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diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/_tabddpm_sample.py b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/_tabddpm_sample.py
new file mode 100644
index 0000000000000000000000000000000000000000..c2cd2aac67ffc33ccf2a00adde62a0c8269cdf3f
--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/_tabddpm_sample.py
@@ -0,0 +1,67 @@
+import os, sys, subprocess, json
+import numpy as np
+import pandas as pd
+
+tabddpm_root = "/workspace/tabddpm/code"
+assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}"
+env = os.environ.copy()
+env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", ""))
+
+# Reuse the compat wrapper (patches collections.Sequence for skorch)
+wrapper = os.path.join(tabddpm_root, "_compat_run.py")
+if not os.path.exists(wrapper):
+    with open(wrapper, "w") as f:
+        f.write(
+            "import collections, collections.abc\n"
+            "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping',"
+            "'MutableSet','Set','Callable','Iterable','Iterator'):\n"
+            "    if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n"
+            "import sys, runpy\n"
+            "sys.argv = sys.argv[1:]\n"
+            "runpy.run_path(sys.argv[0], run_name='__main__')\n"
+        )
+
+print(f"[TabDDPM] Sampling 3680 rows")
+ret = subprocess.run(
+    [sys.executable, wrapper, "scripts/pipeline.py",
+     "--config", "/work/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/config_sample_20260424_034040.toml",
+     "--sample"],
+    cwd=tabddpm_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+
+# 将 .npy 输出转为 CSV
+work_dir = "/work/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725"
+info_path = os.path.join(work_dir, "data", "info.json")
+with open(info_path) as f:
+    info = json.load(f)
+
+output_dir = os.path.join(work_dir, "output")
+col_names = info.get("column_names", [])
+
+parts = []
+x_num_path = os.path.join(output_dir, "X_num_train.npy")
+x_cat_path = os.path.join(output_dir, "X_cat_train.npy")
+y_path = os.path.join(output_dir, "y_train.npy")
+
+if os.path.exists(x_num_path):
+    parts.append(np.load(x_num_path, allow_pickle=True))
+if os.path.exists(x_cat_path):
+    parts.append(np.load(x_cat_path, allow_pickle=True).astype(float))
+if os.path.exists(y_path):
+    y = np.load(y_path, allow_pickle=True)
+    parts.append(y.reshape(-1, 1) if y.ndim == 1 else y)
+
+if parts:
+    combined = np.concatenate(parts, axis=1)
+    if col_names and len(col_names) == combined.shape[1]:
+        df = pd.DataFrame(combined, columns=col_names)
+    else:
+        df = pd.DataFrame(combined)
+    df.to_csv("/work/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/tabddpm-n1-3680-20260424_034040.csv", index=False)
+    print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/tabddpm-n1-3680-20260424_034040.csv")
+else:
+    print("[TabDDPM] WARNING: No output .npy files found")
+    sys.exit(1)
diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/_tabddpm_train.py b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/_tabddpm_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..a556af0e39409e05101083466777998c58776660
--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/_tabddpm_train.py
@@ -0,0 +1,32 @@
+import os, sys, subprocess
+
+tabddpm_root = "/workspace/tabddpm/code"
+assert os.path.isdir(tabddpm_root), f"TabDDPM source not mounted: {tabddpm_root}"
+env = os.environ.copy()
+env["PYTHONPATH"] = tabddpm_root + (os.pathsep + env.get("PYTHONPATH", ""))
+
+# Write a wrapper that patches collections.Sequence (removed in Python 3.10+)
+# before running pipeline.py - needed because skorch uses old API
+wrapper = os.path.join(tabddpm_root, "_compat_run.py")
+with open(wrapper, "w") as f:
+    f.write(
+        "import collections, collections.abc\n"
+        "for _a in ('Sequence','MutableSequence','MutableMapping','Mapping',"
+        "'MutableSet','Set','Callable','Iterable','Iterator'):\n"
+        "    if not hasattr(collections, _a): setattr(collections, _a, getattr(collections.abc, _a, None))\n"
+        "import sys, runpy\n"
+        "sys.argv = sys.argv[1:]\n"
+        "runpy.run_path(sys.argv[0], run_name='__main__')\n"
+    )
+
+print(f"[TabDDPM] Training, config=/work/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/config.toml")
+ret = subprocess.run(
+    [sys.executable, wrapper, "scripts/pipeline.py",
+     "--config", "/work/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/config.toml",
+     "--train"],
+    cwd=tabddpm_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+print("[TabDDPM] Training complete")
diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/config.toml b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/config.toml
new file mode 100644
index 0000000000000000000000000000000000000000..219790b84251a8d0952e1698c4eef3034b53ecfc
--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/config.toml
@@ -0,0 +1,39 @@
+seed = 0
+parent_dir = "/work/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/output"
+real_data_path = "/work/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/data"
+model_type = "mlp"
+num_numerical_features = 54
+device = "cuda:0"
+
+[model_params]
+d_in = 57
+num_classes = 2
+is_y_cond = true
+
+[model_params.rtdl_params]
+d_layers = [256, 256]
+dropout = 0.0
+
+[diffusion_params]
+num_timesteps = 1000
+gaussian_loss_type = "mse"
+
+[train.main]
+steps = 5000
+lr = 0.001
+weight_decay = 0.0
+batch_size = 256
+
+[train.T]
+seed = 0
+normalization = "quantile"
+num_nan_policy = "__none__"
+cat_nan_policy = "__none__"
+cat_min_frequency = "__none__"
+cat_encoding = "__none__"
+y_policy = "default"
+
+[sample]
+num_samples = 1000
+batch_size = 1000
+seed = 0
diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/config_sample_20260424_034040.toml b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/config_sample_20260424_034040.toml
new file mode 100644
index 0000000000000000000000000000000000000000..75726adae15119890f24ff3bdfc344c2c7681d80
--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/config_sample_20260424_034040.toml
@@ -0,0 +1,39 @@
+seed = 0
+parent_dir = "/work/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/output"
+real_data_path = "/work/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/data"
+model_type = "mlp"
