File size: 2,189 Bytes
27813b0 | 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 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 | """Throughput of the local build against the padded-bank conv1d formulation.
python dev/bench.py
"""
import os
import sys
import time
import torch
import torch.nn.functional as Fn
ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.insert(0, ROOT)
import load_local # noqa: E402
rp = load_local.load()
PAIRS = [("44.1k -> 16k (speech in)", 44100, 16000),
("48k -> 16k (speech in)", 48000, 16000),
("16k -> 24k (tts out)", 16000, 24000),
("44.1k -> 48k (device)", 44100, 48000)]
SECONDS = 30.0
REPS = 25
def timeit(fn, reps=REPS):
for _ in range(5):
fn()
best = 1e30
for _ in range(reps):
t0 = time.perf_counter()
fn()
best = min(best, time.perf_counter() - t0)
return best
def ref(x, plan):
L, M, width, kern = plan.L, plan.M, plan.width, plan.kernel
B, T = x.shape
pad = Fn.pad(x, (width, width + M))
r = Fn.conv1d(pad[:, None], kern[:, None, :], stride=M)
return r.transpose(1, 2).reshape(B, -1)[:, :plan.out_len(T)]
print(f"threads={torch.get_num_threads()} audio={SECONDS:.0f}s mono\n")
print(f"{'conversion':28} {'resample-poly':>13} {'conv1d bank':>12} "
f"{'speedup':>8} {'taps/out':>9} {'path':>6}")
for name, orig, new in PAIRS:
T = int(orig * SECONDS)
g = torch.Generator().manual_seed(0)
x = torch.randn(1, T, generator=g, dtype=torch.float32)
plan = rp.Resampler(orig, new)
t_mine = timeit(lambda: plan(x))
t_ref = timeit(lambda: ref(x, plan))
a, b = plan(x), ref(x, plan)
rel = ((a - b).abs().max() / b.abs().max()).item()
assert rel < 2e-5, rel
print(f"{name:28} {t_mine*1e3:12.2f}ms {t_ref*1e3:11.2f}ms "
f"{t_ref/t_mine:7.2f}x {plan.taps_per_output:9.1f} "
f"{'fused' if plan.fused else 'bank':>6}")
plan = rp.Resampler(44100, 16000)
x = torch.randn(1, int(44100 * SECONDS), dtype=torch.float32)
t = timeit(lambda: plan(x))
print(f"\n44.1k->16k realtime factor: {SECONDS / t:,.0f}x "
f"({t*1e3:.2f} ms for {SECONDS:.0f} s)")
print(f"taps stored {plan.taps.numel()} of {plan.kernel.numel()} "
f"padded-bank entries ({plan.density*100:.1f}%)")
|