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.
43 lines
1.8 KiB
Python
43 lines
1.8 KiB
Python
from typing_extensions import Callable
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import hashlib, random, unittest
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from tinygrad import Tensor, Device, getenv, dtypes
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from tinygrad.device import is_dtype_supported
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@unittest.skipUnless(is_dtype_supported(dtypes.uint8) and is_dtype_supported(dtypes.uint64), "Device must support uint8 and uint64")
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@unittest.skipIf(getenv("MOCKGPU") and Device.DEFAULT == "NV", "crashes in NV CI")
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class TestKeccak(unittest.TestCase):
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def setUp(self) -> None: random.seed(1337)
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def test_shape_keeping(self):
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s = (1, 2, 3, 4)
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for i in range(len(s)):
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out_shape = Tensor.randint(*s[i:], high=255, dtype=dtypes.uint8).keccak().shape
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self.assertTupleEqual(s[i:-1], out_shape[:-1])
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def test_sha3_224(self): self._test_preset("sha3_224", [143, 144])
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def test_sha3_256(self): self._test_preset("sha3_256", [135, 136])
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def test_shake_128(self): self._test_preset("shake_128", [167, 168], lambda d: hashlib.shake_128(d).digest(16))
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def _test_preset(self, name: str, special_sizes: list[int], hasher: Callable[[bytes], bytes] | None = None):
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def default_hasher(d: bytes) -> bytes: return getattr(hashlib, name)(d).digest()
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if hasher is None: hasher = default_hasher
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for n in (special_sizes + [special_sizes[0] - 1]):
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a, b = random.randbytes(n), random.randbytes(n)
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ha_ref, hb_ref = hasher(a), hasher(b)
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tres = Tensor.stack(*(Tensor(d) for d in (a, b))).keccak(name)
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ha, hb = tres[0].data(), tres[1].data()
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self.assertEqual(ha_ref, ha)
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self.assertEqual(ha_ref, Tensor(a).keccak(name).data())
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self.assertEqual(hb_ref, hb)
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def test_abc(self):
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# https://www.di-mgt.com.au/sha_testvectors.html
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out = Tensor(b"abc").keccak()
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self.assertEqual(bytes(out.tolist()), bytearray.fromhex("3a985da74fe225b2 045c172d6bd390bd 855f086e3e9d525b 46bfe24511431532"))
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if __name__ == "__main__":
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unittest.main()
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