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b/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_000210/_tabbyflow_gen.py @@ -0,0 +1,33 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n11" +src = r"/work/output-Benchmark-trainonly-v1/n11/tabbyflow/tabbyflow-n11-20260501_000210/tabular_bundle/pipeline_n11" +dst_data = os.path.join(root, "data", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +dst_syn = os.path.join(root, "synthetic", name) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(root) +os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "") +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "test", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_efvfm", + "--ckpt_path", r"/workspace/ef-vfm/ef_vfm/ckpt/pipeline_n11/adapter_efvfm/model_500.pt", + "--num_samples_to_generate", str(int(15215)), +]) +base = os.path.join(root, "ef_vfm", "result", name, r"adapter_efvfm") +best = None +best_t = -1.0 +for r, _, files in os.walk(base): + if "samples.csv" in files: + p = os.path.join(r, "samples.csv") + t = os.path.getmtime(p) + if t > best_t: + best_t, best = t, p +if not best: + raise SystemExit("tabbyflow: no samples.csv in " + base) +shutil.copy(best, r"/work/output-Benchmark-trainonly-v1/n11/tabbyflow/tabbyflow-n11-20260501_000210/tabbyflow-n11-15215-20260501_000941.csv") diff --git a/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_000210/_tabbyflow_train.py b/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_000210/_tabbyflow_train.py new file mode 100644 index 0000000000000000000000000000000000000000..2ec729d06ff321aa6995180adbbf27e2d0b61c1c --- /dev/null +++ b/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_000210/_tabbyflow_train.py @@ -0,0 +1,22 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n11" +src = r"/work/output-Benchmark-trainonly-v1/n11/tabbyflow/tabbyflow-n11-20260501_000210/tabular_bundle/pipeline_n11" +os.makedirs(os.path.join(root, "data", name), exist_ok=True) +dst_data = os.path.join(root, "data", name) +dst_syn = os.path.join(root, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(root) +os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "") +os.environ["EFVFM_SMOKE_STEPS"] = "500" +os.environ["EFVFM_ADAPTER_TRAIN"] = "1" +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "train", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_efvfm", +]) diff --git a/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_000210/gen_20260501_000941.log 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@@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d28858e427269843d994e6532347987c862c60e1cec7b826cc0935c0ba0829ec +size 516222 diff --git a/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/_tabbyflow_gen.py b/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/_tabbyflow_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..f5848f4a7ba7a90bf5e791cdce018d187ac36cb8 --- /dev/null +++ b/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/_tabbyflow_gen.py @@ -0,0 +1,33 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n11" +src = r"/work/output-Benchmark-trainonly-v1/n11/tabbyflow/tabbyflow-n11-20260501_035405/tabular_bundle/pipeline_n11" +dst_data = os.path.join(root, "data", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +dst_syn = os.path.join(root, "synthetic", name) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(root) +os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "") +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "test", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_efvfm", + "--ckpt_path", r"/workspace/ef-vfm/ef_vfm/ckpt/pipeline_n11/adapter_efvfm/model_500.pt", + "--num_samples_to_generate", str(int(15215)), +]) +base = os.path.join(root, "ef_vfm", "result", name, r"adapter_efvfm") +best = None +best_t = -1.0 +for r, _, files in os.walk(base): + if "samples.csv" in files: + p = os.path.join(r, "samples.csv") + t = os.path.getmtime(p) + if t > best_t: + best_t, best = t, p +if not best: + raise SystemExit("tabbyflow: no samples.csv in " + base) +shutil.copy(best, r"/work/output-Benchmark-trainonly-v1/n11/tabbyflow/tabbyflow-n11-20260501_035405/tabbyflow-n11-15215-20260501_040149.csv") diff --git a/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/_tabbyflow_train.py b/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/_tabbyflow_train.py new file mode 100644 index 0000000000000000000000000000000000000000..59e6143ed556cb26e90deb1410a6796ff0118752 --- /dev/null +++ b/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/_tabbyflow_train.py @@ -0,0 +1,22 @@ + +import os, shutil, subprocess, sys +root = r"/workspace/ef-vfm" +name = r"pipeline_n11" +src = r"/work/output-Benchmark-trainonly-v1/n11/tabbyflow/tabbyflow-n11-20260501_035405/tabular_bundle/pipeline_n11" +os.makedirs(os.path.join(root, "data", name), exist_ok=True) +dst_data = os.path.join(root, "data", name) +dst_syn = os.path.join(root, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(root) +os.environ["PYTHONPATH"] = root + os.pathsep + os.environ.get("PYTHONPATH", "") +os.environ["EFVFM_SMOKE_STEPS"] = "500" +os.environ["EFVFM_ADAPTER_TRAIN"] = "1" +subprocess.check_call([ + sys.executable, "main.py", + "--dataname", name, "--mode", "train", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_efvfm", +]) diff --git a/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/gen_20260501_040149.log b/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/gen_20260501_040149.log new file mode 100644 index 0000000000000000000000000000000000000000..ce70067514a4915758933bd7a3e2cefed9ccbb42 --- /dev/null +++ b/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/gen_20260501_040149.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:1f90efc0e932b63b5d1e11d7ce2d52a66db00a8b39c475c72035c888a978908c +size 3066 diff --git a/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/input_snapshot.json 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sha256:95905dd042874f4c4e7523f7525b2864e220ef3c6fcdc58877ca3944645899cf +size 121848 diff --git a/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/train_20260501_035405.log b/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/train_20260501_035405.log new file mode 100644 index 0000000000000000000000000000000000000000..96c27e48de2d51769399925c5a6e17de7a1d5e7f --- /dev/null +++ b/SynthData0523/main/n11/tabbyflow/tabbyflow-n11-20260501_035405/train_20260501_035405.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:909303fe46899c17626d1d87ee607a0b01886541743bf51c10b679044237ed92 +size 516560 diff --git a/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260321_161341/_tabddpm_sample.py b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260321_161341/_tabddpm_sample.py new file mode 100644 index 0000000000000000000000000000000000000000..d11ab2c671ff195623f55fe34902c47643f23050 --- /dev/null +++ b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260321_161341/_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 15215 rows") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/n11/tabddpm/tabddpm-n11-20260321_161341/config_sample_20260425_074742.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/n11/tabddpm/tabddpm-n11-20260321_161341/data/info.json" +with open(info_path) as f: + info = json.load(f) + +output_dir = "/work/output-SpecializedModels/n11/tabddpm/tabddpm-n11-20260321_161341/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/n11/tabddpm/tabddpm-n11-20260321_161341/tabddpm-n11-15215-20260425_074742.csv", index=False) + print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-SpecializedModels/n11/tabddpm/tabddpm-n11-20260321_161341/tabddpm-n11-15215-20260425_074742.csv") +else: + print("[TabDDPM] WARNING: No output .npy files found") + sys.exit(1) diff --git a/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260321_161341/_tabddpm_train.py b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260321_161341/_tabddpm_train.py new file mode 100644 index 0000000000000000000000000000000000000000..fdcfa29ed835cba24003ca3ea301b1e117b10e28 --- /dev/null +++ b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260321_161341/_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/n11/tabddpm/tabddpm-n11-20260321_161341/config.toml") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-SpecializedModels/n11/tabddpm/tabddpm-n11-20260321_161341/config.toml", + "--train"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print("[TabDDPM] Training complete") diff --git a/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260321_161341/config.toml b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260321_161341/config.toml new file mode 100644 index 0000000000000000000000000000000000000000..ea42e86a65427a35a72beac02b38f871463322c1 --- /dev/null +++ b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260321_161341/config.toml @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid 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b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260321_161341/train_20260321_161342.log new file mode 100644 index 0000000000000000000000000000000000000000..61b154a6deb1422944ef154d768932b7e4808c78 --- /dev/null +++ b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260321_161341/train_20260321_161342.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:999a89bb73b91de1d1c53b4a0b31a66b5c0665b0b6043a317cea5577e18bd111 +size 1124 diff --git a/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260430_231115/_tabddpm_sample_r0.py b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260430_231115/_tabddpm_sample_r0.py new file mode 100644 index 0000000000000000000000000000000000000000..49e0b2bc51320fcd11a4aaf9d17f09ca7a97c17d --- /dev/null +++ b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260430_231115/_tabddpm_sample_r0.