Resume SynthData0523 main/c17 batch 3

.gitattributes

@@ -2385,3 +2385,29 @@ SynthData0523/main/c17/tabdiff/tabdiff-c17-20260513_002853/tabular_bundle/pipeli
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SynthData0523/main/c17/tabdiff/tabdiff-c17-20260513_002853/tabular_bundle/pipeline_c17/y_train.npy

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SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/_tabpfgen_generate.py

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+import numpy as np
+import pandas as pd
+import json
+from tabpfgen import TabPFGen
+
+df = pd.read_csv("/work/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/staged/public/train.csv")
+target_col = "type"
+
+feature_cols = [c for c in df.columns if c != target_col]
+
+# --- Label-encode categorical / object columns ---
+cat_encodings = {}  # col -> list of unique values (index = code)
+for col in feature_cols:
+    if df[col].dtype == object or str(df[col].dtype) == 'category':
+        cats = sorted(df[col].dropna().unique().tolist(), key=str)
+        cat_map = {v: i for i, v in enumerate(cats)}
+        df[col] = df[col].map(cat_map).astype(float)
+        cat_encodings[col] = cats
+        print(f"[TabPFGen] Label-encoded '{col}' ({len(cats)} categories)")
+
+# Encode target if categorical
+target_cats = None
+if df[target_col].dtype == object or str(df[target_col].dtype) == 'category':
+    cats = sorted(df[target_col].dropna().unique().tolist(), key=str)
+    t_map = {v: i for i, v in enumerate(cats)}
+    df[target_col] = df[target_col].map(t_map).astype(float)
+    target_cats = cats
+    print(f"[TabPFGen] Label-encoded target '{target_col}' ({len(cats)} categories)")
+
+X = df[feature_cols].values.astype(np.float32)
+y = df[target_col].values
+target_n = int(7045)
+
+# Handle NaN
+for i in range(X.shape[1]):
+    col_vals = X[:, i]
+    mask = np.isnan(col_vals)
+    if mask.any():
+        mean_val = np.nanmean(col_vals)
+        X[mask, i] = mean_val if not np.isnan(mean_val) else 0.0
+
+gen = TabPFGen(
+    n_sgld_steps=1000,
+    sgld_step_size=0.01,
+    sgld_noise_scale=0.01,
+    device="auto",
+)
+
+print(f"[TabPFGen] Generating {target_n} rows via generate_classification")
+X_syn, y_syn = gen.generate_classification(X, y, n_samples=target_n)
+
+syn_df = pd.DataFrame(X_syn, columns=feature_cols)
+syn_df[target_col] = y_syn
+
+# --- Inverse label-encoding for categorical columns ---
+for col, cats in cat_encodings.items():
+    # Round to nearest integer index, clamp to valid range
+    codes = np.round(syn_df[col].values).astype(int)
+    codes = np.clip(codes, 0, len(cats) - 1)
+    syn_df[col] = [cats[c] for c in codes]
+
+if target_cats is not None:
+    codes = np.round(syn_df[target_col].values).astype(int)
+    codes = np.clip(codes, 0, len(target_cats) - 1)
+    syn_df[target_col] = [target_cats[c] for c in codes]
+
+# Ensure output row count is strictly aligned with target_n.
+if len(syn_df) > target_n:
+    print(f"[TabPFGen] Trimming rows: {len(syn_df)} -> {target_n}")
+    syn_df = syn_df.iloc[:target_n].copy()
+elif len(syn_df) < target_n:
+    deficit = target_n - len(syn_df)
+    print(f"[TabPFGen] Padding rows: {len(syn_df)} -> {target_n} (deficit={deficit})")
+    if len(syn_df) > 0:
+        extra = syn_df.sample(n=deficit, replace=True, random_state=42)
+        syn_df = pd.concat([syn_df.reset_index(drop=True), extra.reset_index(drop=True)], ignore_index=True)
+    else:
+        # Defensive fallback: if generator returns empty, bootstrap from training rows.
+        syn_df = df[feature_cols + [target_col]].sample(
+            n=target_n, replace=True, random_state=42
+        ).reset_index(drop=True)
+
+syn_df = syn_df[list(df.columns)]
+if len(syn_df) != target_n:
+    raise RuntimeError(f"[TabPFGen] Row alignment failed: got {len(syn_df)}, expected {target_n}")
+syn_df.to_csv("/work/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/tabpfgen-c17-7045-20260422_191741.csv", index=False)
+print(f"[TabPFGen] Saved {len(syn_df)} rows -> /work/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/tabpfgen-c17-7045-20260422_191741.csv")

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/gen_20260422_191741.log

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SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/input_snapshot.json

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+{
+  "dataset_id": "c17",
+  "model": "tabpfgen",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-train.csv",
+      "exists": true,
+      "size": 2726614,
+      "sha256": "b77d66258f90989c221df405c960fb64e4e947a5369ced2b884002e17e47e1e9"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-val.csv",
+      "exists": true,
+      "size": 342007,
+      "sha256": "d98c48176aedfd33341199220483be09f753ac63f2a63e829d0835286ab577f3"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-test.csv",
+      "exists": true,
+      "size": 339976,
+      "sha256": "e067ef64b2334774f8cc291445c6723301cd374cde1a3db26a51af8da46bda0a"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c17/c17-dataset_profile.json",
+      "exists": true,
+      "size": 6842,
+      "sha256": "75a4478c7d058e9e4753c49ecfa5e7e7764263a853380d2bacbf48401854370e"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c17/c17-dataset_contract_v1.json",
+      "exists": true,
+      "size": 7632,
+      "sha256": "26a27c28d1bb9de6b75ff00efa045708e5a23ea264abb037a6ba47d7e55027fd"
+    }
+  }
+}