+num_numerical_features = 54
+device = "cuda:0"
+
+[model_params]
+d_in = 57
+num_classes = 2
+is_y_cond = true
+
+[model_params.rtdl_params]
+d_layers = [256, 256]
+dropout = 0.0
+
+[diffusion_params]
+num_timesteps = 1000
+gaussian_loss_type = "mse"
+
+[train.main]
+steps = 5000
+lr = 0.001
+weight_decay = 0.0
+batch_size = 256
+
+[train.T]
+seed = 0
+normalization = "quantile"
+num_nan_policy = "__none__"
+cat_nan_policy = "__none__"
+cat_min_frequency = "__none__"
+cat_encoding = "__none__"
+y_policy = "default"
+
+[sample]
+num_samples = 3680
+batch_size = 1000
+seed = 0
diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/data/X_cat_train.npy b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/data/X_cat_train.npy
new file mode 100644
index 0000000000000000000000000000000000000000..f2fcae0340daa12501ab993b46b5430df3c2ff04
--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/data/X_cat_train.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 88448
diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/data/X_num_train.npy b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/data/X_num_train.npy
new file mode 100644
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+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/data/X_num_train.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/data/info.json b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/data/info.json
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index 0000000000000000000000000000000000000000..82b950a489d9d2635967b6fc67eac35e41e5013f
--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/data/info.json
@@ -0,0 +1,132 @@
+{
+  "name": "benchmark_dataset",
+  "task_type": "multiclass",
+  "n_num_features": 54,
+  "n_cat_features": 3,
+  "train_size": 3680,
+  "num_col_idx": [
+    0,
+    1,
+    2,
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+  ],
+  "cat_col_idx": [
+    54,
+    55,
+    56
+  ],
+  "target_col_idx": [
+    57
+  ],
+  "column_names": [
+    "word_freq_make",
+    "word_freq_address",
+    "word_freq_all",
+    "word_freq_our",
+    "word_freq_over",
+    "word_freq_remove",
+    "word_freq_internet",
+    "word_freq_order",
+    "word_freq_mail",
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+is_y_cond = true
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+[model_params.rtdl_params]
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+[diffusion_params]
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+[train.main]
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+[train.T]
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+      "role": "target",
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+    }
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+}
\ No newline at end of file
diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/public_gate/public_gate_report.json b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/public_gate/public_gate_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..76005f0c0dbdfe7ac411d1fdc1e546fbaa201fc6
--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/public_gate/public_gate_report.json
@@ -0,0 +1,37 @@
+{
+  "dataset_id": "n1",
+  "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": "class",
+  "task_type": "classification",
+  "input_splits": {
+    "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-test.csv"
+  }
+}
\ No newline at end of file
diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/public_gate/staged_input_manifest.json b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/public_gate/staged_input_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..00927ecc706b189e3fdd1eddd7bb6bf4215461f3
--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/public_gate/staged_input_manifest.json
@@ -0,0 +1,1227 @@
+{
+  "dataset_id": "n1",
+  "target_column": "class",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/public_gate/public_gate_report.json",
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+}
\ No newline at end of file
diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/runtime_result.json b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/runtime_result.json
new file mode 100644
index 0000000000000000000000000000000000000000..4b5869a671225d8dbbe27a7b878df9dd62ae7fad
--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/runtime_result.json
@@ -0,0 +1,15 @@
+{
+  "dataset_id": "n1",
+  "model": "tabddpm",
+  "run_id": "tabddpm-n1-20260424_033725",
+  "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/n1/tabddpm/tabddpm-n1-20260424_033725/tabddpm-n1-3680-20260424_034040.csv",
+    "model_path": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725"
+  }
+}
\ No newline at end of file
diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/staged/public/staged_features.json b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/staged/public/staged_features.json
new file mode 100644
index 0000000000000000000000000000000000000000..16ebac833523b22ee360679df21047245d9559cc
--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/staged/public/staged_features.json
@@ -0,0 +1,292 @@
+[
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+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
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+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
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+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
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+    "data_type": "binary",
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+  },
+  {
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+    "data_type": "continuous",
+    "is_target": false
+  },
+  {
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+    "data_type": "continuous",
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+  },
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+  },
+  {
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+    "data_type": "continuous",
+    "is_target": false
+  },
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+  {
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+  {
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+  {
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+  },
+  {
+    "feature_name": "word_freq_business",
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+  {
