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
54 lines
2.1 KiB
Python
54 lines
2.1 KiB
Python
import numpy as np
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from tinygrad import dtypes, Tensor
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from tinygrad.helpers import getenv, get_single_element
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from tinygrad.dtype import _to_np_dtype
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from tinygrad.codegen.kernel import OptOps
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from tinygrad.engine.realize import lower_schedule
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dtype_in = dtypes.half if getenv("HALF") else dtypes.bfloat16 if getenv("BFLOAT16") else dtypes.float
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acc_dtype = dtypes.half if getenv("ACC_HALF") else dtypes.bfloat16 if getenv("ACC_BFLOAT16") else None
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if getenv("INT"): dtype_in, acc_dtype = dtypes.int8, dtypes.int32
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if getenv("UINT"): dtype_in, acc_dtype = dtypes.uint8, dtypes.int32
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N = getenv("N", 4096)
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M = getenv("M", N)
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K = getenv("K", N)
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CNT = getenv("CNT", 10)
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ATOL = getenv("ATOL", 1e-4)
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RTOL = getenv("RTOL", 3e-2)
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INT_LOW = getenv("INT_LOW", 0)
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INT_HIGH = getenv("INT_HIGH", 10)
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if __name__ == "__main__":
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def init_matrix(rows, cols):
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rng = np.random.default_rng()
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# NOTE: numpy does not support bfloat16
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if (np_dtype := _to_np_dtype(dtype_in)) is None: np_dtype = np.float32
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if dtype_in in dtypes.ints:
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return Tensor(rng.integers(INT_LOW, INT_HIGH, (rows, cols), dtype=np_dtype)).realize()
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return Tensor(rng.random((rows, cols), dtype=np.float32).astype(np_dtype)-0.5).cast(dtype_in).realize()
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a, b = init_matrix(M, K), init_matrix(K, N)
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for i in range(CNT):
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if i > 0 and getenv("RAND", 0) != 0:
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a, b = init_matrix(M, K), init_matrix(K, N)
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c = a.matmul(b, dtype=acc_dtype).realize()
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if getenv("SHOULD_USE_TC"):
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sched = a.matmul(b, dtype=acc_dtype).schedule()
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lowered = list(lower_schedule(sched))
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ei = get_single_element(lowered)[1]
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assert any(opt.op is OptOps.TC for opt in ei.prg.p.applied_opts), f"TC not triggered, {ei.prg.p.applied_opts}"
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ref = a.numpy().astype(np.float32) @ b.numpy().astype(np.float32)
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res = c.numpy()
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try:
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np.testing.assert_allclose(res, ref, rtol=RTOL, atol=ATOL)
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except AssertionError as e:
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if getenv("DEBUG_VALUES", 0) > 0:
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mismatch = np.where(~np.isclose(res, ref, rtol=RTOL, atol=ATOL))
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print("Mismatch indices:", mismatch)
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print("Result :", res[mismatch])
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print("Ground truth :", ref[mismatch])
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raise e
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