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/public_gate/normalized_schema_snapshot.json

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+{
+  "dataset_id": "c17",
+  "target_column": "type",
+  "task_type": "classification",
+  "columns": [
+    {
+      "name": "show_id",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7045,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "s4961",
+          "s5783",
+          "s4235",
+          "s8539",
+          "s2374"
+        ]
+      }
+    },
+    {
+      "name": "type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000284,
+        "example_values": [
+          "Movie",
+          "TV Show"
+        ]
+      }
+    },
+    {
+      "name": "title",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7044,
+        "unique_ratio": 0.999858,
+        "example_values": [
+          "Happy Anniversary",
+          "Amanda Knox",
+          "Gina Yashere: Laughing to America",
+          "The Truth About Alcohol",
+          "Saladin"
+        ]
+      }
+    },
+    {
+      "name": "director",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.299787,
+        "unique_count": 3784,
+        "unique_ratio": 0.767079,
+        "example_values": [
+          "Jared Stern",
+          "Rod Blackhurst, Brian McGinn",
+          "Paul M. Green",
+          "David Briggs",
+          "Youssef Chahine"
+        ]
+      }
+    },
+    {
+      "name": "cast",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.095387,
+        "unique_count": 6179,
+        "unique_ratio": 0.969559,
+        "example_values": [
+          "Noël Wells, Ben Schwartz, Joe Pantoliano, Annie Potts, Rahul Kohli, Kristin Bauer van Straten, David Walton, Leonardo Nam, Kate Berlant",
+          "Gina Yashere",
+          "Javid Abdelmoneim",
+          "Ahmad Mazhar, Salah Zo El Faqqar, Nadia Lotfi, Hamdy Gheith, Laila Fawzy, Omar El-Hariri, Laila Taher, Hussein Riad, Mahmoud El Meleigy, Zaki Tolaimat",
+          "Vikas Vasistha, Sandeep Varanasi, Rag Mayur, Trishara, Munivenkatapa, Uma Yg, Sirivennela Yanamandhala, Sindhu Sreenivasa Murthy"
+        ]
+      }
+    },
+    {
+      "name": "country",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.095529,
+        "unique_count": 621,
+        "unique_ratio": 0.097458,
+        "example_values": [
+          "United States",
+          "Denmark, United States",
+          "United Kingdom",
+          "Egypt",
+          "India"
+        ]
+      }
+    },
+    {
+      "name": "date_added",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.001136,
+        "unique_count": 1593,
+        "unique_ratio": 0.226375,
+        "example_values": [
+          "March 30, 2018",
+          "September 30, 2016",
+          "December 31, 2018",
+          "August 1, 2017",
+          "June 18, 2020"
+        ]
+      }
+    },
+    {
+      "name": "release_year",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 74,
+        "unique_ratio": 0.010504,
+        "example_values": [
+          "2018",
+          "2016",
+          "2013",
+          "1963",
+          "2021"
+        ]
+      }
+    },
+    {
+      "name": "rating",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.000568,
+        "unique_count": 15,
+        "unique_ratio": 0.00213,
+        "example_values": [
+          "TV-MA",
+          "TV-14",
+          "R",
+          "PG",
+          "TV-PG"
+        ]
+      }
+    },
+    {
+      "name": "duration",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.000142,
+        "unique_count": 211,
+        "unique_ratio": 0.029955,
+        "example_values": [
+          "78 min",
+          "92 min",
+          "68 min",
+          "58 min",
+          "194 min"
+        ]
+      }
+    },
+    {
+      "name": "listed_in",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 484,
+        "unique_ratio": 0.068701,
+        "example_values": [
+          "Comedies, Romantic Movies",
+          "Documentaries",
+          "Stand-Up Comedy",
+          "Documentaries, International Movies",
+          "Action & Adventure, Classic Movies, Dramas"
+        ]
+      }
+    },
+    {
+      "name": "description",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7026,
+        "unique_ratio": 0.997303,
+        "example_values": [
+          "A quirky couple spends their three-year dating anniversary looking back at their relationship and contemplating whether they should break up.",
+          "She was twice convicted and acquitted of murder. Amanda Knox and the people closest to her case speak out in this illuminating documentary.",
+          "British comic Gina Yashere takes the stage in San Francisco, where she shares her thoughts on everything from toilet ninjas to her troublesome name.",
+          "Emergency room doctor Javid Abdelmoneim endeavors to learn the truth about alcohol, both its benefits and risks, by exploring the science of drinking.",
+          "The Sultan of Egypt and Syria launches a campaign to retake Jerusalem amid the Crusades."
+        ]
+      }
+    }
+  ]
+}

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/public_gate/public_gate_report.json

@@ -0,0 +1,37 @@
+{
+  "dataset_id": "c17",
+  "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": "type",
+  "task_type": "classification",
+  "input_splits": {
+    "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-test.csv"
+  }
+}