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+  {
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+  },
+  {
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+  },
+  {
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+  },
+  {
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+  },
+  {
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+    "data_type": "continuous",
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+  },
+  {
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+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tabddpm/tabddpm-n1-20260424_033725/public_gate/public_gate_report.json"
+}
\ No newline at end of file
diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/tabddpm-n1-3680-20260424_034040.csv b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/tabddpm-n1-3680-20260424_034040.csv
new file mode 100644
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--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/tabddpm-n1-3680-20260424_034040.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:91e3710a1a3cf3970eec090622cdb733a5f94940adead93948ede6eaea80690f
+size 1947744
diff --git a/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/train_20260424_033725.log b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/train_20260424_033725.log
new file mode 100644
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--- /dev/null
+++ b/SynthData0523/main/n1/tabddpm/tabddpm-n1-20260424_033725/train_20260424_033725.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 831
diff --git a/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/_tabdiff_gen.py b/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/_tabdiff_gen.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc4c961c19a01587156591ea51d10f5454d572fc
--- /dev/null
+++ b/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/_tabdiff_gen.py
@@ -0,0 +1,36 @@
+
+import os, shutil, subprocess, sys
+td = r"/workspace/TabDiff"
+name = r"pipeline_n1"
+src = r"/work/output-Benchmark-trainonly-v1/n1/tabdiff/tabdiff-n1-20260501_175031/tabular_bundle/pipeline_n1"
+dst_data = os.path.join(td, "data", name)
+dst_syn = os.path.join(td, "synthetic", name)
+shutil.rmtree(dst_data, ignore_errors=True)
+shutil.copytree(src, dst_data)
+os.makedirs(dst_syn, exist_ok=True)
+for fn in ("real.csv", "test.csv", "val.csv"):
+    shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn))
+os.chdir(td)
+os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "")
+subprocess.check_call([
+    sys.executable, "-m", "tabdiff.main",
+    "--dataname", name, "--mode", "test", "--gpu", "0",
+    "--no_wandb", "--exp_name", r"adapter_learnable",
+    "--ckpt_path", r"/workspace/TabDiff/tabdiff/ckpt/pipeline_n1/adapter_learnable/model_500.pt",
+    "--num_samples_to_generate", str(int(3680)),
+])
+# test() 写入 tabdiff/result/<dataname>/<exp>/<epoch>/samples.csv
+import glob as g
+base = os.path.join(td, "tabdiff", "result", name, r"adapter_learnable")
+best = None
+best_t = -1.0
+for root, _, files in os.walk(base):
+    if "samples.csv" in files:
+        p = os.path.join(root, "samples.csv")
+        t = os.path.getmtime(p)
+        if t > best_t:
+            best_t = t
+            best = p
+if not best:
+    raise SystemExit("tabdiff: no samples.csv under " + base)
+shutil.copy(best, r"/work/output-Benchmark-trainonly-v1/n1/tabdiff/tabdiff-n1-20260501_175031/tabdiff-n1-3680-20260501_175339.csv")
diff --git a/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/_tabdiff_train.py b/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/_tabdiff_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..eed28c4788e5ce9ddc363c0ec547d41fa6d62053
--- /dev/null
+++ b/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/_tabdiff_train.py
@@ -0,0 +1,21 @@
+
+import os, shutil, subprocess, sys
+td = r"/workspace/TabDiff"
+name = r"pipeline_n1"
+src = r"/work/output-Benchmark-trainonly-v1/n1/tabdiff/tabdiff-n1-20260501_175031/tabular_bundle/pipeline_n1"
+dst_data = os.path.join(td, "data", name)
+dst_syn = os.path.join(td, "synthetic", name)
+shutil.rmtree(dst_data, ignore_errors=True)
+shutil.copytree(src, dst_data)
+os.makedirs(dst_syn, exist_ok=True)
+for fn in ("real.csv", "test.csv", "val.csv"):
+    shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn))
+os.chdir(td)
+os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "")
+os.environ["TABDIFF_SMOKE_STEPS"] = "500"
+os.environ["TABDIFF_ADAPTER_TRAIN"] = "1"
+subprocess.check_call([
+    sys.executable, "-m", "tabdiff.main",
+    "--dataname", name, "--mode", "train", "--gpu", "0",
+    "--no_wandb", "--exp_name", r"adapter_learnable",
+])
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+version https://git-lfs.github.com/spec/v1
+oid sha256:95fccfea951830a81be642ed8a6b7b609467a19b70ceeca6a4c362957b7924a6
+size 29568
diff --git a/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/tabular_bundle/pipeline_n1/y_train.npy b/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/tabular_bundle/pipeline_n1/y_train.npy
new file mode 100644
index 0000000000000000000000000000000000000000..8f9c77303339ffe29118b71018c2df51a3419653
--- /dev/null
+++ b/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/tabular_bundle/pipeline_n1/y_train.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:95fccfea951830a81be642ed8a6b7b609467a19b70ceeca6a4c362957b7924a6
+size 29568
diff --git a/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/tabular_bundle/pipeline_n1/y_val.npy b/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/tabular_bundle/pipeline_n1/y_val.npy
new file mode 100644
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+++ b/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/tabular_bundle/pipeline_n1/y_val.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:95fccfea951830a81be642ed8a6b7b609467a19b70ceeca6a4c362957b7924a6
+size 29568
diff --git a/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/train_20260501_175032.log b/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/train_20260501_175032.log
new file mode 100644
index 0000000000000000000000000000000000000000..376f76692c8e6cd33e074f59c792c909e112a39a
--- /dev/null
+++ b/SynthData0523/main/n1/tabdiff/tabdiff-n1-20260501_175031/train_20260501_175032.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 297493
