mirror of
https://github.com/firestar5683/StarPilot.git
synced 2026-11-08 05:23:41 +08:00
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.
55 lines
2.3 KiB
Python
55 lines
2.3 KiB
Python
import unittest
|
|
from tinygrad import Tensor, Device, dtypes
|
|
from tinygrad.helpers import DEV
|
|
# similar to test/external/external_test_gpu_ast.py, but universal
|
|
|
|
@unittest.skipIf(Device.DEFAULT in {"CUDA", "NV"} and DEV.interface.startswith("MOCK"), "slow on ocelot")
|
|
class TestSpecific(unittest.TestCase):
|
|
# from openpilot
|
|
|
|
# 1x1 6 <- 24
|
|
def test_1x1_6_24(self):
|
|
x = Tensor.randn(1, 24*4, 32, 64)
|
|
w = Tensor.randn(6*4, 24*4, 1, 1)
|
|
x.conv2d(w).permute(0,2,3,1).reshape(32, 384, 4).contiguous().realize()
|
|
|
|
def test_vec_mul(self):
|
|
# this forces it to be an image...
|
|
x = Tensor.ones(1, 512, 4).contiguous().reshape(1, 2048)
|
|
w = Tensor.randn(2048, 512)
|
|
(x @ w).reshape(1, 128, 4).contiguous().realize()
|
|
|
|
@unittest.skipUnless(dtypes.float16 in Device[Device.DEFAULT].renderer.supported_dtypes(), "need float16 support")
|
|
def test_big_vec_mul(self):
|
|
# from LLaMA
|
|
# 0 buffer<4096, dtypes.float> [View((1024, 1, 1, 4), (4, 0, 0, 1), 0, None)]
|
|
# 1 buffer<4096, dtypes.float> [View((1024, 1024, 4, 4), (0, 4, 1, 0), 0, None)]
|
|
# 2 buffer<16777216, dtypes.half> [View((1024, 1024, 4, 4), (16384, 4, 1, 4096), 0, None)]
|
|
x = Tensor.randn(4096).realize()
|
|
w = Tensor.randn(4096, 4096, dtype=dtypes.float16).realize()
|
|
(x @ w.T).realize()
|
|
|
|
# from https://dl.acm.org/doi/pdf/10.1145/3495243.3517020
|
|
|
|
# ~260 GFLOPS on Adreno 640, should be 260*(720/890)*(596/710) = 176.5 on downclocked 630
|
|
# we get 170
|
|
def test_1x1_28_28(self):
|
|
x = Tensor.randn(1, 256, 28, 28)
|
|
w = Tensor.randn(256, 256, 1, 1)
|
|
x.conv2d(w).permute(0,2,3,1).reshape(28, 28*256//4, 4).contiguous().realize()
|
|
|
|
# 132 GFLOPS on Adreno 640, should be 132*(720/890)*(596/710) = 90 on downclocked 630
|
|
# gets 54 with broken opt, 74 without opt, and 146 if we pad and opt 3!
|
|
def test_3x3_28_28_stride_2(self):
|
|
x = Tensor.randn(1, 288, 36, 36)
|
|
w = Tensor.randn(384, 288, 3, 3)
|
|
x.conv2d(w, stride=2).permute(0,2,3,1).reshape(17, 17*384//4, 4).contiguous().realize()
|
|
|
|
def test_3x3_28_28_stride_2_padded(self):
|
|
x = Tensor.randn(1, 288, 36, 36)
|
|
w = Tensor.randn(384, 288, 3, 3)
|
|
x.conv2d(w, stride=2, padding=1).permute(0,2,3,1).reshape(18, 18*384//4, 4).contiguous().realize()
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|