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/public_gate/staged_input_manifest.json

@@ -0,0 +1,261 @@
+{
+  "dataset_id": "c17",
+  "target_column": "type",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/public_gate/public_gate_report.json",
+  "column_schema": [
+    {
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+        "example_values": [
+          "Happy Anniversary",
+          "Amanda Knox",
+          "Gina Yashere: Laughing to America",
+          "The Truth About Alcohol",
+          "Saladin"
+        ]
+      }
+    },
+    {
+      "name": "director",
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+          "Paul M. Green",
+          "David Briggs",
+          "Youssef Chahine"
+        ]
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+      "role": "id",
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+        "example_values": [
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+          "Gina Yashere",
+          "Javid Abdelmoneim",
+          "Ahmad Mazhar, Salah Zo El Faqqar, Nadia Lotfi, Hamdy Gheith, Laila Fawzy, Omar El-Hariri, Laila Taher, Hussein Riad, Mahmoud El Meleigy, Zaki Tolaimat",
+          "Vikas Vasistha, Sandeep Varanasi, Rag Mayur, Trishara, Munivenkatapa, Uma Yg, Sirivennela Yanamandhala, Sindhu Sreenivasa Murthy"
+        ]
+      }
+    },
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+        "unique_count": 621,
+        "unique_ratio": 0.097458,
+        "example_values": [
+          "United States",
+          "Denmark, United States",
+          "United Kingdom",
+          "Egypt",
+          "India"
+        ]
+      }
+    },
+    {
+      "name": "date_added",
+      "role": "feature",
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+          "September 30, 2016",
+          "December 31, 2018",
+          "August 1, 2017",
+          "June 18, 2020"
+        ]
+      }
+    },
+    {
+      "name": "release_year",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
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+      "impute_strategy": "median",
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+          "2018",
+          "2016",
+          "2013",
+          "1963",
+          "2021"
+        ]
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+    {
+      "name": "rating",
+      "role": "feature",
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+      "nullable": true,
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+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.000568,
+        "unique_count": 15,
+        "unique_ratio": 0.00213,
+        "example_values": [
+          "TV-MA",
+          "TV-14",
+          "R",
+          "PG",
+          "TV-PG"
+        ]
+      }
+    },
+    {
+      "name": "duration",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.000142,
+        "unique_count": 211,
+        "unique_ratio": 0.029955,
+        "example_values": [
+          "78 min",
+          "92 min",
+          "68 min",
+          "58 min",
+          "194 min"
+        ]
+      }
+    },
+    {
+      "name": "listed_in",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 484,
+        "unique_ratio": 0.068701,
+        "example_values": [
+          "Comedies, Romantic Movies",
+          "Documentaries",
+          "Stand-Up Comedy",
+          "Documentaries, International Movies",
+          "Action & Adventure, Classic Movies, Dramas"
+        ]
+      }
+    },
+    {
+      "name": "description",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7026,
+        "unique_ratio": 0.997303,
+        "example_values": [
+          "A quirky couple spends their three-year dating anniversary looking back at their relationship and contemplating whether they should break up.",
+          "She was twice convicted and acquitted of murder. Amanda Knox and the people closest to her case speak out in this illuminating documentary.",
+          "British comic Gina Yashere takes the stage in San Francisco, where she shares her thoughts on everything from toilet ninjas to her troublesome name.",
+          "Emergency room doctor Javid Abdelmoneim endeavors to learn the truth about alcohol, both its benefits and risks, by exploring the science of drinking.",
+          "The Sultan of Egypt and Syria launches a campaign to retake Jerusalem amid the Crusades."
+        ]
+      }
+    }
+  ]
+}

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/runner.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:41f8217555cb6fc344e9dad9dcafa98b5bf270783200196ace37b204c3343729
+size 1946

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/runtime_result.json

@@ -0,0 +1,14 @@
+{
+  "dataset_id": "c17",
+  "model": "tabpfgen",
+  "run_id": "c17-migrated-20260422_193053",
+  "public_gate_status": "pass",
+  "adapter_ready_status": "pass",
+  "train_status": "skipped",
+  "generate_status": "success",
+  "reason_code": null,
+  "reason_detail": null,
+  "artifacts": {
+    "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabpfgen/c17-migrated-20260422_193053/tabpfgen-c17-7045-20260422_191741.csv"
+  }
+}

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/staged/public/staged_features.json

@@ -0,0 +1,62 @@
+[
+  {
+    "feature_name": "show_id",
+    "data_type": "ID",
+    "is_target": false
+  },
+  {
+    "feature_name": "type",
+    "data_type": "categorical",
+    "is_target": true
+  },
+  {
+    "feature_name": "title",
+    "data_type": "ID",
+    "is_target": false
+  },
+  {
+    "feature_name": "director",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "cast",
+    "data_type": "ID",
+    "is_target": false
+  },
+  {
+    "feature_name": "country",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "date_added",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "release_year",
+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
+    "feature_name": "rating",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "duration",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "listed_in",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "description",
+    "data_type": "ID",
+    "is_target": false
+  }
+]

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/staged/public/test.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b9f567ce7dc617caa6a1f54059d6e92185996eef4edeee0dc3704c9e7c40bf63
+size 339093

