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b/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/_fd_X_host.npy new file mode 100644 index 0000000000000000000000000000000000000000..e2da562794cfebfd0e75de6417b0c1ec8351b2e9 --- /dev/null +++ b/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/_fd_X_host.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e794179fed0c3687b848213d44e032a3e33b4023229518cd49d24bbc3de9028d +size 151680 diff --git a/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/_fd_gen.py b/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/_fd_gen.py new file mode 100644 index 0000000000000000000000000000000000000000..0c62d758259da980f6f30b37cf20a4edcb10f910 --- /dev/null +++ b/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/_fd_gen.py @@ -0,0 +1,8 @@ + +import joblib, pandas as pd +m, meta = joblib.load(r'/work/output-Benchmark-trainonly-v1/c4/forestdiffusion/forest-c4-20260510_204828/forestdiffusion_model.joblib') +# generate：batch_size 为样本数 +arr = m.generate(batch_size=int(2557)) +df = pd.DataFrame(arr, columns=meta["column_names"]) +df.to_csv(r'/work/output-Benchmark-trainonly-v1/c4/forestdiffusion/forest-c4-20260510_204828/forest-c4-2557-20260510_204830.csv', index=False) +print("saved", len(df)) diff --git a/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/_fd_meta_host.json b/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/_fd_meta_host.json new file mode 100644 index 0000000000000000000000000000000000000000..c604592afca1cb13b9530e8e34e5dffee99f418e --- /dev/null +++ b/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/_fd_meta_host.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:227c2db87750413f68a3d9b29d0ec01899712314270c64a5d85ae9a2649bb366 +size 498 diff --git a/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/_fd_train.py b/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/_fd_train.py new file mode 100644 index 0000000000000000000000000000000000000000..246dcea9825c7e14729f1500c7cb561e0b1997cb --- /dev/null +++ b/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/_fd_train.py @@ -0,0 +1,36 @@ + +import os, shutil, json +with open('/tmp/pgrep', 'w') as _f: + _f.write("#!/usr/bin/env python3\n") + _f.write("import subprocess, sys\n") + _f.write("ppid = sys.argv[-1]\n") + _f.write("out = subprocess.check_output(['ps', '-o', 'pid=', '--ppid', str(ppid)], text=True)\n") + _f.write("print(out, end='')\n") +os.chmod('/tmp/pgrep', 0o755) +os.environ['PATH'] = '/tmp:' + os.environ.get('PATH', '') +shutil.copy(r'/work/output-Benchmark-trainonly-v1/c4/forestdiffusion/forest-c4-20260510_204828/_fd_X_host.npy', '/tmp/fd_X.npy') +with open(r'/work/output-Benchmark-trainonly-v1/c4/forestdiffusion/forest-c4-20260510_204828/_fd_meta_host.json') as f: + open('/tmp/fd_meta.json','w').write(f.read()) + +import numpy as np, joblib, json, os +from ForestDiffusion import ForestDiffusionModel +X = np.load("/tmp/fd_X.npy") +with open("/tmp/fd_meta.json") as f: + meta = json.load(f) +cat_indexes = meta["cat_indexes"] +print( + "[ForestDiffusion] train config: " + f"rows={X.shape[0]} cols={X.shape[1]} n_t=2 " + f"n_estimators=1 duplicate_K=1 n_jobs=1 " + f"max_depth=2 xgb_verbosity=0 xgb_nthread=1", + flush=True, +) +m = ForestDiffusionModel( + X, n_t=2, n_estimators=1, duplicate_K=1, n_jobs=1, + model="xgboost", max_depth=2, tree_method="hist", cat_indexes=cat_indexes, + verbosity=0, nthread=1, +) +joblib.dump((m, meta), "/tmp/fd_model.joblib") +print("ForestDiffusion train OK") + +shutil.copy('/tmp/fd_model.joblib', r'/work/output-Benchmark-trainonly-v1/c4/forestdiffusion/forest-c4-20260510_204828/forestdiffusion_model.joblib') diff --git a/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/forest-c4-2557-20260510_204830.csv b/SynthData0523/main/c4/forestdiffusion/forest-c4-20260510_204828/forest-c4-2557-20260510_204830.csv new file mode 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