diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/_arf_generate.py b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/_arf_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..ac80a7d87786586e77efd4490f87ca3b71c42e55 --- /dev/null +++ b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/_arf_generate.py @@ -0,0 +1,6 @@ +import pickle +with open("/work/output-SpecializedModels/n17/arf/arf-n17-20260326_191832/arf_model.pkl", "rb") as f: + model = pickle.load(f) +syn = model.forge(n=11600) +syn.to_csv("/work/output-SpecializedModels/n17/arf/arf-n17-20260326_191832/arf-n17-11600-20260330_070859.csv", index=False) +print(f"[ARF] Generated 11600 rows -> /work/output-SpecializedModels/n17/arf/arf-n17-20260326_191832/arf-n17-11600-20260330_070859.csv") diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/_arf_train.py b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/_arf_train.py new file mode 100644 index 0000000000000000000000000000000000000000..d4e2f249b6ccae3a98c74a11669bf4c2e2d051be --- /dev/null +++ b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/_arf_train.py @@ -0,0 +1,19 @@ +import pickle +import pandas as pd +from arfpy import arf + +df = pd.read_csv("/work/output-SpecializedModels/n17/arf/arf-n17-20260326_191832/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/n17/arf/arf-n17-20260326_191832/arf_model.pkl", "wb") as f: + pickle.dump(model, f) +print(f"[ARF] Model saved -> /work/output-SpecializedModels/n17/arf/arf-n17-20260326_191832/arf_model.pkl") diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/arf-n17-1000-20260326_192114.csv b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/arf-n17-1000-20260326_192114.csv new file mode 100644 index 0000000000000000000000000000000000000000..4b33afb8cd9955100b7936addec5ea26f1e7d4f6 --- /dev/null +++ b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/arf-n17-1000-20260326_192114.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d659ea28e8badd665ce9bd529a0a52e41ddde01acd5323b9744d7c93165867bb +size 139238 diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/arf-n17-11600-20260330_070859.csv b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/arf-n17-11600-20260330_070859.csv new file mode 100644 index 0000000000000000000000000000000000000000..5e1705e7523dc4fbaed499db0bf1df6dadf37b02 --- /dev/null +++ b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/arf-n17-11600-20260330_070859.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:64d1dcd5b36f23b5c5a91d685b62d7206a5d16cb68d8fa6a9cb2b6d5c420522e +size 1616031 diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/arf_model.pkl b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/arf_model.pkl new file mode 100644 index 0000000000000000000000000000000000000000..8683fa6b67024089a777ef17f903eb998cdf74bb --- /dev/null +++ b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/arf_model.pkl @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:205cae90caea02f50837fd86230f2dce3d239f207259dfca47a2c072521f84ca +size 49207269 diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/gen_20260326_192114.log b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/gen_20260326_192114.log new file mode 100644 index 0000000000000000000000000000000000000000..f24a91654c44c5ce83020600d6de9de0e3ed2eed --- /dev/null +++ b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/gen_20260326_192114.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:88a6b41def40d485187f49140a2a8f0a75da6ec258b7eecaddee1290eddb98b7 +size 441 diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/gen_20260330_070859.log b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/gen_20260330_070859.log new file mode 100644 index 0000000000000000000000000000000000000000..8dd9c32261fc2528ac6cbcb2694180eb9258bcd8 --- /dev/null +++ b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/gen_20260330_070859.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:adf526f12447ecea9aa4c1ec41fb98a4f44c38c840de9e857be19a40c75485c0 +size 443 diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/input_snapshot.json b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..a33cc75a78e0c0a5d5b71013bed61fb60283d1de --- /dev/null +++ b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n17", + "model": "arf", + "inputs": { + "train_csv": { + "path": 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"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/n17/n17-train.csv", + "val": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n17/n17-val.csv", + "test": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n17/n17-test.