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/staged/public/train.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:788ecf6df79b06c0c0e1c73269eae885e0862c7ad79baf15e72895b3b13032e7
+size 2719568

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/staged/public/val.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:08456e9ce46be6e184eefbd889ca81bd16877e740f0e40c8dbadd4418f95fa86
+size 341126

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/staged/tabpfgen/adapter_report.json

@@ -0,0 +1,7 @@
+{
+  "adapter_ready_status": "pass",
+  "adapter_fail_reason_code": null,
+  "adapter_fail_detail": null,
+  "adapter_transforms_applied": [],
+  "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/staged/tabpfgen/model_input_manifest.json"
+}

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/staged/tabpfgen/adapter_transforms_applied.json

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

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/staged/tabpfgen/model_input_manifest.json

@@ -0,0 +1,263 @@
+{
+  "dataset_id": "c17",
+  "model": "tabpfgen",
+  "target_column": "type",
+  "task_type": "classification",
+  "column_schema": [
+    {
+      "name": "show_id",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7045,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "s4961",
+          "s5783",
+          "s4235",
+          "s8539",
+          "s2374"
+        ]
+      }
+    },
+    {
+      "name": "type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000284,
+        "example_values": [
+          "Movie",
+          "TV Show"
+        ]
+      }
+    },
+    {
+      "name": "title",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7044,
+        "unique_ratio": 0.999858,
+        "example_values": [
+          "Happy Anniversary",
+          "Amanda Knox",
+          "Gina Yashere: Laughing to America",
+          "The Truth About Alcohol",
+          "Saladin"
+        ]
+      }
+    },
+    {
+      "name": "director",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.299787,
+        "unique_count": 3784,
+        "unique_ratio": 0.767079,
+        "example_values": [
+          "Jared Stern",
+          "Rod Blackhurst, Brian McGinn",
+          "Paul M. Green",
+          "David Briggs",
+          "Youssef Chahine"
+        ]
+      }
+    },
+    {
+      "name": "cast",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
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+      "profile_stats": {
+        "missing_rate": 0.095387,
+        "unique_count": 6179,
+        "unique_ratio": 0.969559,
+        "example_values": [
+          "Noël Wells, Ben Schwartz, Joe Pantoliano, Annie Potts, Rahul Kohli, Kristin Bauer van Straten, David Walton, Leonardo Nam, Kate Berlant",
+          "Gina Yashere",
+          "Javid Abdelmoneim",
+          "Ahmad Mazhar, Salah Zo El Faqqar, Nadia Lotfi, Hamdy Gheith, Laila Fawzy, Omar El-Hariri, Laila Taher, Hussein Riad, Mahmoud El Meleigy, Zaki Tolaimat",
+          "Vikas Vasistha, Sandeep Varanasi, Rag Mayur, Trishara, Munivenkatapa, Uma Yg, Sirivennela Yanamandhala, Sindhu Sreenivasa Murthy"
+        ]
+      }
+    },
+    {
+      "name": "country",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.095529,
+        "unique_count": 621,
+        "unique_ratio": 0.097458,
+        "example_values": [
+          "United States",
+          "Denmark, United States",
+          "United Kingdom",
+          "Egypt",
+          "India"
+        ]
+      }
+    },
+    {
+      "name": "date_added",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.001136,
+        "unique_count": 1593,
+        "unique_ratio": 0.226375,
+        "example_values": [
+          "March 30, 2018",
+          "September 30, 2016",
+          "December 31, 2018",
+          "August 1, 2017",
+          "June 18, 2020"
+        ]
+      }
+    },
+    {
+      "name": "release_year",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 74,
+        "unique_ratio": 0.010504,
+        "example_values": [
+          "2018",
+          "2016",
+          "2013",
+          "1963",
+          "2021"
+        ]
+      }
+    },
+    {
+      "name": "rating",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.000568,
+        "unique_count": 15,
+        "unique_ratio": 0.00213,
+        "example_values": [
+          "TV-MA",
+          "TV-14",
+          "R",
+          "PG",
+          "TV-PG"
+        ]
+      }
+    },
+    {
+      "name": "duration",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.000142,
+        "unique_count": 211,
+        "unique_ratio": 0.029955,
+        "example_values": [
+          "78 min",
+          "92 min",
+          "68 min",
+          "58 min",
+          "194 min"
+        ]
+      }
+    },
+    {
+      "name": "listed_in",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 484,
+        "unique_ratio": 0.068701,
+        "example_values": [
+          "Comedies, Romantic Movies",
+          "Documentaries",
+          "Stand-Up Comedy",
+          "Documentaries, International Movies",
+          "Action & Adventure, Classic Movies, Dramas"
+        ]
+      }
+    },
+    {
+      "name": "description",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7026,
+        "unique_ratio": 0.997303,
+        "example_values": [
+          "A quirky couple spends their three-year dating anniversary looking back at their relationship and contemplating whether they should break up.",
+          "She was twice convicted and acquitted of murder. Amanda Knox and the people closest to her case speak out in this illuminating documentary.",
+          "British comic Gina Yashere takes the stage in San Francisco, where she shares her thoughts on everything from toilet ninjas to her troublesome name.",
+          "Emergency room doctor Javid Abdelmoneim endeavors to learn the truth about alcohol, both its benefits and risks, by exploring the science of drinking.",
+          "The Sultan of Egypt and Syria launches a campaign to retake Jerusalem amid the Crusades."
+        ]
+      }
+    }
+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_191739/c17/public_gate/public_gate_report.json"
+}

