Add syntheticFail m8

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/input_snapshot.json

@@ -0,0 +1,36 @@
+{
+  "dataset_id": "m8",
+  "model": "realtabformer",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m8/m8-train.csv",
+      "exists": true,
+      "size": 2964802,
+      "sha256": "f9cbb71aa793de19869a138d41aea5808f772b31082741b185ffb8ca7b821833"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m8/m8-val.csv",
+      "exists": true,
+      "size": 370535,
+      "sha256": "5ee8612128aae92155906abc0fdc752ac24fd04d63c78c080c89e3900efe6525"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m8/m8-test.csv",
+      "exists": true,
+      "size": 370991,
+      "sha256": "6221943e422e75c8317b79b7ef93e9cd01f61fdd8de6ce42909a8e4610966310"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m8/m8-dataset_profile.json",
+      "exists": true,
+      "size": 6553,
+      "sha256": "44f883858641584035a0a8859cb95dbcd3a023c03cbc76931aadfc4c70ef871f"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/m8/m8-dataset_contract_v1.json",
+      "exists": true,
+      "size": 8214,
+      "sha256": "e76df134780ec9b6c6c625a54e5d0c1935e9f4a7d09320ad19279a0492438d92"
+    }
+  }
+}

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/public_gate/normalized_schema_snapshot.json

@@ -0,0 +1,346 @@
+{
+  "dataset_id": "m8",
+  "target_column": "y",
+  "task_type": "classification",
+  "columns": [
+    {
+      "name": "age",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 76,
+        "unique_ratio": 0.002101,
+        "example_values": [
+          "40",
+          "52",
+          "31",
+          "51",
+          "44"
+        ]
+      }
+    },
+    {
+      "name": "job",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 12,
+        "unique_ratio": 0.000332,
+        "example_values": [
+          "admin.",
+          "technician",
+          "entrepreneur",
+          "blue-collar",
+          "services"
+        ]
+      }
+    },
+    {
+      "name": "marital",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3,
+        "unique_ratio": 8.3e-05,
+        "example_values": [
+          "single",
+          "married",
+          "divorced"
+        ]
+      }
+    },
+    {
+      "name": "education",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000111,
+        "example_values": [
+          "secondary",
+          "tertiary",
+          "primary",
+          "unknown"
+        ]
+      }
+    },
+    {
+      "name": "default",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 5.5e-05,
+        "example_values": [
+          "no",
+          "yes"
+        ]
+      }
+    },
+    {
+      "name": "balance",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 6604,
+        "unique_ratio": 0.182592,
+        "example_values": [
+          "419",
+          "31",
+          "7567",
+          "315",
+          "737"
+        ]
+      }
+    },
+    {
+      "name": "housing",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 5.5e-05,
+        "example_values": [
+          "no",
+          "yes"
+        ]
+      }
+    },
+    {
+      "name": "loan",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 5.5e-05,
+        "example_values": [
+          "yes",
+          "no"
+        ]
+      }
+    },
+    {
+      "name": "contact",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3,
+        "unique_ratio": 8.3e-05,
+        "example_values": [
+          "cellular",
+          "unknown",
+          "telephone"
+        ]
+      }
+    },
+    {
+      "name": "day",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 31,
+        "unique_ratio": 0.000857,
+        "example_values": [
+          "28",
+          "7",
+          "11",
+          "12",
+          "14"
+        ]
+      }
+    },
+    {
+      "name": "month",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 12,
+        "unique_ratio": 0.000332,
+        "example_values": [
+          "jul",
+          "may",
+          "aug",
+          "oct",
+          "feb"
+        ]
+      }
+    },
+    {
+      "name": "duration",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 1507,
+        "unique_ratio": 0.041667,
+        "example_values": [
+          "100",
+          "120",
+          "70",
+          "291",
+          "102"
+        ]
+      }
+    },
+    {
+      "name": "campaign",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 47,
+        "unique_ratio": 0.001299,
+        "example_values": [
+          "16",
+          "1",
+          "2",
+          "5",
+          "4"
+        ]
+      }
+    },
+    {
+      "name": "pdays",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 524,
+        "unique_ratio": 0.014488,
+        "example_values": [
+          "-1",
+          "91",
+          "365",
+          "189",
+          "117"
+        ]
+      }
+    },
+    {
+      "name": "previous",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 38,
+        "unique_ratio": 0.001051,
+        "example_values": [
+          "0",
+          "4",
+          "1",
+          "2",
+          "3"
+        ]
+      }
+    },
+    {
+      "name": "poutcome",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000111,
+        "example_values": [
+          "unknown",
+          "failure",
+          "other",
+          "success"
+        ]
+      }
+    },
+    {
+      "name": "y",
+      "role": "target",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 5.5e-05,
+        "example_values": [
+          "no",
+          "yes"
+        ]
+      }
+    }
+  ]
+}