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/public_gate/staged_input_manifest.json b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/public_gate/staged_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..4731aa01f7c0b0946ad0ad38b28bc0bb163e7d19 --- /dev/null +++ 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"generate_status": "success", + "reason_code": null, + "reason_detail": null, + "artifacts": { + "synthetic_csv": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n17/arf/arf-n17-20260326_191832/arf-n17-11600-20260330_070859.csv" + } +} \ No newline at end of file diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/staged/arf/adapter_report.json b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/staged/arf/adapter_report.json new file mode 100644 index 0000000000000000000000000000000000000000..21c54db72af3e7c531ca5fb0833e1fd67505a4b4 --- /dev/null +++ b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/staged/arf/adapter_report.json @@ -0,0 +1,7 @@ +{ + "adapter_ready_status": "pass", + "adapter_fail_reason_code": null, + "adapter_fail_detail": null, + "adapter_transforms_applied": [], + "model_input_manifest": "/data/jialinzhang/SynthesizePipeline-server/output-SpecializedModels/n17/arf/arf-n17-20260326_191832/staged/arf/model_input_manifest.json" +} \ No newline at end of file diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/staged/arf/adapter_transforms_applied.json b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/staged/arf/adapter_transforms_applied.json new file mode 100644 index 0000000000000000000000000000000000000000..0637a088a01e8ddab3bf3fa98dbe804cbde1a0dc --- /dev/null +++ b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/staged/arf/adapter_transforms_applied.json @@ -0,0 +1 @@ +[] \ No newline at end of file diff --git a/syntheticSuccess/n17/arf/arf-n17-20260326_191832/staged/arf/model_input_manifest.json b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/staged/arf/model_input_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..aa0733e6670750c5bc278e04241d528a503b9757 --- /dev/null +++ b/syntheticSuccess/n17/arf/arf-n17-20260326_191832/staged/arf/model_input_manifest.json @@ -0,0 +1,224 @@ +{ + "dataset_id": "n17", + "model": "arf", + "target_column": "class", + "task_type": 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a/syntheticSuccess/n17/bayesnet/bayesnet-n17-20260321_090751/_bayesnet_generate.py b/syntheticSuccess/n17/bayesnet/bayesnet-n17-20260321_090751/_bayesnet_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..e5d2b75864db52de3ad0f1878dfe28b3409e4017 --- /dev/null +++ b/syntheticSuccess/n17/bayesnet/bayesnet-n17-20260321_090751/_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/n17/bayesnet/bayesnet-n17-20260321_090751/bayesnet_model.pkl", "rb") as f: + plugin = pickle.load(f) +syn = plugin.generate(count=11600).dataframe() + +# Restore zero-variance columns that were dropped during training +const_path = "/work/output-SpecializedModels/n17/bayesnet/bayesnet-n17-20260321_090751/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/n17/bayesnet/bayesnet-n17-20260321_090751/bayesnet-n17-11600-20260330_070907.csv", index=False) +print(f"[BayesNet] Generated 11600 rows -> /work/output-SpecializedModels/n17/bayesnet/bayesnet-n17-20260321_090751/bayesnet-n17-11600-20260330_070907.csv") diff --git a/syntheticSuccess/n17/bayesnet/bayesnet-n17-20260321_090751/_bayesnet_train.py b/syntheticSuccess/n17/bayesnet/bayesnet-n17-20260321_090751/_bayesnet_train.py new file mode 100644 index 0000000000000000000000000000000000000000..0c196ea36c5696fa7538850258f8fa3c955e9bea --- /dev/null +++ b/syntheticSuccess/n17/bayesnet/bayesnet-n17-20260321_090751/_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/n17/bayesnet/bayesnet-n17-20260321_090751/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/n17/bayesnet/bayesnet-n17-20260321_090751/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/n17/bayesnet/bayesnet-n17-20260321_090751/bayesnet_model.pkl", "wb") as f: + pickle.dump(plugin, f) +print(f"[BayesNet] Model saved -> /work/output-SpecializedModels/n17/bayesnet/bayesnet-n17-20260321_090751/bayesnet_model.pkl") diff --git 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b/syntheticSuccess/n17/realtabformer/rtf-n17-20260330_022426/train_20260330_022426.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a1354cc251e7a10c101790e91b1a035b63eec5a3c2026baeaea48dbccb554689 +size 2632157 diff --git a/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/_tabddpm_sample.py b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/_tabddpm_sample.py new file mode 100644 index 0000000000000000000000000000000000000000..07dda6b04a7564f9fbb9943d1974d730e801ae65 --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/_tabddpm_sample.py @@ -0,0 +1,66 @@ +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 11600 rows") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/config_sample_20260425_081657.toml", + "--sample"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) + +# 将 .npy 输出转为 CSV（npy 在 TabDDPM 的 parent_dir，即 npy_dir） +info_path = "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/data/info.json" +with open(info_path) as f: + info = json.load(f) + +output_dir = "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/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/n17/tabddpm/tabddpm-n17-20260328_053151/tabddpm-n17-11600-20260425_081657.csv", index=False) + print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/tabddpm-n17-11600-20260425_081657.csv") +else: + print("[TabDDPM] WARNING: No output .npy files found") + sys.exit(1) diff --git a/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/_tabddpm_train.py b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/_tabddpm_train.py new file mode 100644 index 0000000000000000000000000000000000000000..e66d0dbe7f20062d492f36561ef1252e2227e762 --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/_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/n17/tabddpm/tabddpm-n17-20260328_053151/config.toml") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/config.toml", + "--train"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print("[TabDDPM] Training complete") diff --git a/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/config.toml b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/config.toml new file mode 100644 index 0000000000000000000000000000000000000000..738c7c85877d7498e4d49920dd42765e4fb59670 --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/config.