Files
StarPilot/tinygrad_repo/test/external/external_test_example.py
T
firestar5683 22a8575199 Vendor dependencies and resources for standalone builds
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.
2026-10-03 21:01:18 +00:00

75 lines
2.0 KiB
Python

import unittest, sys
from tinygrad import Device
from tinygrad.tensor import Tensor
from tinygrad.helpers import getenv, OSX
def multidevice_test(fxn):
exclude_devices = getenv("EXCLUDE_DEVICES", "").split(",")
def ret(self):
for device in Device._devices:
# broken on OSX USB AMD, why?
if device in ["DISK", "NPY", "FAKE", "DSP", "NULL"] or (OSX and device in ["AMD"]): continue
if sys.stdout.isatty(): print(device)
if device in exclude_devices:
if sys.stdout.isatty(): print(f"WARNING: {device} test is excluded")
continue
with self.subTest(device=device):
try:
Device[device]
except Exception:
if sys.stdout.isatty(): print(f"WARNING: {device} test isn't running")
continue
fxn(self, device)
return ret
class TestExample(unittest.TestCase):
@multidevice_test
def test_convert_to_cpu(self, device):
a = Tensor([[1,2],[3,4]], device=device)
assert a.numpy().shape == (2,2)
b = a.to("CPU")
assert b.numpy().shape == (2,2)
@multidevice_test
def test_2_plus_3(self, device):
a = Tensor([2], device=device)
b = Tensor([3], device=device)
result = a + b
print(f"{a.numpy()} + {b.numpy()} = {result.numpy()}")
assert result.numpy()[0] == 5.
@multidevice_test
def test_example_readme(self, device):
x = Tensor.eye(3).clone().to(device)
y = Tensor([[2.0,0,-2.0]], device=device)
z = y.matmul(x).sum()
z.backward()
x.grad.numpy() # dz/dx
y.grad.numpy() # dz/dy
assert x.grad.device == device
assert y.grad.device == device
@multidevice_test
def test_example_matmul(self, device):
try:
Device[device]
except Exception:
print(f"WARNING: {device} test isn't running")
return
x = Tensor.eye(8).clone().to(device)
y = Tensor.eye(8).clone().to(device)
z = y.matmul(x).sum()
z.backward()
x.grad.numpy() # dz/dx
y.grad.numpy() # dz/dy
assert x.grad.device == device
assert y.grad.device == device
if __name__ == '__main__':
unittest.main()