Add files using upload-large-folder tool

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/_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/c7/tabpfgen/tabpfgen-c7-20260429_061314/staged/public/train.csv")
+target_col = "class"
+
+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(10368)
+
+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/c7/tabpfgen/tabpfgen-c7-20260429_061314/tabpfgen-c7-10368-20260429_061314.csv", index=False)
+print(f"[TabPFGen] Saved {len(syn_df)} rows -> /work/output-Benchmark-trainonly-v1/c7/tabpfgen/tabpfgen-c7-20260429_061314/tabpfgen-c7-10368-20260429_061314.csv")

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/gen_20260429_061314.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:50514dbd9cd064ed6754ea4b46fd82f7df79bcc7f0ff228dab81cdd9aeb3c8a6
+size 1267

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/input_snapshot.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aa0d81821866bd2a65f0adb4ddec8deb4c25e14a6bc21dc30d08d7afb5c9cf02
+size 1349

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/public_gate/normalized_schema_snapshot.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5dd68094a5d8fc40d291695c5aa12bc01cfe8d3a62848b4bcfd82c2e88ed19c9
+size 4177

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/public_gate/public_gate_report.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f08566bcd78a9005059bf27f5f9ecf74954e2be289410d19100e900577f651ea
+size 912

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/public_gate/staged_input_manifest.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c135182fd3cd06b55f916c855c9e1d86c2100b5101445e28f4c4628a13d03470
+size 4993

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/runtime_result.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1268730fa043d04b0ff21f728477d1225e6ae74dab0f4ef9f5a7ea2d475dabb2
+size 597

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/staged/public/staged_features.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07596ae0689482090a05749dba332eca061d863cde5d8bf7a83e8c2c92abb330
+size 851

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/staged/public/test.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2042076337d5c37c6476e6bca2bd33cb5a171450c27894534ef50ac223256058
+size 106030

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/staged/public/train.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b37f6b2ef5257f40bd826ac956749881f0f474362bdb56e8c5728ad629242e3a
+size 847349

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/staged/public/val.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eff6dec27c3740661a1ae84dea391d690dfb60342bfd5d7527b903fdd6009780
+size 106192

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/staged/tabpfgen/adapter_report.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7b5bd12bc857c6e75bf8d52dfa9e9e5840b0dcd5ee456928d1c4372a81b3271a
+size 324

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/staged/tabpfgen/adapter_transforms_applied.json

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

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/staged/tabpfgen/model_input_manifest.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:31c864f09fbd8b3af09f5e07b7e47f014cb6a96ada0ea8726e122be18fdfe2d8
+size 5193

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/tabpfgen-c7-10368-20260429_061314.csv

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:11bb6aee31a1bcbe969d798a8a69906cd73c17223291104079b93797d7cf94d0
+size 843881

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/tabpfgen_meta.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6d24b564dc79998c779f88388e7cb852959589d51fff04613dbb2fe1da220388
+size 445

syntheticSuccess/c7/tabpfgen/tabpfgen-c7-20260429_061314/train_20260429_061314.log

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:73ec563d826ab6396f832e3e1487289794c7c2a744680d747abf25ceb3611619
+size 595