SynthData0523/main/c17/tabpfgen/c17-migrated-20260422_193053/tabpfgen-c17-7045-20260422_191741.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8931fb9649665d80ec74266cdfdd64c3b6972fe7f21acbd96f3b6c28364523e1
+size 2953056

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/_tabsyn_sample.py

@@ -0,0 +1,39 @@
+import os, sys, subprocess
+
+work_dir = "/work/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054"
+dataname = "tabsyn_c17"
+output_csv = "/work/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/tabsyn-c17-7045-20260426_204828.csv"
+tabsyn_root = "/workspace/tabsyn"
+
+assert os.path.exists(tabsyn_root), f"TabSyn source not mounted: {tabsyn_root}"
+
+old = os.environ.get("PYTHONPATH", "")
+os.environ["PYTHONPATH"] = tabsyn_root + (os.pathsep + old if old else "")
+sys.path.insert(0, tabsyn_root)
+
+os.chdir(tabsyn_root)
+
+# Ensure data symlink exists
+data_link = os.path.join(tabsyn_root, "data", dataname)
+data_src = os.path.join(work_dir, "data", dataname)
+os.makedirs(os.path.join(tabsyn_root, "data"), exist_ok=True)
+if os.path.exists(data_link):
+    os.remove(data_link)
+os.symlink(data_src, data_link)
+
+print(f"[TabSyn] Sampling 7045 rows")
+env = os.environ.copy()
+env.setdefault("TABSYN_RESUME", "1")
+ret = subprocess.run(
+    [sys.executable, "main.py",
+     "--dataname", dataname,
+     "--mode", "sample",
+     "--method", "tabsyn",
+     "--gpu", "0",
+     "--save_path", output_csv],
+    cwd=tabsyn_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+print(f"[TabSyn] Saved -> {output_csv}")

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/_tabsyn_train.py

@@ -0,0 +1,63 @@
+import os, sys, subprocess
+
+work_dir = "/work/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054"
+dataname = "tabsyn_c17"
+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")
+_te = 1000
+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)")

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/data/tabsyn_c17/X_cat_test.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:38622a3f3a1e35236e5025830a78f6a5527e618297d12a54fcd90eadcd2a1abd
+size 563728

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/data/tabsyn_c17/X_cat_train.npy

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+size 563728

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/data/tabsyn_c17/X_num_test.npy

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+version https://git-lfs.github.com/spec/v1
+oid sha256:180312a3459bb0e4407a488c06d2c96ccc4d186b7a9ec1cb7de230e903b862db
+size 28308

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/data/tabsyn_c17/X_num_train.npy

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+size 28308

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/data/tabsyn_c17/info.json

@@ -0,0 +1,129 @@
+{
+  "name": "tabsyn_c17",
+  "task_type": "multiclass",
+  "n_num_features": 1,
+  "n_cat_features": 10,
+  "train_size": 7045,
+  "num_col_idx": [
+    7
+  ],
+  "cat_col_idx": [
+    0,
+    2,
+    3,
+    4,
+    5,
+    6,
+    8,
+    9,
+    10,
+    11
+  ],
+  "target_col_idx": [
+    1
+  ],
+  "column_names": [
+    "show_id",
+    "type",
+    "title",
+    "director",
+    "cast",
+    "country",
+    "date_added",
+    "release_year",
+    "rating",
+    "duration",
+    "listed_in",
+    "description"
+  ],
+  "train_num": 7045,
+  "test_num": 7045,
+  "header": 0,
+  "file_type": "csv",
+  "data_path": "data/tabsyn_c17/train.csv",
+  "test_path": null,
+  "idx_mapping": {
+    "0": 1,
+    "1": 11,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "7": 0,
+    "8": 7,
+    "9": 8,
+    "10": 9,
+    "11": 10
+  },
+  "inverse_idx_mapping": {
+    "1": 0,
+    "11": 1,
+    "2": 2,
+    "3": 3,
+    "4": 4,
+    "5": 5,
+    "6": 6,
+    "0": 7,
+    "7": 8,
+    "8": 9,
+    "9": 10,
+    "10": 11
+  },
+  "idx_name_mapping": {
+    "0": "show_id",
+    "1": "type",
+    "2": "title",
+    "3": "director",
+    "4": "cast",
+    "5": "country",
+    "6": "date_added",
+    "7": "release_year",
+    "8": "rating",
+    "9": "duration",
+    "10": "listed_in",
+    "11": "description"
+  },
+  "n_classes": 2,
+  "metadata": {
+    "columns": {
+      "7": {
+        "sdtype": "numerical",
+        "computer_representation": "Float"
+      },
+      "0": {
+        "sdtype": "categorical"
+      },
+      "2": {
+        "sdtype": "categorical"
+      },
+      "3": {
+        "sdtype": "categorical"
+      },
+      "4": {
+        "sdtype": "categorical"
+      },
+      "5": {
+        "sdtype": "categorical"
+      },
+      "6": {
+        "sdtype": "categorical"
+      },
+      "8": {
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+      },
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+      },
+      "10": {
+        "sdtype": "categorical"
+      },
+      "11": {
+        "sdtype": "categorical"
+      },
+      "1": {
+        "sdtype": "categorical"
+      }
+    }
+  }
+}