diff --git a/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/_tabpfgen_generate.py b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/_tabpfgen_generate.py
new file mode 100644
index 0000000000000000000000000000000000000000..7e578c61fe757e08d47a70a52d26227f2fbcb3cc
--- /dev/null
+++ b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/_tabpfgen_generate.py
@@ -0,0 +1,68 @@
+import numpy as np
+import pandas as pd
+import json
+from tabpfgen import TabPFGen
+
+df = pd.read_csv("/work/temp/tabpfgen_regen_parallel_deadline/20260422_070318/n1/staged/public/train.csv")
+target_col = "class"
+
+feature_cols = [c for c in df.columns if c != target_col]
+
+# --- Label-encode categorical / object columns ---
+cat_encodings = {}  # col -> list of unique values (index = code)
+for col in feature_cols:
+    if df[col].dtype == object or str(df[col].dtype) == 'category':
+        cats = sorted(df[col].dropna().unique().tolist(), key=str)
+        cat_map = {v: i for i, v in enumerate(cats)}
+        df[col] = df[col].map(cat_map).astype(float)
+        cat_encodings[col] = cats
+        print(f"[TabPFGen] Label-encoded '{col}' ({len(cats)} categories)")
+
+# Encode target if categorical
+target_cats = None
+if df[target_col].dtype == object or str(df[target_col].dtype) == 'category':
+    cats = sorted(df[target_col].dropna().unique().tolist(), key=str)
+    t_map = {v: i for i, v in enumerate(cats)}
+    df[target_col] = df[target_col].map(t_map).astype(float)
+    target_cats = cats
+    print(f"[TabPFGen] Label-encoded target '{target_col}' ({len(cats)} categories)")
+
+X = df[feature_cols].values.astype(np.float32)
+y = df[target_col].values
+
+# Handle NaN
+for i in range(X.shape[1]):
+    col_vals = X[:, i]
+    mask = np.isnan(col_vals)
+    if mask.any():
+        mean_val = np.nanmean(col_vals)
+        X[mask, i] = mean_val if not np.isnan(mean_val) else 0.0
+
+gen = TabPFGen(
+    n_sgld_steps=1000,
+    sgld_step_size=0.01,
+    sgld_noise_scale=0.01,
+    device="auto",
+)
+
+print(f"[TabPFGen] Generating 3680 rows via generate_classification")
+X_syn, y_syn = gen.generate_classification(X, y, n_samples=3680)
+
+syn_df = pd.DataFrame(X_syn, columns=feature_cols)
+syn_df[target_col] = y_syn
+
+# --- Inverse label-encoding for categorical columns ---
+for col, cats in cat_encodings.items():
+    # Round to nearest integer index, clamp to valid range
+    codes = np.round(syn_df[col].values).astype(int)
+    codes = np.clip(codes, 0, len(cats) - 1)
+    syn_df[col] = [cats[c] for c in codes]
+
+if target_cats is not None:
+    codes = np.round(syn_df[target_col].values).astype(int)
+    codes = np.clip(codes, 0, len(target_cats) - 1)
+    syn_df[target_col] = [target_cats[c] for c in codes]
+
+syn_df = syn_df[list(df.columns)]
+syn_df.to_csv("/work/temp/tabpfgen_regen_parallel_deadline/20260422_070318/n1/tabpfgen-n1-3680-20260422_070321.csv", index=False)
+print(f"[TabPFGen] Saved {len(syn_df)} rows -> /work/temp/tabpfgen_regen_parallel_deadline/20260422_070318/n1/tabpfgen-n1-3680-20260422_070321.csv")
diff --git a/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/gen_20260422_070321.log b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/gen_20260422_070321.log
new file mode 100644
index 0000000000000000000000000000000000000000..4ee92e8aea325ccbe83cd3e313f2a08bc5aeb8b6
--- /dev/null
+++ b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/gen_20260422_070321.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e06df6dce87e23c10449af6c481f279fcb4e5e414386c81c0bf247295100f9bc
+size 478
diff --git a/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/input_snapshot.json b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/input_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..38942c7fceb29ed84ae30ae10ec78d7b777057ae
--- /dev/null
+++ b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/input_snapshot.json
@@ -0,0 +1,36 @@
+{
+  "dataset_id": "n1",
+  "model": "tabpfgen",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-train.csv",
+      "exists": true,
+      "size": 563021,
+      "sha256": "e603fe5195edac0e926f63b398fd1af936766c1b502b300341a478e70aef4df5"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-val.csv",
+      "exists": true,
+      "size": 71100,
+      "sha256": "29ec664376ba652ee157545c9afe81d1afa054e30a554bc50ab2ebf1c52cef83"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-test.csv",
+      "exists": true,
+      "size": 71605,
+      "sha256": "2696873d18a2f693dc4b08f1c30f34a30cf96f1195790479ab8947fee8bc35ef"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n1/n1-dataset_profile.json",
+      "exists": true,
+      "size": 21967,
+      "sha256": "62128c1a7c75e9b7c23136d477b5795a9477bc710734776bd4a1378d3d81dc33"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n1/n1-dataset_contract_v1.json",
+      "exists": true,
+      "size": 27866,
+      "sha256": "cf9ef940957593e898ef55899808bb02267775fdad024ec6bf75793ef28b7ba1"
+    }
+  }
+}
\ No newline at end of file
diff --git a/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/public_gate/normalized_schema_snapshot.json b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/public_gate/normalized_schema_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..4ea0990f267498755e921b225d08fb0704a147d4
--- /dev/null
+++ b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/public_gate/normalized_schema_snapshot.json
@@ -0,0 +1,1222 @@
+{
+  "dataset_id": "n1",
+  "target_column": "class",
+  "task_type": "classification",
+  "columns": [
+    {
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+      "profile_stats": {
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+        "example_values": [
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+        "unique_ratio": 0.042391,
+        "example_values": [
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+          "0.1",
+          "0.32"
+        ]
+      }
+    },
+    {
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+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+          "0.41",
+          "1.24"
+        ]
+      }
+    },
+    {
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+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
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+        ]
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+    },
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+        "unique_ratio": 0.06712,
