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tinygrad
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skip a few clang test that took > 30 seconds in CI (#4126) 

* skip slow CLANG test test_train_cifar

* skip those too

* and that

* only CI

* one more
This commit is contained in:
chenyu 2024-04-10 02:00:34 -04:00 committed by GitHub
parent 08ddeb5685
commit 6bbbeb93ac
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3 changed files with 9 additions and 9 deletions
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4
test/models/test_mnist.py
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@ -1,8 +1,9 @@
#!/usr/bin/env python
import unittest
import numpy as np
from tinygrad import Tensor, Device
from tinygrad.helpers import CI
from tinygrad.nn.state import get_parameters
from tinygrad.tensor import Tensor
from tinygrad.nn import optim, BatchNorm2d
from extra.training import train, evaluate
from extra.datasets import fetch_mnist
@ -48,6 +49,7 @@ class TinyConvNet:
x = x.reshape(shape=[x.shape[0], -1])
return x.dot(self.l1)
@unittest.skipIf(CI and Device.DEFAULT == "CLANG", "slow")
class TestMNIST(unittest.TestCase):
def test_sgd_onestep(self):
np.random.seed(1337)

6
test/models/test_real_world.py
View File

@ -64,7 +64,6 @@ class TestRealWorld(unittest.TestCase):
return t.realize()
helper_test("test_mini_sd", lambda: (Tensor.empty(4, 16, 8, 8), Tensor.empty(1, 24)), test, 0.01, 43)
@unittest.skipIf(Device.DEFAULT == "LLVM", "LLVM segmentation fault")
@unittest.skipUnless(is_dtype_supported(dtypes.float16), "need dtypes.float16")
def test_llama(self):
dtypes.default_float = dtypes.float16
@ -89,6 +88,7 @@ class TestRealWorld(unittest.TestCase):
def test(t, v): return model(t, v).realize()
helper_test("test_gpt2", lambda: (Tensor([[1,]]),Variable("pos", 1, 100).bind(1)), test, 0.23 if CI else 0.9, 164 if CI else 468, all_jitted=True)
@unittest.skipIf(CI and Device.DEFAULT == "CLANG", "slow")
def test_train_mnist(self):
from examples.beautiful_mnist import Model
with Tensor.train():
@ -106,8 +106,7 @@ class TestRealWorld(unittest.TestCase):
helper_test("train_mnist", lambda: (Tensor.randn(BS, 1, 28, 28),), train, 0.07, 127)
@unittest.skipIf(Device.DEFAULT == "LLVM", "LLVM segmentation fault")
@unittest.skipUnless(is_dtype_supported(dtypes.float16), "need dtypes.float16")
@unittest.skipIf(CI and Device.DEFAULT in {"CLANG", "GPU"}, "slow")
def test_train_cifar(self):
with Tensor.train():
model = SpeedyResNet(Tensor.ones((12,3,2,2)))
@ -125,7 +124,6 @@ class TestRealWorld(unittest.TestCase):
helper_test("train_cifar", lambda: (Tensor.randn(BS, 3, 32, 32),), train, (1.0/48)*BS, 142 if CI else 154) # it's 154 on metal
@unittest.skipIf(Device.DEFAULT == "LLVM", "LLVM segmentation fault")
@unittest.skipUnless(is_dtype_supported(dtypes.float16), "need dtypes.float16")
def test_train_cifar_hyp(self):
dtypes.default_float = dtypes.float16

8
test/test_fuzz_shape_ops.py
View File

@ -6,7 +6,7 @@ from hypothesis.extra import numpy as stn
import numpy as np
import torch
import tinygrad
from tinygrad import Tensor, Device
from tinygrad.helpers import CI
@ -26,9 +26,9 @@ def st_shape(draw) -> tuple[int, ...]:
return s
def tensors_for_shape(s:tuple[int, ...]) -> tuple[torch.tensor, tinygrad.Tensor]:
def tensors_for_shape(s:tuple[int, ...]) -> tuple[torch.tensor, Tensor]:
x = np.arange(prod(s)).reshape(s)
return torch.from_numpy(x), tinygrad.Tensor(x)
return torch.from_numpy(x), Tensor(x)
def apply(tor, ten, tor_fn, ten_fn=None):
ok = True
@ -38,7 +38,7 @@ def apply(tor, ten, tor_fn, ten_fn=None):
except: ten, ok = None, not ok # noqa: E722
return tor, ten, ok
@unittest.skipIf(CI and Device.DEFAULT == "CLANG", "slow")
class TestShapeOps(unittest.TestCase):
@settings.get_profile(__file__)
@given(st_shape(), st_int32, st.one_of(st_int32, st.lists(st_int32)))