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/data/tabsyn_c17/test.csv

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+size 314091

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/data/tabsyn_c17/train.csv

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+size 314091

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/data/tabsyn_c17/y_test.npy

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+size 56488

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/data/tabsyn_c17/y_train.npy

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SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/gen_20260426_204828.log

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+size 672

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/input_snapshot.json

@@ -0,0 +1,36 @@
+{
+  "dataset_id": "c17",
+  "model": "tabsyn",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-train.csv",
+      "exists": true,
+      "size": 2726614,
+      "sha256": "b77d66258f90989c221df405c960fb64e4e947a5369ced2b884002e17e47e1e9"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-val.csv",
+      "exists": true,
+      "size": 342007,
+      "sha256": "d98c48176aedfd33341199220483be09f753ac63f2a63e829d0835286ab577f3"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-test.csv",
+      "exists": true,
+      "size": 339976,
+      "sha256": "e067ef64b2334774f8cc291445c6723301cd374cde1a3db26a51af8da46bda0a"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c17/c17-dataset_profile.json",
+      "exists": true,
+      "size": 6842,
+      "sha256": "75a4478c7d058e9e4753c49ecfa5e7e7764263a853380d2bacbf48401854370e"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/c17/c17-dataset_contract_v1.json",
+      "exists": true,
+      "size": 7632,
+      "sha256": "26a27c28d1bb9de6b75ff00efa045708e5a23ea264abb037a6ba47d7e55027fd"
+    }
+  }
+}

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/public_gate/normalized_schema_snapshot.json

@@ -0,0 +1,256 @@
+{
+  "dataset_id": "c17",
+  "target_column": "type",
+  "task_type": "classification",
+  "columns": [
+    {
+      "name": "show_id",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7045,
+        "unique_ratio": 1.0,
+        "example_values": [
+          "s4961",
+          "s5783",
+          "s4235",
+          "s8539",
+          "s2374"
+        ]
+      }
+    },
+    {
+      "name": "type",
+      "role": "target",
+      "semantic_type": "categorical",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 2,
+        "unique_ratio": 0.000284,
+        "example_values": [
+          "Movie",
+          "TV Show"
+        ]
+      }
+    },
+    {
+      "name": "title",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7044,
+        "unique_ratio": 0.999858,
+        "example_values": [
+          "Happy Anniversary",
+          "Amanda Knox",
+          "Gina Yashere: Laughing to America",
+          "The Truth About Alcohol",
+          "Saladin"
+        ]
+      }
+    },
+    {
+      "name": "director",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.299787,
+        "unique_count": 3784,
+        "unique_ratio": 0.767079,
+        "example_values": [
+          "Jared Stern",
+          "Rod Blackhurst, Brian McGinn",
+          "Paul M. Green",
+          "David Briggs",
+          "Youssef Chahine"
+        ]
+      }
+    },
+    {
+      "name": "cast",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": true,
+      "missing_tokens": [],
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+        "unique_count": 6179,
+        "unique_ratio": 0.969559,
+        "example_values": [
+          "Noël Wells, Ben Schwartz, Joe Pantoliano, Annie Potts, Rahul Kohli, Kristin Bauer van Straten, David Walton, Leonardo Nam, Kate Berlant",
+          "Gina Yashere",
+          "Javid Abdelmoneim",
+          "Ahmad Mazhar, Salah Zo El Faqqar, Nadia Lotfi, Hamdy Gheith, Laila Fawzy, Omar El-Hariri, Laila Taher, Hussein Riad, Mahmoud El Meleigy, Zaki Tolaimat",
+          "Vikas Vasistha, Sandeep Varanasi, Rag Mayur, Trishara, Munivenkatapa, Uma Yg, Sirivennela Yanamandhala, Sindhu Sreenivasa Murthy"
+        ]
+      }
+    },
+    {
+      "name": "country",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
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+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.095529,
+        "unique_count": 621,
+        "unique_ratio": 0.097458,
+        "example_values": [
+          "United States",
+          "Denmark, United States",
+          "United Kingdom",
+          "Egypt",
+          "India"
+        ]
+      }
+    },
+    {
+      "name": "date_added",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
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+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.001136,
+        "unique_count": 1593,
+        "unique_ratio": 0.226375,
+        "example_values": [
+          "March 30, 2018",
+          "September 30, 2016",
+          "December 31, 2018",
+          "August 1, 2017",
+          "June 18, 2020"
+        ]
+      }
+    },
+    {
+      "name": "release_year",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
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+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 74,
+        "unique_ratio": 0.010504,
+        "example_values": [
+          "2018",
+          "2016",
+          "2013",
+          "1963",
+          "2021"
+        ]
+      }
+    },
+    {
+      "name": "rating",
+      "role": "feature",
+      "semantic_type": "categorical",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.000568,
+        "unique_count": 15,
+        "unique_ratio": 0.00213,
+        "example_values": [
+          "TV-MA",
+          "TV-14",
+          "R",
+          "PG",
+          "TV-PG"
+        ]
+      }
+    },
+    {
+      "name": "duration",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.000142,
+        "unique_count": 211,
+        "unique_ratio": 0.029955,
+        "example_values": [
+          "78 min",
+          "92 min",
+          "68 min",
+          "58 min",
+          "194 min"
+        ]
+      }
+    },
+    {
+      "name": "listed_in",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 484,
+        "unique_ratio": 0.068701,
+        "example_values": [
+          "Comedies, Romantic Movies",
+          "Documentaries",
+          "Stand-Up Comedy",
+          "Documentaries, International Movies",
+          "Action & Adventure, Classic Movies, Dramas"
+        ]
+      }
+    },
+    {
+      "name": "description",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "keep_raw",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 7026,
+        "unique_ratio": 0.997303,
+        "example_values": [
+          "A quirky couple spends their three-year dating anniversary looking back at their relationship and contemplating whether they should break up.",
+          "She was twice convicted and acquitted of murder. Amanda Knox and the people closest to her case speak out in this illuminating documentary.",
+          "British comic Gina Yashere takes the stage in San Francisco, where she shares her thoughts on everything from toilet ninjas to her troublesome name.",
+          "Emergency room doctor Javid Abdelmoneim endeavors to learn the truth about alcohol, both its benefits and risks, by exploring the science of drinking.",
+          "The Sultan of Egypt and Syria launches a campaign to retake Jerusalem amid the Crusades."
+        ]
+      }
+    }
+  ]
+}