+        "example_values": [
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+        ]
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+    },
+    {
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+          "0.24",
+          "0.58",
+          "0.2"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_remove",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_ratio": 0.043478,
+        "example_values": [
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+          "0.2",
+          "0.62",
+          "0.16"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_internet",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_ratio": 0.042391,
+        "example_values": [
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+          "0.08",
+          "0.33",
+          "0.1",
+          "0.88"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_order",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_ratio": 0.035326,
+        "example_values": [
+          "0",
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+          "1.43",
+          "0.03",
+          "0.3"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_mail",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "unique_ratio": 0.063043,
+        "example_values": [
+          "0",
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+          "0.66",
+          "1.96",
+          "0.82"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_receive",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "unique_ratio": 0.029076,
+        "example_values": [
+          "0",
+          "0.08",
+          "0.24",
+          "0.1",
+          "0.62"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_will",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
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+      "impute_strategy": "median",
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+          "1.81",
+          "0.57",
+          "1.24"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_people",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
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+        ]
+      }
+    },
+    {
+      "name": "word_freq_report",
+      "role": "feature",
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+          "0.2",
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+        ]
+      }
+    },
+    {
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+    },
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+        ]
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+    },
+    {
+      "name": "word_freq_credit",
+      "role": "feature",
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+      }
+    },
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+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
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+    },
+    {
+      "name": "word_freq_font",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
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+        "unique_ratio": 0.022283,
+        "example_values": [
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+          "12.8",
+          "0",
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+    },
+    {
+      "name": "word_freq_000",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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\ No newline at end of file
diff --git a/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/public_gate/public_gate_report.json b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/public_gate/public_gate_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..76005f0c0dbdfe7ac411d1fdc1e546fbaa201fc6
--- /dev/null
+++ b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/public_gate/public_gate_report.json
@@ -0,0 +1,37 @@
+{
+  "dataset_id": "n1",
+  "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": "class",
+  "task_type": "classification",
+  "input_splits": {
+    "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-test.csv"
+  }
+}
\ No newline at end of file
diff --git a/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/public_gate/staged_input_manifest.json b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/public_gate/staged_input_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..80df88c47047a1c0ba4fff2cd2615c58247a8194
--- /dev/null
+++ b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/public_gate/staged_input_manifest.json
@@ -0,0 +1,1227 @@
+{
+  "dataset_id": "n1",
+  "target_column": "class",
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+        ]
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+    },
+    {
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+      "role": "feature",
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+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
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+        "unique_ratio": 0.048913,
+        "example_values": [
+          "0",
+          "0.64",
+          "0.17",
+          "0.71",
+          "0.18"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_parts",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 48,
+        "unique_ratio": 0.013043,
+        "example_values": [
+          "0",
+          "0.14",
+          "1.44",
+          "0.04",
+          "0.29"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_pm",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
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+        "unique_ratio": 0.040489,
+        "example_values": [
+          "0",
+          "0.1",
+          "0.14",
+          "1.58",
+          "1.96"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_direct",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
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+        "unique_ratio": 0.030435,
+        "example_values": [
+          "0",
+          "0.08",
+          "0.17",
+          "0.16",
+          "0.03"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_cs",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "unique_ratio": 0.025815,
+        "example_values": [
+          "0",
+          "0.34",
+          "0.51",
+          "3.12",
+          "0.37"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_meeting",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_ratio": 0.046739,
