diff --git a/syntheticSuccess/c11/arf/arf-c11-20260321_113607/_arf_generate.py b/syntheticSuccess/c11/arf/arf-c11-20260321_113607/_arf_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..92f13058b19c77cf6c76408584da22b9d593fc50 --- /dev/null +++ b/syntheticSuccess/c11/arf/arf-c11-20260321_113607/_arf_generate.py @@ -0,0 +1,6 @@ +import pickle +with open("/work/output-SpecializedModels/c11/arf/arf-c11-20260321_113607/arf_model.pkl", "rb") as f: + model = pickle.load(f) +syn = model.forge(n=54045) +syn.to_csv("/work/output-SpecializedModels/c11/arf/arf-c11-20260321_113607/arf-c11-54045-20260330_065348.csv", index=False) +print(f"[ARF] Generated 54045 rows -> /work/output-SpecializedModels/c11/arf/arf-c11-20260321_113607/arf-c11-54045-20260330_065348.csv") diff --git a/syntheticSuccess/c11/arf/arf-c11-20260321_113607/_arf_train.py b/syntheticSuccess/c11/arf/arf-c11-20260321_113607/_arf_train.py new file mode 100644 index 0000000000000000000000000000000000000000..c7941d70b4f4f1ea2567e16abe54338e395e798a --- /dev/null +++ b/syntheticSuccess/c11/arf/arf-c11-20260321_113607/_arf_train.py @@ -0,0 +1,19 @@ +import pickle +import pandas as pd +from arfpy import arf + +df = pd.read_csv("/work/output-SpecializedModels/c11/arf/arf-c11-20260321_113607/staged/public/train.csv") +df = df.dropna(axis=1, how="all") +print(f"[ARF] Training on {len(df)} rows, {len(df.columns)} cols") + +model = arf.arf(x=df) +if hasattr(model, "fit"): + model.fit() +elif hasattr(model, "forde"): + model.forde() +else: + raise RuntimeError("arfpy API: no fit() / forde()") + +with open("/work/output-SpecializedModels/c11/arf/arf-c11-20260321_113607/arf_model.pkl", "wb") as f: + pickle.dump(model, f) +print(f"[ARF] Model saved -> /work/output-SpecializedModels/c11/arf/arf-c11-20260321_113607/arf_model.pkl") diff --git a/syntheticSuccess/c11/arf/arf-c11-20260321_113607/arf-c11-1000-20260321_133718.csv 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b/syntheticSuccess/c11/bayesnet/bayesnet-c11-20260321_062357/_bayesnet_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..a1405fae48c00eda30a7e1ddeaa076fa740c577b --- /dev/null +++ b/syntheticSuccess/c11/bayesnet/bayesnet-c11-20260321_062357/_bayesnet_generate.py @@ -0,0 +1,43 @@ +import subprocess, sys, os + +pip_libs = "/pip_libs" +sys.path.insert(0, pip_libs) +os.environ["PYTHONPATH"] = pip_libs + os.pathsep + os.environ.get("PYTHONPATH", "") + +def _ensure_deps(): + try: + import synthcity + except ModuleNotFoundError: + print("[BayesNet] synthcity not found - installing to cache...") + subprocess.run( + [sys.executable, "-m", "pip", "install", + "--target", pip_libs, "synthcity==0.2.12", "numpy<2", "-q"], + check=True + ) + import shutil, glob + for pat in ["torch", "torch-*", "torchvision", "torchvision-*", + "torchvision.libs", "torchgen", "nvidia*", "triton*"]: + for p in glob.glob(os.path.join(pip_libs, pat)): + if os.path.isdir(p): shutil.rmtree(p) + else: os.remove(p) + if pip_libs not in sys.path: + sys.path.insert(0, pip_libs) + +_ensure_deps() + +import pickle, json as _json +with open("/work/output-SpecializedModels/c11/bayesnet/bayesnet-c11-20260321_062357/bayesnet_model.pkl", "rb") as f: + plugin = pickle.load(f) +syn = plugin.generate(count=54045).dataframe() + +# Restore zero-variance columns that were dropped during training +const_path = "/work/output-SpecializedModels/c11/bayesnet/bayesnet-c11-20260321_062357/bayesnet_model.pkl".replace("bayesnet_model.pkl", "const_cols.json") +if os.path.exists(const_path): + with open(const_path) as _f: + const_cols = _json.load(_f) + for col, val in const_cols.items(): + syn[col] = val + print(f"[BayesNet] Restored constant column '{col}' = {val}") + +syn.to_csv("/work/output-SpecializedModels/c11/bayesnet/bayesnet-c11-20260321_062357/bayesnet-c11-54045-20260330_065348.csv", index=False) +print(f"[BayesNet] Generated 54045 rows -> /work/output-SpecializedModels/c11/bayesnet/bayesnet-c11-20260321_062357/bayesnet-c11-54045-20260330_065348.csv") diff --git a/syntheticSuccess/c11/bayesnet/bayesnet-c11-20260321_062357/_bayesnet_train.py b/syntheticSuccess/c11/bayesnet/bayesnet-c11-20260321_062357/_bayesnet_train.py new file mode 100644 index 