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/output" +real_data_path = "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/data" +model_type = "mlp" +num_numerical_features = 9 +device = "cuda:0" + +[model_params] +d_in = 9 +num_classes = 7 +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/n17/tabddpm/tabddpm-n17-20260328_053151/config_sample_20260424_212839.toml b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/config_sample_20260424_212839.toml new file mode 100644 index 0000000000000000000000000000000000000000..9787111f517b9bf04a55dc1a8eba63b5c646a449 --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/config_sample_20260424_212839.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/output" +real_data_path = "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/data" +model_type = "mlp" +num_numerical_features = 9 +device = "cuda:0" + +[model_params] +d_in = 9 +num_classes = 7 +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 = 11600 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/config_sample_20260425_034408.toml b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/config_sample_20260425_034408.toml new file mode 100644 index 0000000000000000000000000000000000000000..9787111f517b9bf04a55dc1a8eba63b5c646a449 --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/config_sample_20260425_034408.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/output" +real_data_path = "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/data" +model_type = "mlp" +num_numerical_features = 9 +device = "cuda:0" + +[model_params] +d_in = 9 +num_classes = 7 +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 = 11600 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/config_sample_20260425_081657.toml b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/config_sample_20260425_081657.toml new file mode 100644 index 0000000000000000000000000000000000000000..9787111f517b9bf04a55dc1a8eba63b5c646a449 --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/config_sample_20260425_081657.toml @@ -0,0 +1,39 @@ +seed = 0 +parent_dir = "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/output" +real_data_path = "/work/output-SpecializedModels/n17/tabddpm/tabddpm-n17-20260328_053151/data" +model_type = "mlp" +num_numerical_features = 9 +device = "cuda:0" + +[model_params] +d_in = 9 +num_classes = 7 +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 = 11600 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/data/X_num_test.npy b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/data/X_num_test.npy new file mode 100644 index 0000000000000000000000000000000000000000..9b553c454690be9ce33e48765dc562fd9645b1b7 --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/data/X_num_test.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:977f6b25461eb763297734338ef71a271b568165ee5e95f47b1bb096d3518c4c +size 52364 diff --git a/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/data/X_num_train.npy b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/data/X_num_train.npy new file mode 100644 index 0000000000000000000000000000000000000000..86afbfdcec310cfc4db889a60c3015ad881a302c --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/data/X_num_train.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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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 = 11600 +batch_size = 1000 +seed = 0 diff --git a/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/output/data/info.json b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/output/data/info.json new file mode 100644 index 0000000000000000000000000000000000000000..931e056b0eb216611c9a849f90f2014fba9b0c56 --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/output/data/info.json @@ -0,0 +1,35 @@ +{ + "name": "benchmark_dataset", + "task_type": "multiclass", + "n_num_features": 9, + "n_cat_features": 0, + "train_size": 11600, + "num_col_idx": [ + 0, + 1, + 2, + 3, + 4, + 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newline at end of file diff --git a/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/tabddpm-n17-1000-20260328_053515.csv b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/tabddpm-n17-1000-20260328_053515.csv new file mode 100644 index 0000000000000000000000000000000000000000..3430da8c18922b32da1ba45e420810a94178adb7 --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/tabddpm-n17-1000-20260328_053515.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6c1e1ae972fa7f3dfebef5a75024f121a5f5bd1f14f3db05aacf1431007e5d38 +size 60537 diff --git a/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/tabddpm-n17-11600-20260425_081657.csv b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/tabddpm-n17-11600-20260425_081657.csv new file mode 100644 index 0000000000000000000000000000000000000000..a989358281c398dacce66bc714e517cad454e077 --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/tabddpm-n17-11600-20260425_081657.