+        "example_values": [
+          "0",
+          "0.9",
+          "1.21",
+          "0.71",
+          "0.04"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_original",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "missing_rate": 0.0,
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+        "unique_ratio": 0.033424,
+        "example_values": [
+          "0",
+          "0.94",
+          "0.43",
+          "0.09",
+          "0.39"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_project",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
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+        "unique_ratio": 0.038587,
+        "example_values": [
+          "0",
+          "0.97",
+          "1.08",
+          "0.41",
+          "0.37"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_re",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 222,
+        "unique_ratio": 0.060326,
+        "example_values": [
+          "0",
+          "0.08",
+          "0.17",
+          "0.38",
+          "1.18"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_edu",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 203,
+        "unique_ratio": 0.055163,
+        "example_values": [
+          "0",
+          "4.76",
+          "0.25",
+          "0.28",
+          "0.9"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_table",
+      "role": "feature",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 31,
+        "unique_ratio": 0.008424,
+        "example_values": [
+          "0",
+          "1.51",
+          "0.72",
+          "0.61",
+          "0.04"
+        ]
+      }
+    },
+    {
+      "name": "word_freq_conference",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 94,
+        "unique_ratio": 0.025543,
+        "example_values": [
+          "0",
+          "0.03",
+          "2.22",
+          "0.14",
+          "0.74"
+        ]
+      }
+    },
+    {
+      "name": "char_freq_%3B",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 281,
+        "unique_ratio": 0.076359,
+        "example_values": [
+          "0",
+          "0.119",
+          "0.028",
+          "0.176",
+          "0.023"
+        ]
+      }
+    },
+    {
+      "name": "char_freq_%28",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 586,
+        "unique_ratio": 0.159239,
+        "example_values": [
+          "0",
+          "0.04",
+          "0.159",
+          "0.095",
+          "0.132"
+        ]
+      }
+    },
+    {
+      "name": "char_freq_%5B",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 200,
+        "unique_ratio": 0.054348,
+        "example_values": [
+          "0",
+          "0.264",
+          "0.298",
+          "0.119",
+          "0.046"
+        ]
+      }
+    },
+    {
+      "name": "char_freq_%21",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 870,
+        "unique_ratio": 0.236413,
+        "example_values": [
+          "0.265",
+          "0.709",
+          "0",
+          "0.751",
+          "0.25"
+        ]
+      }
+    },
+    {
+      "name": "char_freq_%24",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 461,
+        "unique_ratio": 0.125272,
+        "example_values": [
+          "0.088",
+          "0",
+          "0.159",
+          "0.255",
+          "0.224"
+        ]
+      }
+    },
+    {
+      "name": "char_freq_%23",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
+        "missing_rate": 0.0,
+        "unique_count": 279,
+        "unique_ratio": 0.075815,
+        "example_values": [
+          "1.151",
+          "1.56",
+          "0",
+          "0.095",
+          "0.013"
+        ]
+      }
+    },
+    {
+      "name": "capital_run_length_average",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_ratio": 0.506793,
+        "example_values": [
+          "11.066",
+          "7.82",
+          "1.902",
+          "1.515",
+          "4.163"
+        ]
+      }
+    },
+    {
+      "name": "capital_run_length_longest",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "example_values": [
+          "67",
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+          "10",
+          "5",
+          "84"
+        ]
+      }
+    },
+    {
+      "name": "capital_run_length_total",
+      "role": "feature",
+      "semantic_type": "numeric",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "median",
+      "profile_stats": {
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+        "unique_count": 828,
+        "unique_ratio": 0.225,
+        "example_values": [
+          "332",
+          "305",
+          "175",
+          "50",
+          "712"
+        ]
+      }
+    },
+    {
+      "name": "class",
+      "role": "target",
+      "semantic_type": "boolean",
+      "nullable": false,
+      "missing_tokens": [],
+      "parse_format": null,
+      "impute_strategy": "mode",
+      "profile_stats": {
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+        "unique_ratio": 0.000543,
+        "example_values": [
+          "1",
+          "0"
+        ]
+      }
+    }
+  ],
+  "public_manifest": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_070318/n1/public_gate/staged_input_manifest.json",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_070318/n1/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_070318/n1/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_070318/n1/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_070318/n1/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/temp/tabpfgen_regen_parallel_deadline/20260422_070318/n1/public_gate/public_gate_report.json"
+}
\ No newline at end of file
diff --git a/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/tabpfgen-n1-3680-20260422_070321.csv b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/tabpfgen-n1-3680-20260422_070321.csv
new file mode 100644
index 0000000000000000000000000000000000000000..4174a27d3e33faac6ac5a31cb25c5d374d0bddf4
--- /dev/null
+++ b/SynthData0523/main/n1/tabpfgen/n1-migrated-20260422_183752/tabpfgen-n1-3680-20260422_070321.csv
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f2d35a16d60c7f27139a112247822f0eb777b4f63721c290d285e03bdc3794d7
+size 2726714
diff --git a/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/_tabsyn_sample.py b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/_tabsyn_sample.py
