diff --git a/syntheticSuccess/n6/arf/arf-n6-20260325_091411/_arf_generate.py b/syntheticSuccess/n6/arf/arf-n6-20260325_091411/_arf_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..3f2c9aa0c1ecbb8232bdeab32ee6362809b5d12c --- /dev/null +++ b/syntheticSuccess/n6/arf/arf-n6-20260325_091411/_arf_generate.py @@ -0,0 +1,6 @@ +import pickle +with open("/work/output-SpecializedModels/n6/arf/arf-n6-20260325_091411/arf_model.pkl", "rb") as f: + model = pickle.load(f) +syn = model.forge(n=6400) +syn.to_csv("/work/output-SpecializedModels/n6/arf/arf-n6-20260325_091411/arf-n6-6400-20260330_070203.csv", index=False) +print(f"[ARF] Generated 6400 rows -> /work/output-SpecializedModels/n6/arf/arf-n6-20260325_091411/arf-n6-6400-20260330_070203.csv") diff --git a/syntheticSuccess/n6/arf/arf-n6-20260325_091411/_arf_train.py b/syntheticSuccess/n6/arf/arf-n6-20260325_091411/_arf_train.py new file mode 100644 index 0000000000000000000000000000000000000000..ba2149d27d822ec87bd5e63b11d7a96cbd1d32de --- /dev/null +++ b/syntheticSuccess/n6/arf/arf-n6-20260325_091411/_arf_train.py @@ -0,0 +1,19 @@ +import pickle +import pandas as pd +from arfpy import arf + +df = pd.read_csv("/work/output-SpecializedModels/n6/arf/arf-n6-20260325_091411/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/n6/arf/arf-n6-20260325_091411/arf_model.pkl", "wb") as f: + pickle.dump(model, f) +print(f"[ARF] Model saved -> /work/output-SpecializedModels/n6/arf/arf-n6-20260325_091411/arf_model.pkl") diff --git a/syntheticSuccess/n6/arf/arf-n6-20260325_091411/arf-n6-1000-20260325_092040.csv 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https://git-lfs.github.com/spec/v1 +oid sha256:60a3dd7f655f8086e53402dcdcfa42297d586d8483f2afd6e1bbc6bd3521303f +size 39705 diff --git a/syntheticSuccess/n6/arf/arf-n6-20260325_091411/train_20260325_091411.log b/syntheticSuccess/n6/arf/arf-n6-20260325_091411/train_20260325_091411.log new file mode 100644 index 0000000000000000000000000000000000000000..43c3e2cb1492ac48cba0988b7db0b6b060fa4cf4 --- /dev/null +++ b/syntheticSuccess/n6/arf/arf-n6-20260325_091411/train_20260325_091411.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6b0b9c68c6b2e5d371af1d29f6b7e171dc5174549f70310772c98969df13688d +size 417 diff --git a/syntheticSuccess/n6/bayesnet/bayesnet-n6-20260321_083501/_bayesnet_generate.py b/syntheticSuccess/n6/bayesnet/bayesnet-n6-20260321_083501/_bayesnet_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..2500875241cd1d9be4eecac745b5d70fa92bf750 --- /dev/null +++ b/syntheticSuccess/n6/bayesnet/bayesnet-n6-20260321_083501/_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/n6/bayesnet/bayesnet-n6-20260321_083501/bayesnet_model.pkl", "rb") as f: + plugin = pickle.load(f) +syn = plugin.generate(count=6400).dataframe() + +# Restore zero-variance columns that were dropped during training +const_path = "/work/output-SpecializedModels/n6/bayesnet/bayesnet-n6-20260321_083501/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/n6/bayesnet/bayesnet-n6-20260321_083501/bayesnet-n6-6400-20260330_070213.csv", index=False) +print(f"[BayesNet] Generated 6400 rows -> /work/output-SpecializedModels/n6/bayesnet/bayesnet-n6-20260321_083501/bayesnet-n6-6400-20260330_070213.csv") diff --git a/syntheticSuccess/n6/bayesnet/bayesnet-n6-20260321_083501/_bayesnet_train.py b/syntheticSuccess/n6/bayesnet/bayesnet-n6-20260321_083501/_bayesnet_train.py new file mode 100644 index 0000000000000000000000000000000000000000..962c088147fd10cff25fd8ec30dc9cdaca87357c --- /dev/null +++ b/syntheticSuccess/n6/bayesnet/bayesnet-n6-20260321_083501/_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/n6/bayesnet/bayesnet-n6-20260321_083501/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/n6/bayesnet/bayesnet-n6-20260321_083501/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/n6/bayesnet/bayesnet-n6-20260321_083501/bayesnet_model.pkl", "wb") as f: + pickle.dump(plugin, f) +print(f"[BayesNet] Model saved -> /work/output-SpecializedModels/n6/bayesnet/bayesnet-n6-20260321_083501/bayesnet_model.pkl") diff --git a/syntheticSuccess/n6/bayesnet/bayesnet-n6-20260321_083501/bayesnet-n6-1000-20260321_083603.csv b/syntheticSuccess/n6/bayesnet/bayesnet-n6-20260321_083501/bayesnet-n6-1000-20260321_083603.csv new file mode 100644 index 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b/syntheticSuccess/n6/tvae/tvae-n6-20260320_072129/_tvae_generate.py @@ -0,0 +1,5 @@ +from ctgan.synthesizers.tvae import TVAE +model = TVAE.load("/work/output-SpecializedModels/n6/tvae/tvae-n6-20260320_072129/models_300epochs/tvae_300epochs.pt") +samples = model.sample(6400) +samples.to_csv("/work/output-SpecializedModels/n6/tvae/tvae-n6-20260320_072129/tvae-n6-6400-20260330_070145.csv", index=False) +print(f"[TVAE] Generated 6400 rows -> /work/output-SpecializedModels/n6/tvae/tvae-n6-20260320_072129/tvae-n6-6400-20260330_070145.csv") diff --git a/syntheticSuccess/n6/tvae/tvae-n6-20260320_072129/_tvae_train.py b/syntheticSuccess/n6/tvae/tvae-n6-20260320_072129/_tvae_train.py new file mode 100644 index 0000000000000000000000000000000000000000..c2fe493d494b2d4e411ad21ad79dff456f4a1e95 --- /dev/null +++ b/syntheticSuccess/n6/tvae/tvae-n6-20260320_072129/_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/DatasetNew/n6/n6-train.csv" +meta_path = "/work/output-SpecializedModels/n6/tvae/tvae-n6-20260320_072129/tvae_metadata.json" +save_path = "/work/output-SpecializedModels/n6/tvae/tvae-n6-20260320_072129/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/n6/tvae/tvae-n6-20260320_072129/gen_20260320_072435.log b/syntheticSuccess/n6/tvae/tvae-n6-20260320_072129/gen_20260320_072435.log new file mode 100644 index 0000000000000000000000000000000000000000..b9690aafc0af69ab7330687b2713a434f9a35ea8 --- /dev/null +++ b/syntheticSuccess/n6/tvae/tvae-n6-20260320_072129/gen_20260320_072435.log @@ -0,0 +1,3 @@ +version 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