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c0fb9ab286dfb3aab12c0f4443405cfb91a2e57df1d2bf8871c96316182cb545 +size 701750 diff --git a/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/train_20260328_053151.log b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/train_20260328_053151.log new file mode 100644 index 0000000000000000000000000000000000000000..1cea4e4f2c2471142eed514939b10ef14de32c4e --- /dev/null +++ b/syntheticSuccess/n17/tabddpm/tabddpm-n17-20260328_053151/train_20260328_053151.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:4f9a31e9fdf0db6921a41897940d4e3e13508dde83c39852dd3f1d4f6562d375 +size 1122 diff --git a/syntheticSuccess/n17/tabpfgen/n17-migrated-20260422_183752/_tabpfgen_generate.py b/syntheticSuccess/n17/tabpfgen/n17-migrated-20260422_183752/_tabpfgen_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..f4b75c848fe865988850ce554e59c9cedd043372 --- /dev/null +++ b/syntheticSuccess/n17/tabpfgen/n17-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/n17/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 11600 rows via generate_regression") +X_syn, y_syn = gen.generate_regression(X, y, n_samples=11600) + +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/n17/tabpfgen-n17-11600-20260422_070321.csv", index=False) +print(f"[TabPFGen] Saved {len(syn_df)} rows -> /work/temp/tabpfgen_regen_parallel_deadline/20260422_070318/n17/tabpfgen-n17-11600-20260422_070321.csv") diff --git a/syntheticSuccess/n17/tabpfgen/n17-migrated-20260422_183752/gen_20260422_070321.log b/syntheticSuccess/n17/tabpfgen/n17-migrated-20260422_183752/gen_20260422_070321.log new file mode 100644 index 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a/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/_tabsyn_sample.py b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/_tabsyn_sample.py new file mode 100644 index 0000000000000000000000000000000000000000..ad08c884d857e1b6024ae0b68336b021a5420bb1 --- /dev/null +++ b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/_tabsyn_sample.py @@ -0,0 +1,39 @@ +import os, sys, subprocess + +work_dir = "/work/output-SpecializedModels/n17/tabsyn/tabsyn-n17-20260427_025147" +dataname = "tabsyn_n17" +output_csv = "/work/output-SpecializedModels/n17/tabsyn/tabsyn-n17-20260427_025147/tabsyn-n17-11600-20260427_025208.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 11600 rows") +env = os.environ.copy() +env.setdefault("TABSYN_RESUME", "1") +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/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/_tabsyn_train.py b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/_tabsyn_train.py new file mode 100644 index 0000000000000000000000000000000000000000..863b39a85c1d3c27bf52341bd43760baca8560a8 --- /dev/null +++ b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/_tabsyn_train.py @@ -0,0 +1,63 @@ +import os, sys, subprocess + +work_dir = "/work/output-SpecializedModels/n17/tabsyn/tabsyn-n17-20260427_025147" +dataname = "tabsyn_n17" +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() +env.setdefault("TABSYN_RESUME", "1") +env.setdefault("TABSYN_VAE_BATCH_SIZE", "1024") +_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/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/data/tabsyn_n17/X_cat_test.npy b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/data/tabsyn_n17/X_cat_test.npy new file mode 100644 index 0000000000000000000000000000000000000000..29f83feb4c9da23628a00297575be78927a98eaf --- /dev/null +++ b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/data/tabsyn_n17/X_cat_test.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:de9ff993887498884d64fb519047b34c91490bbaf7ca2e06b5d61a9ad03a289e +size 128 diff --git a/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/data/tabsyn_n17/X_cat_train.npy b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/data/tabsyn_n17/X_cat_train.npy new file mode 100644 index 0000000000000000000000000000000000000000..29f83feb4c9da23628a00297575be78927a98eaf --- /dev/null +++ b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/data/tabsyn_n17/X_cat_train.npy @@ -0,0 +1,3 @@ +version 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index 0000000000000000000000000000000000000000..cc1d1b80e322f177d5a6b2346099ca319e4ff81e --- /dev/null +++ b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/synthetic/tabsyn_n17/real.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:373383578478c8df244051d26a774f0126f89a64fbb8b53842ed634266dc32fa +size 307507 diff --git a/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/synthetic/tabsyn_n17/test.csv b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/synthetic/tabsyn_n17/test.csv new file mode 100644 index 0000000000000000000000000000000000000000..cc1d1b80e322f177d5a6b2346099ca319e4ff81e --- /dev/null +++ b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/synthetic/tabsyn_n17/test.