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/public_gate/public_gate_report.json

@@ -0,0 +1,37 @@
+{
+  "dataset_id": "m8",
+  "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": "y",
+  "task_type": "classification",
+  "input_splits": {
+    "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m8/m8-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m8/m8-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/m8/m8-test.csv"
+  }
+}

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/public_gate/staged_input_manifest.json

@@ -0,0 +1,351 @@
+{
+  "dataset_id": "m8",
+  "target_column": "y",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/public_gate/public_gate_report.json",
+  "column_schema": [
+    {
+      "name": "age",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 76,
+        "unique_ratio": 0.002101,
+        "example_values": [
+          "40",
+          "52",
+          "31",
+          "51",
+          "44"
+        ]
+      }
+    },
+    {
+      "name": "job",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 12,
+        "unique_ratio": 0.000332,
+        "example_values": [
+          "admin.",
+          "technician",
+          "entrepreneur",
+          "blue-collar",
+          "services"
+        ]
+      }
+    },
+    {
+      "name": "marital",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3,
+        "unique_ratio": 8.3e-05,
+        "example_values": [
+          "single",
+          "married",
+          "divorced"
+        ]
+      }
+    },
+    {
+      "name": "education",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000111,
+        "example_values": [
+          "secondary",
+          "tertiary",
+          "primary",
+          "unknown"
+        ]
+      }
+    },
+    {
+      "name": "default",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 5.5e-05,
+        "example_values": [
+          "no",
+          "yes"
+        ]
+      }
+    },
+    {
+      "name": "balance",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 6604,
+        "unique_ratio": 0.182592,
+        "example_values": [
+          "419",
+          "31",
+          "7567",
+          "315",
+          "737"
+        ]
+      }
+    },
+    {
+      "name": "housing",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 5.5e-05,
+        "example_values": [
+          "no",
+          "yes"
+        ]
+      }
+    },
+    {
+      "name": "loan",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 5.5e-05,
+        "example_values": [
+          "yes",
+          "no"
+        ]
+      }
+    },
+    {
+      "name": "contact",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 3,
+        "unique_ratio": 8.3e-05,
+        "example_values": [
+          "cellular",
+          "unknown",
+          "telephone"
+        ]
+      }
+    },
+    {
+      "name": "day",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 31,
+        "unique_ratio": 0.000857,
+        "example_values": [
+          "28",
+          "7",
+          "11",
+          "12",
+          "14"
+        ]
+      }
+    },
+    {
+      "name": "month",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 12,
+        "unique_ratio": 0.000332,
+        "example_values": [
+          "jul",
+          "may",
+          "aug",
+          "oct",
+          "feb"
+        ]
+      }
+    },
+    {
+      "name": "duration",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 1507,
+        "unique_ratio": 0.041667,
+        "example_values": [
+          "100",
+          "120",
+          "70",
+          "291",
+          "102"
+        ]
+      }
+    },
+    {
+      "name": "campaign",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 47,
+        "unique_ratio": 0.001299,
+        "example_values": [
+          "16",
+          "1",
+          "2",
+          "5",
+          "4"
+        ]
+      }
+    },
+    {
+      "name": "pdays",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 524,
+        "unique_ratio": 0.014488,
+        "example_values": [
+          "-1",
+          "91",
+          "365",
+          "189",
+          "117"
+        ]
+      }
+    },
+    {
+      "name": "previous",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 38,
+        "unique_ratio": 0.001051,
+        "example_values": [
+          "0",
+          "4",
+          "1",
+          "2",
+          "3"
+        ]
+      }
+    },
+    {
+      "name": "poutcome",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 4,
+        "unique_ratio": 0.000111,
+        "example_values": [
+          "unknown",
+          "failure",
+          "other",
+          "success"
+        ]
+      }
+    },
+    {
+      "name": "y",
+      "role": "target",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 5.5e-05,
+        "example_values": [
+          "no",
+          "yes"
+        ]
+      }
+    }
+  ]
+}