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 15215 rows") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260430_231115/config_sample_20260430_231138_r0.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-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260430_231115/data/info.json" +with open(info_path) as f: + info = json.load(f) + +output_dir = "/work/output-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260430_231115/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-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260430_231115/tabddpm-n11-15215-20260430_231138.csv", index=False) + print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260430_231115/tabddpm-n11-15215-20260430_231138.csv") +else: + print("[TabDDPM] WARNING: No output .npy files found") + sys.exit(1) diff --git a/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260430_231115/_tabddpm_train.py b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260430_231115/_tabddpm_train.py new file mode 100644 index 0000000000000000000000000000000000000000..2e720ea747bf44eb62aa7b7e41ec9aa33b9928b4 --- /dev/null +++ b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260430_231115/_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-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260430_231115/config.toml") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260430_231115/config.toml", + "--train"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print("[TabDDPM] Training complete") diff --git a/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260430_231115/config.toml b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260430_231115/config.toml new file mode 100644 index 0000000000000000000000000000000000000000..788a37b608a2d127c1890d7c217d579f1d5a4c6b --- /dev/null +++ b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260430_231115/config.toml @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:50f96999b47b7e87a752bd33d9e3e93a32e22ca18363ef3e4bb79390906122be +size 774 diff --git 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b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260430_231115/train_20260430_231115.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e57dcf25d39069140e75289c1b815ac106901118c56eaef39a3badb0da3ca641 +size 1070 diff --git a/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260501_040207/_tabddpm_sample_r0.py b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260501_040207/_tabddpm_sample_r0.py new file mode 100644 index 0000000000000000000000000000000000000000..18f19fa2fffb24c497523ccaddd3c30f5ebd089b --- /dev/null +++ b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260501_040207/_tabddpm_sample_r0.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 15215 rows") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260501_040207/config_sample_20260501_040230_r0.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-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260501_040207/data/info.json" +with open(info_path) as f: + info = json.load(f) + +output_dir = "/work/output-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260501_040207/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-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260501_040207/tabddpm-n11-15215-20260501_040230.csv", index=False) + print(f"[TabDDPM] Saved {len(df)} rows -> /work/output-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260501_040207/tabddpm-n11-15215-20260501_040230.csv") +else: + print("[TabDDPM] WARNING: No output .npy files found") + sys.exit(1) diff --git a/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260501_040207/_tabddpm_train.py b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260501_040207/_tabddpm_train.py new file mode 100644 index 0000000000000000000000000000000000000000..3ebc291becaccd52078510a369a2795499393b62 --- /dev/null +++ b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260501_040207/_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-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260501_040207/config.toml") +ret = subprocess.run( + [sys.executable, wrapper, "scripts/pipeline.py", + "--config", "/work/output-Benchmark-trainonly-v1/n11/tabddpm/tabddpm-n11-20260501_040207/config.toml", + "--train"], + cwd=tabddpm_root, + env=env +) +if ret.returncode != 0: + sys.exit(ret.returncode) +print("[TabDDPM] Training complete") diff --git a/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260501_040207/config.toml