9c7833faf9
* Vegetarian Filet o Fish model * fix.. atc.. * test cluster_speed_limit * fix.. cluster_speed_limit.. 2 * fix.. clusterspeedlimit3 * cruise speed to roadlimit speed * fix.. * fix.. eng * deltaUp/Down for lanechange * fix.. atc desire... * fix.. * ff * ff * fix.. * fix.. eng * fix engsound * Update desire_helper.py * fix.. connect... * fix curve_min speed * Revert "fix curve_min speed" This reverts commit fcc9c2eb14eb3504abef3e420db93e8882e56f37. * Reapply "fix curve_min speed" This reverts commit 2d2bba476c58a7b4e13bac3c3ad0e4694c95515d. * fix.. auto speed up.. roadlimit * fix.. atc auto lanechange... * Update desire_helper.py * Update cruise.py * debug atc... * fix.. waze alert offset.. * fix.. * test atc.. * fix.. * fix.. atc * atc test.. * fix.. atc * fix.. atc2 * fix.. atc3 * KerryGold Model. latsmooth_sec = 0.0 * lat smooth seconds 0.13 * fix comment * fix.. auto cruise, and speed unit * change lanemode switching. * erase mazda lkas button.
21 lines
727 B
Python
21 lines
727 B
Python
from tinygrad import Tensor, dtypes
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from tinygrad.engine.jit import TinyJit
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from tinygrad.helpers import Timing, getenv
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if __name__ == "__main__":
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BS = getenv("BS", 2**14)
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BLOCKSIZE = getenv("BLOCKSIZE", 4096)
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HASHFN = getenv("HASHFN", "shake_128")
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NRUNS = getenv("NRUNS", 5)
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@TinyJit
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def hasher(data: Tensor): return data.keccak(HASHFN)
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t = Tensor.randn(BS, BLOCKSIZE, dtype=dtypes.uint8).realize()
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ds_mib = t.nbytes() / 1024**2
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print(f"--- benchmarking (hash: {HASHFN}, data size: {ds_mib} MiB, block size: {BLOCKSIZE} B, batch size: {BS})")
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for i in range(NRUNS):
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with Timing(f"run: {i+1}, elapsed time: ", (lambda et: f", throughput: {ds_mib / (et*1e-9):.2f} MiB/s")):
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hasher(t).realize()
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