynthData0523/main/m9/bayesnet/bayesnet-m9-20260321_080130/input_snapshot.json

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+{
+  "dataset_id": "m9",
+  "model": "bayesnet",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m9/m9-train.csv",
+      "exists": true,
+      "size": 1582666,
+      "sha256": "a3f8afdc773b440d51abd0d3490ff6dd140f091235334aa58569b075b44a200a"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m9/m9-val.csv",
+      "exists": true,
+      "size": 199049,
+      "sha256": "e502e558e93bf38ce6eb32cd839eebaf5a0e428bd8949a13d6f6bbc6c94b56b6"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m9/m9-test.csv",
+      "exists": true,
+      "size": 198975,
+      "sha256": "ea619037db7eed6d1be2023c1b315852b421cf64e17dcb85bd3068d306a093a0"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m9/m9-dataset_profile.json",
+      "exists": true,
+      "size": 6232,
+      "sha256": "4c610aaaca65a4d30b558d1400dd96c2bf90091fcf91257fbcb164d0072d5f20"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m9/m9-dataset_contract_v1.json",
+      "exists": true,
+      "size": 7292,
+      "sha256": "260b8491ad4298f588ea417cbe5685f50711c85e61ee38789fb8bf3f7269178c"
+    }
+  }
+}

SynthData0523/main/m9/bayesnet/bayesnet-m9-20260321_080130/public_gate/normalized_schema_snapshot.json

@@ -0,0 +1,291 @@
+{
+  "dataset_id": "m9",
+  "target_column": "target",
+  "task_type": "classification",
+  "columns": [
+    {
+      "name": "enrollee_id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 15326,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "32408",
+          "5965",
+          "32011",
+          "32184",
+          "13892"
+        ]
+      }
+    },
+    {
+      "name": "city",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 122,
+        "unique_ratio": 0.00796,
+        "example_values": [
+          "city_103",
+          "city_13",
+          "city_136",
+          "city_114",
+          "city_21"
+        ]
+      }
+    },
+    {
+      "name": "city_development_index",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 92,
+        "unique_ratio": 0.006003,
+        "example_values": [
+          "0.92",
+          "0.8270000000000001",
+          "0.897",
+          "0.9259999999999999",
+          "0.624"
+        ]
+      }
+    },
+    {
+      "name": "gender",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.238353,
+        "unique_count": 3,
+        "unique_ratio": 0.000257,
+        "example_values": [
+          "Male",
+          "Female",
+          "Other"
+        ]
+      }
+    },
+    {
+      "name": "relevent_experience",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.00013,
+        "example_values": [
+          "No relevent experience",
+          "Has relevent experience"
+        ]
+      }
+    },
+    {
+      "name": "enrolled_university",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.02088,
+        "unique_count": 3,
+        "unique_ratio": 0.0002,
+        "example_values": [
+          "no_enrollment",
+          "Part time course",
+          "Full time course"
+        ]
+      }
+    },
+    {
+      "name": "education_level",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.024403,
+        "unique_count": 5,
+        "unique_ratio": 0.000334,
+        "example_values": [
+          "Primary School",
+          "Masters",
+          "Graduate",
+          "High School",
+          "Phd"
+        ]
+      }
+    },
+    {
+      "name": "major_discipline",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.148636,
+        "unique_count": 6,
+        "unique_ratio": 0.00046,
+        "example_values": [
+          "STEM",
+          "Humanities",
+          "Business Degree",
+          "No Major",
+          "Other"
+        ]
+      }
+    },
+    {
+      "name": "experience",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
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+      "impute_strategy": "mode",
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+          "5",
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+          "3",
+          ">20"
+        ]
+      }
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+      "name": "company_size",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
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+      "impute_strategy": "mode",
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+        "example_values": [
+          "50-99",
+          "10000+",
+          "<10",
+          "1000-4999",
+          "100-500"
+        ]
+      }
+    },
+    {
+      "name": "company_type",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.322393,
+        "unique_count": 6,
+        "unique_ratio": 0.000578,
+        "example_values": [
+          "Pvt Ltd",
+          "Early Stage Startup",
+          "Public Sector",
+          "Funded Startup",
+          "NGO"
+        ]
+      }
+    },
+    {
+      "name": "last_new_job",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
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+      "impute_strategy": "mode",
+      "profile_stats": {
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+        "unique_ratio": 0.0004,
+        "example_values": [
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+          "2",
+          ">4",
+          "4"
+        ]
+      }
+    },
+    {
+      "name": "training_hours",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_count": 241,
+        "unique_ratio": 0.015725,
+        "example_values": [
+          "25",
+          "11",
+          "84",
+          "29",
+          "46"
+        ]
+      }
+    },
+    {
+      "name": "target",
+      "role": "target",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_count": 2,
+        "unique_ratio": 0.00013,
+        "example_values": [
+          "0.0",
+          "1.0"
+        ]
+      }
+    }
+  ]
+}

SynthData0523/main/m9/bayesnet/bayesnet-m9-20260321_080130/public_gate/public_gate_report.json

@@ -0,0 +1,37 @@
+{
+  "dataset_id": "m9",
+  "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/m9/m9-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m9/m9-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m9/m9-test.csv"
+  }
+}

SynthData0523/main/m9/bayesnet/bayesnet-m9-20260321_080130/public_gate/staged_input_manifest.json

@@ -0,0 +1,296 @@
+{
+  "dataset_id": "m9",
+  "target_column": "target",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/bayesnet/bayesnet-m9-20260321_080130/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/bayesnet/bayesnet-m9-20260321_080130/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/bayesnet/bayesnet-m9-20260321_080130/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/bayesnet/bayesnet-m9-20260321_080130/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/m9/bayesnet/bayesnet-m9-20260321_080130/public_gate/public_gate_report.json",
+  "column_schema": [
+    {
+      "name": "enrollee_id",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 15326,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "32408",
+          "5965",
+          "32011",
+          "32184",
+          "13892"
+        ]
+      }
+    },
+    {
+      "name": "city",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 122,
+        "unique_ratio": 0.00796,
+        "example_values": [
+          "city_103",
+          "city_13",
+          "city_136",
+          "city_114",
+          "city_21"
+        ]
+      }
+    },
+    {
+      "name": "city_development_index",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
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