Add files using upload-large-folder tool

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/_tabpfgen_generate.py

@@ -0,0 +1,100 @@
+import os
+import numpy as np
+import pandas as pd
+import json
+from tabpfgen import TabPFGen
+
+df = pd.read_csv("/work/output-Benchmark-trainonly-v1/m6/tabpfgen/tabpfgen-m6-20260429_061036/staged/public/train.csv")
+target_col = "VisitorType"
+
+target_missing = df[target_col].isna()
+if target_missing.any():
+    dropped = int(target_missing.sum())
+    df = df.loc[~target_missing].copy()
+    print(
+        f"[TabPFGen] Dropped {dropped} rows with missing target '{target_col}'"
+    )
+if df.empty:
+    raise ValueError(
+        f"[TabPFGen] No rows remain after dropping missing target '{target_col}'"
+    )
+
+feature_cols = [c for c in df.columns if c != target_col]
+
+cat_encodings = {}
+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)")
+
+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(9864)
+
+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
+
+# TabPFGen v0.1.x API：仅支持 n_sgld_steps / sgld_* / device。
+# （旧版脚本中的 energy_*_chunk 与上游 TabPFGen 不一致，会导致 TypeError。）
+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
+
+for col, cats in cat_encodings.items():
+    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]
+
+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:
+        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/output-Benchmark-trainonly-v1/m6/tabpfgen/tabpfgen-m6-20260429_061036/tabpfgen-m6-9864-20260429_061037.csv", index=False)
+print(f"[TabPFGen] Saved {len(syn_df)} rows -> /work/output-Benchmark-trainonly-v1/m6/tabpfgen/tabpfgen-m6-20260429_061036/tabpfgen-m6-9864-20260429_061037.csv")

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/gen_20260429_061037.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c1298acab3bbb43c47659b717ab2fc82eefbb9b5e3f3fe5b0bdefee94ea6ce77
+size 1009

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/input_snapshot.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9b4ca3cc1d16acda0fdcf10667afd7ef7951249ea9217774677d3fd239ba2dd9
+size 1349

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/public_gate/normalized_schema_snapshot.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9a347e1961ed33117b9d30b34fc15249721c7bd0b25fb31ac7f974d158104bdd
+size 8408

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/public_gate/public_gate_report.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eab3321ed4d9b51e430632d2aedeca5d0260df7acff58b7d732c556dd377db9d
+size 918

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/public_gate/staged_input_manifest.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c6870a55834824cd60f9d8d4774b69f4a83e0b3e6cc2672bee29ca008289d951
+size 9224

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/runtime_result.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a043b711dac86ce0ba0516df4394b8059f14b5de3a318e79b42e937f8b4009ef
+size 596

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/staged/public/staged_features.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:23eac1d28d264cb53a977ae6229286741b38cdeec8b02eb2ee5f9a2949661e29
+size 1780

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/staged/public/test.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d16d0389cb0fe4b23bab344dc10070de6678357a9452f9f620d0eeba66a6b12d
+size 116376

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/staged/public/train.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e1f0338c367408dc21d5a4ec9cdc5d3fe8188916db6085f3fd326304a55551e1
+size 924849

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/staged/public/val.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb9169f3c7213420491d9b709ee1cc650aeaed732fa77dcbd6ffe3583366b2d4
+size 116198

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/staged/tabpfgen/adapter_report.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7db65002e3fcb93b7ae3b98fdccc4f6b784b16069e59576e7bc29767ed3019b3
+size 324

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/staged/tabpfgen/adapter_transforms_applied.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4f53cda18c2baa0c0354bb5f9a3ecbe5ed12ab4d8e11ba873c2f11161202b945
+size 2

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/staged/tabpfgen/model_input_manifest.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8b7b113931e970bbbbf3b55b001f32df3b731fb6a381ec092f5cb82cadfaea16
+size 9424

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/tabpfgen-m6-9864-20260429_061037.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:add4f4a878f040f1c7d2159a18e9300a83135f301ad1a81224dd9c17e49f14b0
+size 1969051

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/tabpfgen_meta.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eca07e4cf63fd4963a12130f37ca86561522727a8b2615aef1924d214c133245
+size 451

syntheticSuccess/m6/tabpfgen/tabpfgen-m6-20260429_061036/train_20260429_061037.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cb1ebbf34920b287311be084a383babac0d04e9f6379859eeb08115d9c1ee42e
+size 595