TabQueryBench's picture
Add files using upload-large-folder tool
a2d108c verified
Raw
History Blame Contribute Delete
1.39 kB
import os, shutil, subprocess, sys
root = r"/workspace/ef-vfm"
rt = r"/work/output-Benchmark-trainonly-v1/c19/tabbyflow/tabbyflow-c19-20260510_210211/_efvfm_runtime"
name = r"pipeline_c19"
src = r"/work/output-Benchmark-trainonly-v1/c19/tabbyflow/tabbyflow-c19-20260510_210211/tabular_bundle/pipeline_c19"
shutil.rmtree(rt, ignore_errors=True)
def _ignore(_, names):
skip = {"__pycache__", "data", "synthetic", "result", "results", "ckpt"}
return [n for n in names if n in skip or n.endswith(".pyc")]
shutil.copytree(root, rt, ignore=_ignore)
dst_data = os.path.join(rt, "data", name)
dst_syn = os.path.join(rt, "synthetic", name)
shutil.rmtree(dst_data, ignore_errors=True)
os.makedirs(os.path.dirname(dst_data), exist_ok=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(rt)
os.environ["PYTHONPATH"] = rt + os.pathsep + os.environ.get("PYTHONPATH", "")
os.environ["EFVFM_SMOKE_STEPS"] = "100"
os.environ["EFVFM_ADAPTER_TRAIN"] = "1"
os.environ.setdefault("EFVFM_SAMPLE_BATCH_SIZE", "128")
os.environ.setdefault("EFVFM_EVAL_NUM_SAMPLES", "512")
subprocess.check_call([
sys.executable, os.path.join(rt, "main.py"),
"--dataname", name, "--mode", "train", "--gpu", "0",
"--no_wandb", "--exp_name", r"adapter_efvfm",
])