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https://github.com/firestar5683/StarPilot.git
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firestar5683
22a8575199
Keep official openpilot ancestry and dependency licenses. Store resources directly in Git, remove LFS setup requirements, and leave the downloadable big model outside the source tree.
34 lines
1.3 KiB
Python
34 lines
1.3 KiB
Python
from tinygrad.helpers import getenv
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from tinygrad import dtypes, Tensor
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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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CNT = getenv("CNT", 8)
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BS = getenv("BS", 16)
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CIN = getenv("CIN", 128)
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COUT = getenv("COUT", 128)
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HW = getenv("HW", 128)
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K = getenv("K", 3)
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PADDING = getenv("PADDING", 1)
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COMP = getenv("COMP", 0)
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ATOL = getenv("ATOL", 1e-4)
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RTOL = getenv("RTOL", 3e-2)
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FLOPS = BS*K*K*CIN*HW*HW*COUT*2
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def rand_input(): return Tensor.rand(BS, CIN, HW, HW, dtype=dtype_in).realize(), Tensor.rand(COUT, CIN, K, K, dtype=dtype_in).realize()
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if __name__ == "__main__":
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a, b = rand_input()
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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_input()
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c = a.conv2d(b, padding=PADDING, dtype=acc_dtype).realize()
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if COMP:
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import numpy as np, time, torch
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torch_device = "cuda:0" if torch.cuda.is_available() else ("mps" if getenv("MPS", 0) else "cpu")
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ta, tb = torch.from_numpy(a.numpy()).to(torch_device), torch.from_numpy(b.numpy()).to(torch_device)
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tc = torch.nn.functional.conv2d(ta, tb, padding=PADDING)
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np.testing.assert_allclose(c.numpy(), tc.cpu(), atol=ATOL, rtol=RTOL)
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