b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260501_040207/config.toml new file mode 100644 index 0000000000000000000000000000000000000000..f4ca5fd5c84c861c22e16263eab02ce36303300b --- /dev/null +++ b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260501_040207/config.toml @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bb40617631bffe9d9837914415b9641e449dd3c496d8a15993874064427a9183 +size 774 diff --git a/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260501_040207/config_sample_20260501_040230_r0.toml b/SynthData0523/main/n11/tabddpm/tabddpm-n11-20260501_040207/config_sample_20260501_040230_r0.toml new file mode 100644 index 0000000000000000000000000000000000000000..2ab5c2e171b1306df164e964d3e8864765a2d1e0 --- /dev/null +++ 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sha256:9a6655141042b55a49a2fad70327340fa9a2e84f45031c2120e904b0eecaabcd +size 1070 diff --git a/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260430_234952/_tabdiff_gen.py b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260430_234952/_tabdiff_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..26883d5f2725ca698b7c8f931e0a12c3fa7af912 --- /dev/null +++ b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260430_234952/_tabdiff_gen.py @@ -0,0 +1,36 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_n11" +src = r"/work/output-Benchmark-trainonly-v1/n11/tabdiff/tabdiff-n11-20260430_234952/tabular_bundle/pipeline_n11" +dst_data = os.path.join(td, "data", name) +dst_syn = os.path.join(td, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(td) +os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "") +subprocess.check_call([ + sys.executable, "-m", "tabdiff.main", + "--dataname", name, "--mode", "test", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_learnable", + "--ckpt_path", r"/workspace/TabDiff/tabdiff/ckpt/pipeline_n11/adapter_learnable/model_500.pt", + "--num_samples_to_generate", str(int(15215)), +]) +# test() 写入 tabdiff/result////samples.csv +import glob as g +base = os.path.join(td, "tabdiff", "result", name, r"adapter_learnable") +best = None +best_t = -1.0 +for root, _, files in os.walk(base): + if "samples.csv" in files: + p = os.path.join(root, "samples.csv") + t = os.path.getmtime(p) + if t > best_t: + best_t = t + best = p +if not best: + raise SystemExit("tabdiff: no samples.csv under " + base) +shutil.copy(best, r"/work/output-Benchmark-trainonly-v1/n11/tabdiff/tabdiff-n11-20260430_234952/tabdiff-n11-15215-20260430_235717.csv") diff --git a/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260430_234952/_tabdiff_train.py b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260430_234952/_tabdiff_train.py new file mode 100644 index 0000000000000000000000000000000000000000..eb9f605f157e9a4241a34352a2798a079e66f010 --- /dev/null +++ b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260430_234952/_tabdiff_train.py @@ -0,0 +1,21 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_n11" +src = r"/work/output-Benchmark-trainonly-v1/n11/tabdiff/tabdiff-n11-20260430_234952/tabular_bundle/pipeline_n11" +dst_data = os.path.join(td, "data", name) +dst_syn = os.path.join(td, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(td) +os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "") +os.environ["TABDIFF_SMOKE_STEPS"] = "500" +os.environ["TABDIFF_ADAPTER_TRAIN"] = "1" +subprocess.check_call([ + sys.executable, "-m", "tabdiff.main", + "--dataname", name, "--mode", "train", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_learnable", +]) diff --git a/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260430_234952/gen_20260430_235717.log b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260430_234952/gen_20260430_235717.log new file mode 100644 index 0000000000000000000000000000000000000000..e3f8e07a46fb3562e493c2e1d8c8ce68da14136e --- /dev/null +++ b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260430_234952/gen_20260430_235717.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2a187b75dc57c0e9de8da75b6c28dd71213398633e32406853dfa00327d85b6b +size 5234 diff --git a/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260430_234952/input_snapshot.json b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260430_234952/input_snapshot.json new file mode 100644 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sha256:a49888b32205527eafc4ffb5eba65de4c5caf474e94ca2890a41b99d0c0e2e4f +size 523301 diff --git a/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260501_040258/_tabdiff_gen.py b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260501_040258/_tabdiff_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..809de068f16506c7cee58d03ebaf82e49dee8590 --- /dev/null +++ b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260501_040258/_tabdiff_gen.py @@ -0,0 +1,36 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_n11" +src = r"/work/output-Benchmark-trainonly-v1/n11/tabdiff/tabdiff-n11-20260501_040258/tabular_bundle/pipeline_n11" +dst_data = os.path.join(td, "data", name) +dst_syn = os.path.join(td, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(td) +os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "") +subprocess.check_call([ + sys.executable, "-m", "tabdiff.main", + "--dataname", name, "--mode", "test", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_learnable", + "--ckpt_path", r"/workspace/TabDiff/tabdiff/ckpt/pipeline_n11/adapter_learnable/model_500.pt", + "--num_samples_to_generate", str(int(15215)), +]) +# test() 写入 tabdiff/result////samples.csv +import glob as g +base = os.path.join(td, "tabdiff", "result", name, r"adapter_learnable") +best = None +best_t = -1.0 +for root, _, files in os.walk(base): + if "samples.csv" in files: + p = os.path.join(root, "samples.csv") + t = os.path.getmtime(p) + if t > best_t: + best_t = t + best = p +if not best: + raise SystemExit("tabdiff: no samples.csv under " + base) +shutil.copy(best, r"/work/output-Benchmark-trainonly-v1/n11/tabdiff/tabdiff-n11-20260501_040258/tabdiff-n11-15215-20260501_041026.csv") diff --git a/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260501_040258/_tabdiff_train.py b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260501_040258/_tabdiff_train.py new file mode 100644 index 0000000000000000000000000000000000000000..94dc7809d0ecd56e23f1083d62d52826290360ea --- /dev/null +++ b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260501_040258/_tabdiff_train.py @@ -0,0 +1,21 @@ + +import os, shutil, subprocess, sys +td = r"/workspace/TabDiff" +name = r"pipeline_n11" +src = r"/work/output-Benchmark-trainonly-v1/n11/tabdiff/tabdiff-n11-20260501_040258/tabular_bundle/pipeline_n11" +dst_data = os.path.join(td, "data", name) +dst_syn = os.path.join(td, "synthetic", name) +shutil.rmtree(dst_data, ignore_errors=True) +shutil.copytree(src, dst_data) +os.makedirs(dst_syn, exist_ok=True) +for fn in ("real.csv", "test.csv", "val.csv"): + shutil.copy(os.path.join(src, fn), os.path.join(dst_syn, fn)) +os.chdir(td) +os.environ["PYTHONPATH"] = td + os.pathsep + os.environ.get("PYTHONPATH", "") +os.environ["TABDIFF_SMOKE_STEPS"] = "500" +os.environ["TABDIFF_ADAPTER_TRAIN"] = "1" +subprocess.check_call([ + sys.executable, "-m", "tabdiff.main", + "--dataname", name, "--mode", "train", "--gpu", "0", + "--no_wandb", "--exp_name", r"adapter_learnable", +]) diff --git a/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260501_040258/gen_20260501_041026.log b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260501_040258/gen_20260501_041026.log new file mode 100644 index 0000000000000000000000000000000000000000..9701a22cbf2b0bebbb2a5e537e45d3bbe3593b10 --- /dev/null +++ b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260501_040258/gen_20260501_041026.log @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:d5f2b9b75de54caa7e8c92b60117e3990f0f02a36ea983f8003b0d16a152c627 +size 5236 diff --git a/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260501_040258/input_snapshot.json b/SynthData0523/main/n11/tabdiff/tabdiff-n11-20260501_040258/input_snapshot.json new file mode 100644 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sha256:f1764cc5d7712c6440ab22a5f8591e7d131aca91949b3b159b5fc72971cd89e3 +size 523020 diff --git a/SynthData0523/main/n11/tabpfgen/n11-migrated-20260422_193053/_tabpfgen_generate.py b/SynthData0523/main/n11/tabpfgen/n11-migrated-20260422_193053/_tabpfgen_generate.py new file mode 100644 index 0000000000000000000000000000000000000000..888afbad538067e7e30e1109ba13e5980bb1ea7f --- /dev/null +++ b/SynthData0523/main/n11/tabpfgen/n11-migrated-20260422_193053/_tabpfgen_generate.py @@ -0,0 +1,87 @@ +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_191739/n11/staged/public/train.csv") +target_col = "g" + +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 +target_n = int(15215) + +# 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 {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 + +# --- 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] + +# Ensure output row count is strictly aligned with target_n. +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: + # Defensive fallback: if generator returns empty, bootstrap from training rows. + 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/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n11/tabpfgen-n11-15215-20260422_191741.csv", index=False) +print(f"[TabPFGen] Saved {len(syn_df)} rows -> /work/temp/tabpfgen_regen_parallel_deadline/20260422_191739/n11/tabpfgen-n11-15215-20260422_191741.csv") diff --git 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