0000000000000000000000000000000000000000..7905d9bdf6ecfe2262a79badd090a1881e3e6ad5 --- /dev/null +++ b/syntheticSuccess/c11/bayesnet/bayesnet-c11-20260321_062357/_bayesnet_train.py @@ -0,0 +1,62 @@ +import subprocess, sys, os + +pip_libs = "/pip_libs" +sys.path.insert(0, pip_libs) +os.environ["PYTHONPATH"] = pip_libs + os.pathsep + os.environ.get("PYTHONPATH", "") + +def _ensure_deps(): + try: + import synthcity + except ModuleNotFoundError: + print("[BayesNet] synthcity not found - installing to cache (first run, may take minutes)...") + # Install synthcity with numpy<2 to avoid conflicts + subprocess.run( + [sys.executable, "-m", "pip", "install", + "--target", pip_libs, "synthcity==0.2.12", "numpy<2", "-q"], + check=True + ) + # Remove torch/torchvision from pip_libs to avoid shadowing system versions + import shutil, glob + for pat in ["torch", "torch-*", "torchvision", "torchvision-*", + "torchvision.libs", "torchgen", "nvidia*", "triton*"]: + for p in glob.glob(os.path.join(pip_libs, pat)): + if os.path.isdir(p): shutil.rmtree(p) + else: os.remove(p) + if pip_libs not in sys.path: + sys.path.insert(0, pip_libs) + +_ensure_deps() + +from synthcity.plugins import Plugins +import pickle +import pandas as pd +from synthcity.plugins.core.dataloader import GenericDataLoader + +df = pd.read_csv("/work/output-SpecializedModels/c11/bayesnet/bayesnet-c11-20260321_062357/staged/public/train.csv") +df = df.dropna(axis=1, how="all") + +# Drop zero-variance columns (only 1 unique value) to avoid +# synthcity encoder KeyError during generation +import json as _json +const_cols = {} +for col in list(df.columns): + nuniq = df[col].nunique() + if nuniq <= 1: + const_cols[col] = df[col].iloc[0] if len(df) > 0 else None + df = df.drop(columns=[col]) + print(f"[BayesNet] Dropped zero-variance column '{col}' (value={const_cols[col]})") + +# Save constant columns info so generate can restore them +const_path = "/work/output-SpecializedModels/c11/bayesnet/bayesnet-c11-20260321_062357/bayesnet_model.pkl".replace("bayesnet_model.pkl", "const_cols.json") +with open(const_path, "w") as _f: + _json.dump({k: str(v) for k, v in const_cols.items()}, _f) + +print(f"[BayesNet] Training on {len(df)} rows, {len(df.columns)} cols") + +loader = GenericDataLoader(df) +plugin = Plugins().get("bayesian_network") +plugin.fit(loader) + +with open("/work/output-SpecializedModels/c11/bayesnet/bayesnet-c11-20260321_062357/bayesnet_model.pkl", "wb") as f: + pickle.dump(plugin, f) +print(f"[BayesNet] Model saved -> /work/output-SpecializedModels/c11/bayesnet/bayesnet-c11-20260321_062357/bayesnet_model.pkl") diff --git 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"/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c11/realtabformer/rtf-c11-20260329_105536/staged/public/staged_features.json", + "public_gate_report": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/c11/realtabformer/rtf-c11-20260329_105536/public_gate/public_gate_report.json" +} \ No newline at end of file diff --git a/syntheticSuccess/c11/realtabformer/rtf-c11-20260329_105536/train_20260329_105539.log b/syntheticSuccess/c11/realtabformer/rtf-c11-20260329_105536/train_20260329_105539.log new file mode 100644 index 0000000000000000000000000000000000000000..872a92598141ccd436b9103e67c6106b75dcf1b8 --- /dev/null +++ b/syntheticSuccess/c11/realtabformer/rtf-c11-20260329_105536/train_20260329_105539.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:76c9637086bcbc6d4fc44030b49dc2fad665d22e9b6697c49770ea6fc5addcd6 +size 12607406 diff --git a/syntheticSuccess/c11/tabddpm/tabddpm-c11-20260422_220946/_tabddpm_sample.py b/syntheticSuccess/c11/tabddpm/tabddpm-c11-20260422_220946/_tabddpm_sample.py new file mode 100644 index 0000000000000000000000000000000000000000..8f6ca220afc0dec014f8c53d8e6e55e474381f59 --- /dev/null +++ b/syntheticSuccess/c11/tabddpm/tabddpm-c11-20260422_220946/_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 54045 rows") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/c11/tabddpm/tabddpm-c11-20260422_220946/config_sample_20260422_221822.