efee1712aa
* fix.. speed_limit error... * draw tpms settings. * fix.. traffic light stopping only.. * fix.. waze cam * fix.. waze... * add setting (Enable comma connect ) * auto detect LFA2 * fix.. cruisespeed1 * vff2 driving model. * fix.. * agnos 12.3 * fix.. * ff * ff * test * ff * fix.. drawTurnInfo.. * Update drive_helpers.py * fix.. support eng voice eng sounds fix settings... english fix.. mph.. fix.. roadlimit speed bug.. * new vff model.. 250608 * fix soundd.. * fix safe exit speed.. * fix.. sounds. * fix.. radar timeStep.. * KerryGold model * Update drive_helpers.py * fix.. model. * fix.. * fix.. * Revert "fix.." This reverts commit b09ec459afb855c533d47fd7e8a1a6b1a09466e7. * Revert "fix.." This reverts commit 290bec6b83a4554ca232d531a911edccf94a2156. * fix esim * add more acc table. 10kph * kg update.. * fix cruisebutton mode3 * test atc..cond. * fix.. canfd * fix.. angle control limit
41 lines
1.7 KiB
Python
41 lines
1.7 KiB
Python
from tinygrad import Device
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from tinygrad.helpers import getenv, DEBUG, BEAM
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from tinygrad.engine.search import beam_search, bufs_from_lin
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from tinygrad.codegen.heuristic import hand_coded_optimizations
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from extra.optimization.helpers import load_worlds, ast_str_to_lin, time_linearizer
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if __name__ == "__main__":
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filter_reduce = bool(getenv("FILTER_REDUCE"))
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ast_strs = load_worlds(filter_reduce=filter_reduce, filter_novariable=True)
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dev = Device[Device.DEFAULT]
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test_n = getenv("TEST_N", 10)
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single = getenv("NUM", -1)
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if single != -1: ast_strs = ast_strs[single:single+1]
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beam_won, tested = 0, 0
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for num, ast in enumerate(ast_strs[:test_n]):
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def new_lin(): return ast_str_to_lin(ast, opts=dev.renderer)
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k = new_lin()
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if not (used_tensor_cores:=k.apply_tensor_cores(getenv("TC", 1))): k.apply_opts(hand_coded_optimizations(k))
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assert BEAM > 0
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lins = [(("tc" if used_tensor_cores else "hc"), k)]
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if used_tensor_cores:
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lins.append(("hc", new_lin()))
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lins[-1][1].apply_opts(hand_coded_optimizations(lins[-1][1]))
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kb = new_lin()
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test_rawbuffers = bufs_from_lin(kb) # allocate scratch buffers for optimization
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lins.append((f"beam{BEAM.value}", beam_search(kb, test_rawbuffers, BEAM.value, bool(getenv("BEAM_ESTIMATE", 1)))))
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timed = sorted([(nm, tk, time_linearizer(tk, test_rawbuffers, allow_test_size=False, clear_l2=True)) for nm, tk in lins], key=lambda x: x[2])
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if DEBUG >= 1: print(" < ".join(f"{nm:6s} : {lin.colored_shape(30, dense=True)} : {tm*1e6:8.2f} us" for nm, lin, tm in timed))
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tested += 1
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if timed[0][0].startswith("beam"):
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beam_won += 1
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print(f"{beam_won=} / {tested=} = {beam_won/tested:.3f}") |