Function bench

tests/profile_subclass/profiling.py:30–42

(t1, t2)

def bench(t1, t2):
    bench_times = []
    for _ in range(NUM_REPEAT_OF_REPEATS):
        with PerfContext() as pc:
            for _ in range(NUM_REPEATS):
                torch.add(t1, t2)
        bench_times.append(pc.total_time)

    bench_time_min = float(torch.min(torch.Tensor(bench_times))) / NUM_REPEATS
    bench_time_avg = float(torch.sum(torch.Tensor(bench_times))) / (NUM_REPEATS * NUM_REPEAT_OF_REPEATS)
    bench_time_med = float(torch.median(torch.Tensor(bench_times))) / NUM_REPEATS
    bench_std = float(torch.std(torch.Tensor(bench_times))) / NUM_REPEATS
    return bench_time_min, bench_time_avg, bench_time_med, bench_std


def main():