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:373383578478c8df244051d26a774f0126f89a64fbb8b53842ed634266dc32fa +size 307507 diff --git a/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/tabsyn-n17-11600-20260427_025208.csv b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/tabsyn-n17-11600-20260427_025208.csv new file mode 100644 index 0000000000000000000000000000000000000000..6ada61788b26196128caa7e45764b9bce32e00b2 --- /dev/null +++ b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/tabsyn-n17-11600-20260427_025208.csv @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5d4d534f7e7556362f749a0e8f97ec368a8f1deb95d13fd23417c1166b44bcff +size 590107 diff --git a/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/train_20260427_025148.log b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/train_20260427_025148.log new file mode 100644 index 0000000000000000000000000000000000000000..08e5faa1726a2cb739178b702682d6f4d1ec55bc --- /dev/null +++ b/syntheticSuccess/n17/tabsyn/tabsyn-n17-20260427_025147/train_20260427_025148.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:312cf14ebc65fb12b2b80c61b8634412c022607df54dac8e8394982f93e15814 +size 3344 diff --git a/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/_tvae_generate.py b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/_tvae_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..bcea2160fba365c3a10f1d08026da06dfd56b900 --- /dev/null +++ b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/_tvae_generate.py @@ -0,0 +1,5 @@ +from ctgan.synthesizers.tvae import TVAE +model = TVAE.load("/work/output-SpecializedModels/n17/tvae/tvae-n17-20260328_054240/models_300epochs/tvae_300epochs.pt") +samples = model.sample(11600) +samples.to_csv("/work/output-SpecializedModels/n17/tvae/tvae-n17-20260328_054240/tvae-n17-11600-20260330_070841.csv", index=False) +print(f"[TVAE] Generated 11600 rows -> /work/output-SpecializedModels/n17/tvae/tvae-n17-20260328_054240/tvae-n17-11600-20260330_070841.csv") diff --git a/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/_tvae_train.py b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/_tvae_train.py new file mode 100644 index 0000000000000000000000000000000000000000..8c5171720d3853e79e45e744d68899c50a497cf2 --- /dev/null +++ b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/_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/n17/tvae/tvae-n17-20260328_054240/staged/public/train.csv" +meta_path = "/work/output-SpecializedModels/n17/tvae/tvae-n17-20260328_054240/tvae_metadata.json" +save_path = "/work/output-SpecializedModels/n17/tvae/tvae-n17-20260328_054240/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/n17/tvae/tvae-n17-20260328_054240/gen_20260328_100702.log b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/gen_20260328_100702.log new file mode 100644 index 0000000000000000000000000000000000000000..7b23abc3f0e795c0f053aded2763a976c766b169 --- /dev/null +++ b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/gen_20260328_100702.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:547986faf9651ac743a38420481ce3469c8e11ed8b74dc0392e2e9aeef5019b5 +size 129 diff --git a/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/gen_20260330_070841.log b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/gen_20260330_070841.log new file mode 100644 index 0000000000000000000000000000000000000000..3dd7baf6c18c3e8eaca69fc83964d8afdbbef16d --- /dev/null +++ b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/gen_20260330_070841.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2d4b51b75d88a95546f74e51ece66ce73d7564bfec6f30fb63bfacbd8c971f8b +size 131 diff --git a/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/input_snapshot.json b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/input_snapshot.json new file mode 100644 index 0000000000000000000000000000000000000000..a9ace93f365dffdc4c3ee57a1156566427724f0e --- /dev/null +++ b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/input_snapshot.json @@ -0,0 +1,36 @@ +{ + "dataset_id": "n17", + "model": "tvae", + "inputs": { + "train_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n17/n17-train.csv", + "exists": true, + "size": 319108, + "sha256": "99cb629d6e58372a6cbfe396c89994cfb68d279d18ae29e954faeb7b1af8ffce" + }, + "val_csv": { + "path": "/data/jialinzhang/SynthesizePipeline-server/DatasetNew/n17/n17-val.csv", + "exists": true, + "size": 39916, + "sha256": "7e6d4456b11d527ca043a524c39ddd525a8f746ed01b5ebd6606e4910c188ab8" + }, + "test_csv": { + "path": 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0000000000000000000000000000000000000000..ca66d6ac80b553eb2d540391a7a17c80b8ed0cd3 --- /dev/null +++ b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/models_300epochs/train_20260328_054240.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:967299f630503fe9aa7a4407784c3bc5054404ab7ca4c2c87c4a400aae7d9663 +size 173 diff --git a/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/models_300epochs/tvae_300epochs.pt b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/models_300epochs/tvae_300epochs.pt new file mode 100644 index 0000000000000000000000000000000000000000..4c97ed5e1ebc7d6b8b79b08abfb3b6daf2895732 --- /dev/null +++ b/syntheticSuccess/n17/tvae/tvae-n17-20260328_054240/models_300epochs/tvae_300epochs.pt @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:6c2f6f420cdb95297e56ba82911ceca5cf5a41b69a5f3085e1a839e29a43d384 +size 686828 diff --git 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