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/public_gate/public_gate_report.json

@@ -0,0 +1,37 @@
+{
+  "dataset_id": "c17",
+  "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": "type",
+  "task_type": "classification",
+  "input_splits": {
+    "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/c17/c17-test.csv"
+  }
+}

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/public_gate/staged_input_manifest.json

@@ -0,0 +1,261 @@
+{
+  "dataset_id": "c17",
+  "target_column": "type",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/public_gate/public_gate_report.json",
+  "column_schema": [
+    {
+      "name": "show_id",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
+      "missing_tokens": [],
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+      "impute_strategy": "keep_raw",
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+        "unique_ratio": 1.0,
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+          "s8539",
+          "s2374"
+        ]
+      }
+    },
+    {
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+      "role": "target",
+      "semantic_type": "categorical",
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+        "example_values": [
+          "Movie",
+          "TV Show"
+        ]
+      }
+    },
+    {
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+          "Gina Yashere",
+          "Javid Abdelmoneim",
+          "Ahmad Mazhar, Salah Zo El Faqqar, Nadia Lotfi, Hamdy Gheith, Laila Fawzy, Omar El-Hariri, Laila Taher, Hussein Riad, Mahmoud El Meleigy, Zaki Tolaimat",
+          "Vikas Vasistha, Sandeep Varanasi, Rag Mayur, Trishara, Munivenkatapa, Uma Yg, Sirivennela Yanamandhala, Sindhu Sreenivasa Murthy"
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+      "role": "feature",
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+        ]
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+          "She was twice convicted and acquitted of murder. Amanda Knox and the people closest to her case speak out in this illuminating documentary.",
+          "British comic Gina Yashere takes the stage in San Francisco, where she shares her thoughts on everything from toilet ninjas to her troublesome name.",
+          "Emergency room doctor Javid Abdelmoneim endeavors to learn the truth about alcohol, both its benefits and risks, by exploring the science of drinking.",
+          "The Sultan of Egypt and Syria launches a campaign to retake Jerusalem amid the Crusades."
+        ]
+      }
+    }
+  ]
+}

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/runtime_result.json

@@ -0,0 +1,15 @@
+{
+  "dataset_id": "c17",
+  "model": "tabsyn",
+  "run_id": "tabsyn-c17-20260426_203054",
+  "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/c17/tabsyn/tabsyn-c17-20260426_203054/tabsyn-c17-7045-20260426_204828.csv",
+    "model_path": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054"
+  }
+}

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/staged_features.json

@@ -0,0 +1,62 @@
+[
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+    "data_type": "ID",
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+    "data_type": "categorical",
+    "is_target": true
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+    "feature_name": "title",
+    "data_type": "ID",
+    "is_target": false
+  },
+  {
+    "feature_name": "director",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "cast",
+    "data_type": "ID",
+    "is_target": false
+  },
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+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
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+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "release_year",
+    "data_type": "continuous",
+    "is_target": false
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+  {
+    "feature_name": "rating",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "duration",
+    "data_type": "categorical",
+    "is_target": false
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+  {
+    "feature_name": "listed_in",
+    "data_type": "categorical",
+    "is_target": false
+  },
+  {
+    "feature_name": "description",
+    "data_type": "ID",
+    "is_target": false
+  }
+]

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/test.csv

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+size 339093

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/train.csv

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+oid sha256:788ecf6df79b06c0c0e1c73269eae885e0862c7ad79baf15e72895b3b13032e7
+size 2719568

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/val.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:08456e9ce46be6e184eefbd889ca81bd16877e740f0e40c8dbadd4418f95fa86
+size 341126

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/staged/tabsyn/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/c17/tabsyn/tabsyn-c17-20260426_203054/staged/tabsyn/model_input_manifest.json"
+}

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/staged/tabsyn/adapter_transforms_applied.json

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

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/staged/tabsyn/model_input_manifest.json

