File size: 1,151 Bytes
0cc8c0e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 |
import os, shutil, subprocess, sys
td = r"/workspace/TabDiff"
name = r"pipeline_m5"
src = r"/work/output-Benchmark-trainonly-v1/m5/tabdiff/tabdiff-m5-20260510_071943/tabular_bundle/pipeline_m5"
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"] = "200"
os.environ["TABDIFF_STEPS"] = "200"
os.environ["TABDIFF_BATCH_SIZE"] = "256"
os.environ["TABDIFF_TRAIN_BATCH_SIZE"] = "256"
os.environ["TABDIFF_LR"] = "0.0005"
os.environ["TABDIFF_LEARNING_RATE"] = "0.0005"
os.environ["TABDIFF_NUM_TIMESTEPS"] = "50"
os.environ["TABDIFF_TIMESTEPS"] = "50"
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",
])
|