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/realtabformer_features.json

@@ -0,0 +1,87 @@
+[
+  {
+    "feature_name": "age",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
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+    "data_type": "continuous",
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+    "data_type": "continuous",
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+]

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/runtime_result.json

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+{
+  "dataset_id": "m8",
+  "model": "realtabformer",
+  "run_id": "rtf-m8-20260430_214341",
+  "public_gate_status": "pass",
+  "adapter_ready_status": "pass",
+  "train_status": "fail",
+  "generate_status": "skipped",
+  "reason_code": "adapter_runtime_error",
+  "reason_detail": "Command '['docker', 'run', '--rm', '--init', '--cidfile', '/tmp/bench_docker_realtabformer_myvvh160/container.cid', '--gpus', 'device=1', '-e', 'CUDA_VISIBLE_DEVICES=0', '-e', 'NCCL_P2P_DISABLE=1', '-e', 'HOME=/tmp', '-v', '/data/jialinzhang/SynthesizePipeline-server:/work', '-w', '/work/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341', 'benchmark:realtabformer-zjl', 'python', '-m', 'realtabformer.benchmark_cli', '--csv', '/work/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/staged/public/train.csv', '--model-dir', '/work/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/models_100epochs', '--train-only', '--epochs', '100', '--features-json', '/work/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/realtabformer_features.json']' returned non-zero exit status 137.",
+  "artifacts": {},
+  "timings": {
+    "train": {
+      "started_at": "2026-04-30T21:43:42",
+      "ended_at": "2026-04-30T21:44:03",
+      "duration_sec": 21.707
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+}

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/staged/public/staged_features.json

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+[
+  {
+    "feature_name": "age",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "job",
+    "data_type": "categorical",
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+    "data_type": "categorical",
+    "is_target": false
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+    "data_type": "categorical",
+    "is_target": false
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+    "data_type": "binary",
+    "is_target": false
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+    "data_type": "continuous",
+    "is_target": false
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+    "data_type": "binary",
+    "is_target": false
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+    "data_type": "binary",
+    "is_target": false
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+    "feature_name": "contact",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
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+    "data_type": "continuous",
+    "is_target": false
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+  {
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+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "duration",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "campaign",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "pdays",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "previous",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "poutcome",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "y",
+    "data_type": "binary",
+    "is_target": true
+  }
+]

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/staged/public/test.csv

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+size 370991

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/staged/public/train.csv

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+size 2964802

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/staged/public/val.csv

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+size 370535

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/staged/realtabformer/adapter_report.json

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+{
+  "adapter_ready_status": "pass",
+  "adapter_fail_reason_code": null,
+  "adapter_fail_detail": null,
+  "adapter_transforms_applied": [],
+  "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/staged/realtabformer/model_input_manifest.json"
+}

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/staged/realtabformer/adapter_transforms_applied.json

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+[]

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/staged/realtabformer/model_input_manifest.json