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+{
+  "dataset_id": "c17",
+  "model": "tabsyn",
+  "target_column": "type",
+  "task_type": "classification",
+  "column_schema": [
+    {
+      "name": "show_id",
+      "role": "id",
+      "semantic_type": "id",
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+        "unique_ratio": 1.0,
+        "example_values": [
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+          "s4235",
+          "s8539",
+          "s2374"
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+    {
+      "name": "type",
+      "role": "target",
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+      "profile_stats": {
+        "missing_rate": 0.0,
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+        "unique_ratio": 0.000284,
+        "example_values": [
+          "Movie",
+          "TV Show"
+        ]
+      }
+    },
+    {
+      "name": "title",
+      "role": "id",
+      "semantic_type": "id",
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+      "missing_tokens": [],
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+        "unique_ratio": 0.999858,
+        "example_values": [
+          "Happy Anniversary",
+          "Amanda Knox",
+          "Gina Yashere: Laughing to America",
+          "The Truth About Alcohol",
+          "Saladin"
+        ]
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+          "Paul M. Green",
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+          "Vikas Vasistha, Sandeep Varanasi, Rag Mayur, Trishara, Munivenkatapa, Uma Yg, Sirivennela Yanamandhala, Sindhu Sreenivasa Murthy"
+        ]
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+          "Egypt",
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+          "2018",
+          "2016",
+          "2013",
+          "1963",
+          "2021"
+        ]
+      }
+    },
+    {
+      "name": "rating",
+      "role": "feature",
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+        "example_values": [
+          "TV-MA",
+          "TV-14",
+          "R",
+          "PG",
+          "TV-PG"
+        ]
+      }
+    },
+    {
+      "name": "duration",
+      "role": "feature",
+      "semantic_type": "text",
+      "nullable": true,
+      "missing_tokens": [],
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+          "78 min",
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+          "68 min",
+          "58 min",
+          "194 min"
+        ]
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+    },
+    {
+      "name": "listed_in",
+      "role": "feature",
+      "semantic_type": "text",
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+      "missing_tokens": [],
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+      "profile_stats": {
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+        "example_values": [
+          "Comedies, Romantic Movies",
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+          "Stand-Up Comedy",
+          "Documentaries, International Movies",
+          "Action & Adventure, Classic Movies, Dramas"
+        ]
+      }
+    },
+    {
+      "name": "description",
+      "role": "id",
+      "semantic_type": "id",
+      "nullable": false,
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+        "unique_ratio": 0.997303,
+        "example_values": [
+          "A quirky couple spends their three-year dating anniversary looking back at their relationship and contemplating whether they should break up.",
+          "She was twice convicted and acquitted of murder. Amanda Knox and the people closest to her case speak out in this illuminating documentary.",
+          "British comic Gina Yashere takes the stage in San Francisco, where she shares her thoughts on everything from toilet ninjas to her troublesome name.",
+          "Emergency room doctor Javid Abdelmoneim endeavors to learn the truth about alcohol, both its benefits and risks, by exploring the science of drinking.",
+          "The Sultan of Egypt and Syria launches a campaign to retake Jerusalem amid the Crusades."
+        ]
+      }
+    }
+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c17/tabsyn/tabsyn-c17-20260426_203054/public_gate/public_gate_report.json"
+}

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/synthetic/tabsyn_c17/real.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d7f6aabfa7f5a789e39dad7bc260eed625d811b036261b6855755ab504525a69
+size 314091

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/synthetic/tabsyn_c17/test.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d7f6aabfa7f5a789e39dad7bc260eed625d811b036261b6855755ab504525a69
+size 314091

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/tabsyn-c17-7045-20260426_204828.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:97b2d6c7eb690f138d227cda813d7b37a401c644cb691fcbf33cfa1080a434ea
+size 389146

SynthData0523/main/c17/tabsyn/tabsyn-c17-20260426_203054/train_20260426_203055.log

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+version https://git-lfs.github.com/spec/v1
+oid sha256:602fea9eac17bddd28b73dd4e73a99fe826d7757cb213adb780ffc7bfeabacaa
+size 902896

SynthData0523/main/c17/tvae/tvae-c17-20260328_052612/_tvae_generate.py

@@ -0,0 +1,5 @@
+from ctgan.synthesizers.tvae import TVAE
+model = TVAE.load("/work/output-SpecializedModels/c17/tvae/tvae-c17-20260328_052612/models_300epochs/tvae_300epochs.pt")
+samples = model.sample(7045)
+samples.to_csv("/work/output-SpecializedModels/c17/tvae/tvae-c17-20260328_052612/tvae-c17-7045-20260330_065440.csv", index=False)
+print(f"[TVAE] Generated 7045 rows -> /work/output-SpecializedModels/c17/tvae/tvae-c17-20260328_052612/tvae-c17-7045-20260330_065440.csv")

SynthData0523/main/c17/tvae/tvae-c17-20260328_052612/_tvae_train.py

@@ -0,0 +1,16 @@
+import json, sys
+import pandas as pd
+from ctgan.data import read_csv
+from ctgan.synthesizers.tvae import TVAE
+
+csv_path = "/work/output-SpecializedModels/c17/tvae/tvae-c17-20260328_052612/staged/public/train.csv"
+meta_path = "/work/output-SpecializedModels/c17/tvae/tvae-c17-20260328_052612/tvae_metadata.json"
+save_path = "/work/output-SpecializedModels/c17/tvae/tvae-c17-20260328_052612/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}")