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fuzz test transcend math (#5383)

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* fuzz test transcend math

found something wrong with float64 sin reduction

```
from tinygrad import Tensor, dtypes
import numpy as np
print(Tensor([39800.0], dtype=dtypes.float64).sin().numpy())
print(Tensor([39800.0], dtype=dtypes.float32).sin().numpy())
print(Tensor([39800.0], dtype=dtypes.float16).sin().numpy())
print(np.sin(np.array([39800.0], dtype=np.float64)))
print(np.sin(np.array([39800.0], dtype=np.float32)))
print(np.sin(np.array([39800.0], dtype=np.float16)))
```

```
CLANG=1 python test.py
[0.92785633]
[0.7428573]
[-0.7705]
[0.74285722]
[0.7428572]
[-0.7705]
```

* fix test

* abs

* skip
This commit is contained in:
chenyu
2024-07-13 01:54:52 -04:00
committed by GitHub
parent 3a7262d923
commit e398734890
1 changed files with 40 additions and 2 deletions
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42
test/test_transcendental.py
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@@ -1,7 +1,45 @@
import unittest
from tinygrad.tensor import Tensor
from tinygrad.helpers import Context
from tinygrad import Tensor, Device, dtypes
from tinygrad.tensor import _to_np_dtype
from tinygrad.helpers import Context, getenv
from test.test_schedule import check_schedule
from test.test_dtype_alu import ht
from test.helpers import is_dtype_supported
import numpy as np
from hypothesis import given, settings, strategies as strat
settings.register_profile("my_profile", max_examples=200, deadline=None, derandomize=getenv("DERANDOMIZE_CI", False))
settings.load_profile("my_profile")
class TestTranscendentalMath(unittest.TestCase):
@unittest.skipUnless(is_dtype_supported(dtypes.float64, Device.DEFAULT), f"no float64 on {Device.DEFAULT}")
@unittest.skipIf(getenv("CUDACPU") or (getenv("MOCKGPU") and Device.DEFAULT == "NV"), "crashed")
@given(ht.float64, strat.sampled_from([(Tensor.exp, np.exp), (Tensor.log, np.log), (Tensor.sin, np.sin)]))
def test_float64(self, x, op):
if op[0] == Tensor.sin:
# TODO: reduction does not work
if abs(x) > 2 ** 32: return
with Context(TRANSCENDENTAL=2):
np.testing.assert_allclose(op[0](Tensor([x], dtype=dtypes.float64)).numpy(),
op[1](np.array([x], dtype=_to_np_dtype(dtypes.float64))),
atol=1e-5)
@unittest.skipIf(getenv("CUDACPU") or (getenv("MOCKGPU") and Device.DEFAULT == "NV"), "crashed")
@given(ht.float32, strat.sampled_from([(Tensor.exp, np.exp), (Tensor.log, np.log), (Tensor.sin, np.sin)]))
def test_float32(self, x, op):
with Context(TRANSCENDENTAL=2):
np.testing.assert_allclose(op[0](Tensor([x], dtype=dtypes.float32)).numpy(),
op[1](np.array([x], dtype=_to_np_dtype(dtypes.float32))),
atol=1e-5)
@unittest.skipUnless(is_dtype_supported(dtypes.float16, Device.DEFAULT), f"no float16 on {Device.DEFAULT}")
@given(ht.float16, strat.sampled_from([(Tensor.exp, np.exp), (Tensor.log, np.log), (Tensor.sin, np.sin)]))
def test_float16(self, x, op):
with Context(TRANSCENDENTAL=2):
np.testing.assert_allclose(op[0](Tensor([x], dtype=dtypes.float16)).numpy(),
op[1](np.array([x], dtype=_to_np_dtype(dtypes.float16))),
atol=1e-2, rtol=2e-3)
class TestTranscendentalSchedule(unittest.TestCase):
# w/ payne_hanek_reduction (fp32)