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+        "unique_ratio": 0.000332,
+        "example_values": [
+          "admin.",
+          "technician",
+          "entrepreneur",
+          "blue-collar",
+          "services"
+        ]
+      }
+    },
+    {
+      "name": "marital",
+      "role": "feature",
+      "semantic_type": "categorical",
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+        "unique_ratio": 8.3e-05,
+        "example_values": [
+          "single",
+          "married",
+          "divorced"
+        ]
+      }
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+    {
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+  ],
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+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-Benchmark-trainonly-v1/m8/realtabformer/rtf-m8-20260430_214341/public_gate/public_gate_report.json"
+}

syntheticFail/m8/realtabformer/rtf-m8-20260430_214341/train_20260430_214342.log

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syntheticFail/m8/tabsyn/tabsyn-m8-20260501_000347/_tabsyn_train.py

@@ -0,0 +1,65 @@
+import os, sys, subprocess
+
+work_dir = "/work/output-Benchmark-trainonly-v1/m8/tabsyn/tabsyn-m8-20260501_000347"
+dataname = "tabsyn_m8"
+tabsyn_root = "/workspace/tabsyn"
+
+assert os.path.exists(tabsyn_root), f"TabSyn source not mounted: {tabsyn_root}"
+
+old = os.environ.get("PYTHONPATH", "")
+os.environ["PYTHONPATH"] = tabsyn_root + (os.pathsep + old if old else "")
+sys.path.insert(0, tabsyn_root)
+
+os.chdir(tabsyn_root)
+
+# Symlink data dir into TabSyn data/
+data_link = os.path.join(tabsyn_root, "data", dataname)
+data_src = os.path.join(work_dir, "data", dataname)
+os.makedirs(os.path.join(tabsyn_root, "data"), exist_ok=True)
+if os.path.exists(data_link):
+    os.remove(data_link)
+os.symlink(data_src, data_link)
+
+env = os.environ.copy()
+env.setdefault("TABSYN_RESUME", "1")
+env.setdefault("TABSYN_VAE_BATCH_SIZE", "1024")
+# Safer defaults for wide tables on Docker: reduce shared-memory pressure in diffusion DataLoader.
+env.setdefault("TABSYN_DIFFUSION_NUM_WORKERS", "0")
+_te = None
+if _te is not None:
+    env["TABSYN_VAE_EPOCHS"] = str(_te)
+    env["TABSYN_DIFFUSION_MAX_EPOCHS"] = str(max(_te + 1, 2))
+
+# Data preprocessing is done on the host side (_prepare_data_dir)
+# which creates .npy files, train/test CSVs, and info.json
+
+# Step 1: Train VAE (produces latent embeddings)
+print(f"[TabSyn] Step 1/2: Training VAE in {tabsyn_root}, dataname={dataname}")
+ret = subprocess.run(
+    [sys.executable, "main.py",
+     "--dataname", dataname,
+     "--mode", "train",
+     "--method", "vae",
+     "--gpu", "0"],
+    cwd=tabsyn_root,
+    env=env
+)
+if ret.returncode != 0:
+    print("[TabSyn] VAE training failed")
+    sys.exit(ret.returncode)
+
+# Step 2: Train diffusion model on latent space
+print(f"[TabSyn] Step 2/2: Training diffusion model")
+ret = subprocess.run(
+    [sys.executable, "main.py",
+     "--dataname", dataname,
+     "--mode", "train",
+     "--method", "tabsyn",
+     "--gpu", "0"],
+    cwd=tabsyn_root,
+    env=env
+)
+if ret.returncode != 0:
+    print("[TabSyn] Diffusion training failed")
+    sys.exit(ret.returncode)
+print("[TabSyn] Training complete (VAE + Diffusion)")

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+size 1012832

syntheticFail/m8/tabsyn/tabsyn-m8-20260501_000347/data/tabsyn_m8/info.json

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+{
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