mirror of https://github.com/commaai/tinygrad.git
31 lines
1.1 KiB
Python
31 lines
1.1 KiB
Python
import numpy as np
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from tinygrad.helpers import getenv
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from tinygrad import dtypes, Tensor, Device
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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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GPUS = getenv("GPUS", 0)
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M = getenv("M", 16384)
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N = getenv("N", 4096)
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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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def _rand(device):
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a, b = Tensor.rand(M, N, dtype=dtype_in).realize(), Tensor.rand(N, dtype=dtype_in).realize()
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if isinstance(device, tuple):
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a.shard_(device, axis=1)
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b.shard_(device, axis=0)
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return a, b
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if __name__ == "__main__":
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device = tuple(f"{Device.DEFAULT}:{i}" for i in range(GPUS)) if GPUS > 1 else Device.DEFAULT
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a, b = _rand(device)
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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 = _rand(device)
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c = a.matmul(b, acc_dtype=acc_dtype).realize()
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nc = c.numpy()
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comp = a.numpy().astype(np.float32) @ b.numpy().astype(np.float32)
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np.testing.assert_allclose(nc, comp, atol=ATOL, rtol=RTOL)
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