new file mode 100644
index 0000000000000000000000000000000000000000..59ca8bd1dc6980ad26914eb949282e39ea8009cf
--- /dev/null
+++ b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/_tabsyn_sample.py
@@ -0,0 +1,38 @@
+import os, sys, subprocess
+
+work_dir = "/work/output-SpecializedModels/n1/tabsyn/tabsyn-n1-20260413_054310"
+dataname = "benchmark_ds"
+output_csv = "/work/output-SpecializedModels/n1/tabsyn/tabsyn-n1-20260413_054310/tabsyn-n1-100-20260413_054349.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 100 rows")
+env = os.environ.copy()
+ret = subprocess.run(
+    [sys.executable, "main.py",
+     "--dataname", dataname,
+     "--mode", "sample",
+     "--method", "tabsyn",
+     "--gpu", "0",
+     "--save_path", output_csv],
+    cwd=tabsyn_root,
+    env=env
+)
+if ret.returncode != 0:
+    sys.exit(ret.returncode)
+print(f"[TabSyn] Saved -> {output_csv}")
diff --git a/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/_tabsyn_train.py b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/_tabsyn_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..643f0d1318b7fc274302e9832037027160f763ed
--- /dev/null
+++ b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/_tabsyn_train.py
@@ -0,0 +1,61 @@
+import os, sys, subprocess
+
+work_dir = "/work/output-SpecializedModels/n1/tabsyn/tabsyn-n1-20260413_054310"
+dataname = "benchmark_ds"
+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()
+_te = 1
+if _te is not None:
+    env["TABSYN_VAE_EPOCHS"] = str(_te)
+    env["TABSYN_DIFFUSION_MAX_EPOCHS"] = str(max(_te + 1, 2))
+
+# Data preprocessing is done on the host side (_prepare_data_dir)
+# which creates .npy files, train/test CSVs, and info.json
+
+# Step 1: Train VAE (produces latent embeddings)
+print(f"[TabSyn] Step 1/2: Training VAE in {tabsyn_root}, dataname={dataname}")
+ret = subprocess.run(
+    [sys.executable, "main.py",
+     "--dataname", dataname,
+     "--mode", "train",
+     "--method", "vae",
+     "--gpu", "0"],
+    cwd=tabsyn_root,
+    env=env
+)
+if ret.returncode != 0:
+    print("[TabSyn] VAE training failed")
+    sys.exit(ret.returncode)
+
+# Step 2: Train diffusion model on latent space
+print(f"[TabSyn] Step 2/2: Training diffusion model")
+ret = subprocess.run(
+    [sys.executable, "main.py",
+     "--dataname", dataname,
+     "--mode", "train",
+     "--method", "tabsyn",
+     "--gpu", "0"],
+    cwd=tabsyn_root,
+    env=env
+)
+if ret.returncode != 0:
+    print("[TabSyn] Diffusion training failed")
+    sys.exit(ret.returncode)
+print("[TabSyn] Training complete (VAE + Diffusion)")
diff --git a/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_cat_test.npy b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_cat_test.npy
new file mode 100644
index 0000000000000000000000000000000000000000..8158d4136400e5d8cb8335f6231240859db1d36a
--- /dev/null
+++ b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_cat_test.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5fa174e8e451ec918a72a0814cb77bca182e1180065081a41e593041b4a6c4aa
+size 11192
diff --git a/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_cat_train.npy b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_cat_train.npy
new file mode 100644
index 0000000000000000000000000000000000000000..b175f2450fedfa34f0a2c5404e0e7cfbbf932e55
--- /dev/null
+++ b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_cat_train.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5c4d57185bdbb48ec560db86dbe10869cd9683a3da89c5fef6530bb5a2112efc
+size 99488
diff --git a/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_num_test.npy b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_num_test.npy
new file mode 100644
index 0000000000000000000000000000000000000000..c93113c53b291497ccf7a3a1a45ea0a0bf5131bc
--- /dev/null
+++ b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_num_test.npy
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 99704
diff --git a/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_num_train.npy b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_num_train.npy
new file mode 100644
index 0000000000000000000000000000000000000000..717d21183fa11f6d92c254ea71ffea84bc98c833
--- /dev/null
+++ b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/data/benchmark_ds/X_num_train.npy
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diff --git a/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/synthetic/benchmark_ds/real.csv b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/synthetic/benchmark_ds/real.csv
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diff --git a/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/synthetic/benchmark_ds/test.csv b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/synthetic/benchmark_ds/test.csv
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diff --git a/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/tabsyn-n1-100-20260413_054349.csv b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/tabsyn-n1-100-20260413_054349.csv
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+++ b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/tabsyn-n1-100-20260413_054349.csv
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diff --git a/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/train_20260413_054311.log b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/train_20260413_054311.log
new file mode 100644
index 0000000000000000000000000000000000000000..307a854c77aa0b50d203a0818b585bb95634e9ac
--- /dev/null
+++ b/SynthData0523/main/n1/tabsyn/tabsyn-n1-20260413_054310/train_20260413_054311.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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diff --git a/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/_tvae_generate.py b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/_tvae_generate.py
new file mode 100644
index 0000000000000000000000000000000000000000..237cb9bb7bd2cb048e142f92de1dc1a067262bd2
--- /dev/null
+++ b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/_tvae_generate.py
@@ -0,0 +1,5 @@
+from ctgan.synthesizers.tvae import TVAE
+model = TVAE.load("/work/output-SpecializedModels/n1/tvae/tvae-n1-20260321_065834/models_300epochs/tvae_300epochs.pt")
+samples = model.sample(3680)
