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import torch | |
from ..utils.tools import get_class | |
from .eval_pipeline import EvalPipeline | |
def get_benchmark(benchmark): | |
return get_class(f"{__name__}.{benchmark}", EvalPipeline) | |
def run_benchmark(benchmark, eval_conf, experiment_dir, model=None): | |
"""This overwrites existing benchmarks""" | |
experiment_dir.mkdir(exist_ok=True, parents=True) | |
bm = get_benchmark(benchmark) | |
pipeline = bm(eval_conf) | |
return pipeline.run( | |
experiment_dir, model=model, overwrite=True, overwrite_eval=True | |
) | |