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/c11/tabddpm/tabddpm-c11-20260422_220946" +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/c11/tabddpm/tabddpm-c11-20260422_220946/tabddpm-c11-54045-20260422_221822.csv", index=False) + print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-SpecializedModels/c11/tabddpm/tabddpm-c11-20260422_220946/tabddpm-c11-54045-20260422_221822.csv") +else: + print("[TabDDPM] WARNING: No output .npy files found") + sys.exit(1) diff --git a/syntheticSuccess/c11/tabddpm/tabddpm-c11-20260422_220946/_tabddpm_train.py b/syntheticSuccess/c11/tabddpm/tabddpm-c11-20260422_220946/_tabddpm_train.py new file mode 100644 index 0000000000000000000000000000000000000000..b6d51329e0432409270f93f2346b6409ad17ed92 --- /dev/null +++ b/syntheticSuccess/c11/tabddpm/tabddpm-c11-20260422_220946/_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/c11/tabddpm/tabddpm-c11-20260422_220946/config.toml") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/c11/tabddpm/tabddpm-c11-20260422_220946/config.toml", + "--train"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print("[TabDDPM] Training complete") diff --git a/syntheticSuccess/c11/tabddpm/tabddpm-c11-20260422_220946/config.toml b/syntheticSuccess/c11/tabddpm/tabddpm-c11-20260422_220946/config.toml new file mode 100644 index 0000000000000000000000000000000000000000..01747c7f320abb3da253d901389af0392fee0caa --- /dev/null +++ b/syntheticSuccess/c11/tabddpm/tabddpm-c11-20260422_220946/config.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/c11/tabddpm/tabddpm-c11-20260422_220946/output" +real_data_path = "/work/output-SpecializedModels/c11/tabddpm/tabddpm-c11-20260422_220946/data" +model_type = "mlp" +num_numerical_features = 0 +device = "cuda:0" + +[model_params] +d_in = 42 +num_classes = 3 +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/syntheticSuccess/c11/tabddpm/tabddpm-c11-20260422_220946/config_sample_20260422_221822.toml 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0000000000000000000000000000000000000000..15df591e07f97f39f2482e75eafaaa0b05dabc28 --- /dev/null +++ b/syntheticSuccess/c11/tabddpm/tabddpm-c11-20260422_220946/train_20260422_220951.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:16c4c8a5604bafd35591edb858daa0c5dba881cc51c0179cc00ddde84e53fb4a +size 880 diff --git a/syntheticSuccess/c11/tvae/tvae-c11-20260321_112101/_tvae_generate.py b/syntheticSuccess/c11/tvae/tvae-c11-20260321_112101/_tvae_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..e86180ea473db40caa5daead89aa58c89adce52c --- /dev/null +++ b/syntheticSuccess/c11/tvae/tvae-c11-20260321_112101/_tvae_generate.py @@ -0,0 +1,5 @@ +from ctgan.synthesizers.tvae import TVAE +model = TVAE.load("/work/output-SpecializedModels/c11/tvae/tvae-c11-20260321_112101/models_300epochs/tvae_300epochs.pt") +samples = model.sample(54045) +samples.to_csv("/work/output-SpecializedModels/c11/tvae/tvae-c11-20260321_112101/tvae-c11-54045-20260330_065346.csv", index=False) +print(f"[TVAE] Generated 54045 rows -> /work/output-SpecializedModels/c11/tvae/tvae-c11-20260321_112101/tvae-c11-54045-20260330_065346.csv") diff --git a/syntheticSuccess/c11/tvae/tvae-c11-20260321_112101/_tvae_train.py b/syntheticSuccess/c11/tvae/tvae-c11-20260321_112101/_tvae_train.py new file mode 100644 index 0000000000000000000000000000000000000000..faaed93d7c2f6c43e99d8f8eb75c595a0a9cefcb --- /dev/null +++ b/syntheticSuccess/c11/tvae/tvae-c11-20260321_112101/_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/c11/tvae/tvae-c11-20260321_112101/staged/public/train.csv" +meta_path = "/work/output-SpecializedModels/c11/tvae/tvae-c11-20260321_112101/tvae_metadata.json" +save_path = "/work/output-SpecializedModels/c11/tvae/tvae-c11-20260321_112101/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/syntheticSuccess/c11/tvae/tvae-c11-20260321_112101/gen_20260321_113621.log b/syntheticSuccess/c11/tvae/tvae-c11-20260321_112101/gen_20260321_113621.log new file mode 100644 index 0000000000000000000000000000000000000000..f961c86c1e1459220eb845e07316eaf075343451 --- /dev/null +++ b/syntheticSuccess/c11/tvae/tvae-c11-20260321_112101/gen_20260321_113621.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:70ed06181da9f0710f5a3eeeb8f427e8aa1fa32c78ef2dd012e7f450a19b38bc +size 129 diff --git 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