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pybench.py
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pybench.py
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from time import time_ns
import rlbot_flatbuffers as flat
def test_gtp():
print("Testing GamePacket")
pack_times = []
unpack_times = []
gtp = flat.GamePacket(
balls=[flat.BallInfo(shape=flat.SphereShape()) for _ in range(128)],
players=[flat.PlayerInfo() for _ in range(128)],
boost_pads=[flat.BoostPadState() for _ in range(128)],
teams=[flat.TeamInfo() for _ in range(2)],
)
for _ in range(20_000):
start = time_ns()
packed = gtp.pack()
pack_times.append(time_ns() - start)
start = time_ns()
flat.GamePacket.unpack(packed)
unpack_times.append(time_ns() - start)
avg_time_ns = sum(pack_times) / len(pack_times)
print(f"Average pack time per: {avg_time_ns / 1000:.1f}us")
print(f"Minimum pack time per: {min(pack_times) / 1000:.1f}us")
avg_time_ns = sum(unpack_times) / len(unpack_times)
print(f"Average unpack time per: {avg_time_ns / 1000:.1f}us")
print(f"Minimum unpack time per: {min(unpack_times) / 1000:.1f}us")
def test_ballpred():
print("Testing 10s BallPrediction")
times = []
ballPred = flat.BallPrediction([flat.PredictionSlice(1) for _ in range(120 * 10)])
print(len(ballPred.pack()))
for _ in range(40_000):
start = time_ns()
packed = ballPred.pack()
flat.BallPrediction.unpack(packed)
times.append(time_ns() - start)
print(f"Total time: {sum(times) / 1_000_000_000:.3f}s")
avg_time_ns = sum(times) / len(times)
print(f"Average time per: {avg_time_ns / 1000:.1f}us")
print(f"Minimum time per: {min(times) / 1000:.1f}us")
print()
print("Testing 6s BallPrediction")
times = []
ballPred = flat.BallPrediction([flat.PredictionSlice(1) for _ in range(120 * 6)])
print(len(ballPred.pack()))
for _ in range(40_000):
start = time_ns()
packed = ballPred.pack()
flat.BallPrediction.unpack(packed)
times.append(time_ns() - start)
print(f"Total time: {sum(times) / 1_000_000_000:.3f}s")
avg_time_ns = sum(times) / len(times)
print(f"Average time per: {avg_time_ns / 1000:.1f}us")
print(f"Minimum time per: {min(times) / 1000:.1f}us")
def find_slice_at_time(ball_prediction: flat.BallPrediction, game_time: float):
"""
This will find the future position of the ball at the specified time. The returned
Slice object will also include the ball's velocity, etc.
"""
start_time = ball_prediction.slices[0].game_seconds
approx_index = int(
(game_time - start_time) * 120
) # We know that there are 120 slices per second.
if 0 <= approx_index < len(ball_prediction.slices):
return ball_prediction.slices[approx_index]
return None
def test_loop():
print("Testing access times")
ballPred = flat.BallPrediction([flat.PredictionSlice(1) for _ in range(120 * 6)])
start = time_ns()
for _ in range(100):
li = []
for t in range(1, 301):
ball_in_future = find_slice_at_time(ballPred, t / 60)
li.append(ball_in_future)
print(f"Total time: {(time_ns() - start) / 1_000_000:.3f}ms")
times = []
for _ in range(50_000):
start = time_ns()
li = []
for t in range(1, 301):
ball_in_future = find_slice_at_time(ballPred, t / 60)
li.append(ball_in_future)
times.append(time_ns() - start)
print()
print(f"Total time: {sum(times) / 1_000_000_000:.3f}s")
avg_time_ns = sum(times) / len(times)
print(f"Average time per: {avg_time_ns / 1000:.1f}us")
print(f"Minimum time per: {min(times) / 1000:.1f}us")
times = []
for _ in range(50_000):
start = time_ns()
li = [find_slice_at_time(ballPred, t / 60) for t in range(1, 301)]
times.append(time_ns() - start)
print()
print(f"Total time: {sum(times) / 1_000_000_000:.3f}s")
avg_time_ns = sum(times) / len(times)
print(f"Average time per: {avg_time_ns / 1000:.1f}us")
print(f"Minimum time per: {min(times) / 1000:.1f}us")
times = []
for _ in range(1_000_000):
start = time_ns()
li = list(ballPred.slices[1:602:2])
times.append(time_ns() - start)
print()
print(f"Total time: {sum(times) / 1_000_000_000:.3f}s")
avg_time_ns = sum(times) / len(times)
print(f"Average time per: {avg_time_ns / 1000:.1f}us")
print(f"Minimum time per: {min(times) / 1000:.1f}us")
if __name__ == "__main__":
test_gtp()
print()
test_ballpred()
print()
test_loop()