+samples.to_csv("/work/output-SpecializedModels/n1/tvae/tvae-n1-20260321_065834/tvae-n1-3680-20260330_065936.csv", index=False)
+print(f"[TVAE] Generated 3680 rows -> /work/output-SpecializedModels/n1/tvae/tvae-n1-20260321_065834/tvae-n1-3680-20260330_065936.csv")
diff --git a/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/_tvae_train.py b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/_tvae_train.py
new file mode 100644
index 0000000000000000000000000000000000000000..6f84ae0c4856a7f169bc345babdad1aaf2730b4d
--- /dev/null
+++ b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/_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/n1/tvae/tvae-n1-20260321_065834/staged/public/train.csv"
+meta_path = "/work/output-SpecializedModels/n1/tvae/tvae-n1-20260321_065834/tvae_metadata.json"
+save_path = "/work/output-SpecializedModels/n1/tvae/tvae-n1-20260321_065834/models_300epochs/tvae_300epochs.pt"
+epochs = 300
+
+data, discrete_columns = read_csv(csv_path, meta_path, header=True, discrete=None)
+print(f"[TVAE] Training on {len(data)} rows, {len(data.columns)} cols, epochs={epochs}")
+model = TVAE(epochs=epochs, batch_size=500)
+model.fit(data, discrete_columns)
+model.save(save_path)
+print(f"[TVAE] Model saved -> {save_path}")
diff --git a/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/gen_20260321_070349.log b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/gen_20260321_070349.log
new file mode 100644
index 0000000000000000000000000000000000000000..f00478614529c2b8e0bf928ee77086138badae2c
--- /dev/null
+++ b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/gen_20260321_070349.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 126
diff --git a/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/gen_20260330_065936.log b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/gen_20260330_065936.log
new file mode 100644
index 0000000000000000000000000000000000000000..2f04af654d0a1a5f6508a77bbe7158344474c31c
--- /dev/null
+++ b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/gen_20260330_065936.log
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
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+size 126
diff --git a/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/input_snapshot.json b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/input_snapshot.json
new file mode 100644
index 0000000000000000000000000000000000000000..206ec0de5c339d94206e817ddf029c52c81b4efb
--- /dev/null
+++ b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/input_snapshot.json
@@ -0,0 +1,36 @@
+{
+  "dataset_id": "n1",
+  "model": "tvae",
+  "inputs": {
+    "train_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-train.csv",
+      "exists": true,
+      "size": 563021,
+      "sha256": "e603fe5195edac0e926f63b398fd1af936766c1b502b300341a478e70aef4df5"
+    },
+    "val_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-val.csv",
+      "exists": true,
+      "size": 71100,
+      "sha256": "29ec664376ba652ee157545c9afe81d1afa054e30a554bc50ab2ebf1c52cef83"
+    },
+    "test_csv": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-test.csv",
+      "exists": true,
+      "size": 71605,
+      "sha256": "2696873d18a2f693dc4b08f1c30f34a30cf96f1195790479ab8947fee8bc35ef"
+    },
+    "profile_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n1/n1-dataset_profile.json",
+      "exists": true,
+      "size": 21967,
+      "sha256": "62128c1a7c75e9b7c23136d477b5795a9477bc710734776bd4a1378d3d81dc33"
+    },
+    "contract_json": {
+      "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/artifacts/data_core/tabular/n1/n1-dataset_contract_v1.json",
+      "exists": true,
+      "size": 27866,
+      "sha256": "cf9ef940957593e898ef55899808bb02267775fdad024ec6bf75793ef28b7ba1"
+    }
+  }
+}
\ No newline at end of file
diff --git a/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/models_300epochs/train_20260321_065835.log b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/models_300epochs/train_20260321_065835.log
new file mode 100644
index 0000000000000000000000000000000000000000..50c3c58ef8c68c44a9efb22d0492a50f7dec0569
--- /dev/null
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\ No newline at end of file
diff --git a/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/public_gate/public_gate_report.json b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/public_gate/public_gate_report.json
new file mode 100644
index 0000000000000000000000000000000000000000..76005f0c0dbdfe7ac411d1fdc1e546fbaa201fc6
--- /dev/null
+++ b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/public_gate/public_gate_report.json
@@ -0,0 +1,37 @@
+{
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+  "status": "pass",
+  "checks": [
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+      "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": "class",
+  "task_type": "classification",
+  "input_splits": {
+    "train": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-train.csv",
+    "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-val.csv",
+    "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n1/n1-test.csv"
+  }
+}
\ No newline at end of file
diff --git a/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/public_gate/staged_input_manifest.json b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/public_gate/staged_input_manifest.json
new file mode 100644
index 0000000000000000000000000000000000000000..36fce01d0854c010607d8c69c5bb731943c81fd5
--- /dev/null
+++ b/SynthData0523/main/n1/tvae/tvae-n1-20260321_065834/public_gate/staged_input_manifest.json
@@ -0,0 +1,1227 @@
+{
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+  "target_column": "class",
+  "task_type": "classification",
+  "train_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tvae/tvae-n1-20260321_065834/staged/public/train.csv",
+  "val_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tvae/tvae-n1-20260321_065834/staged/public/val.csv",
+  "test_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tvae/tvae-n1-20260321_065834/staged/public/test.csv",
+  "features_json": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tvae/tvae-n1-20260321_065834/staged/public/staged_features.json",
+  "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n1/tvae/tvae-n1-20260321_065834/public_gate/public_gate_report.json",
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