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remove staticmethod dtypes.max/min (#15227)

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always use x.dtype.max/min
This commit is contained in:
chenyu
2026-03-11 23:11:24 -04:00
committed by GitHub
parent 18dc77ccab
commit 842c978df3
13 changed files with 41 additions and 48 deletions
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3
test/backend/test_dtype.py
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@@ -101,7 +101,7 @@ class TestDType(unittest.TestCase):
@unittest.skipIf(isinstance(Device[Device.DEFAULT].renderer, (PTXRenderer, NIRRenderer)), "skip for now")
def test_uint_overflow(self):
if not dtypes.is_unsigned(self.DTYPE): raise unittest.SkipTest("only for unsigned")
v = dtypes.max(self.DTYPE)
v = self.DTYPE.max
_test_to_np(Tensor(v, dtype=self.DTYPE)+2, _to_np_dtype(self.DTYPE), np.array(v, dtype=_to_np_dtype(self.DTYPE))+2)
_test_to_np(Tensor(v, dtype=self.DTYPE)*2, _to_np_dtype(self.DTYPE), np.array(v, dtype=_to_np_dtype(self.DTYPE))*2)
@@ -516,4 +516,3 @@ class TestOpsBFloat16(unittest.TestCase):
if __name__ == '__main__':
unittest.main()

2
test/backend/test_dtype_alu.py
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@@ -366,7 +366,7 @@ class TestDTypeALU(unittest.TestCase):
@unittest.expectedFailure
def test_unsafe_cast_float_to_int_failure(self):
val = float(dtypes.max(dtypes.int32) - 1)
val = float(dtypes.int32.max - 1)
t1 = Tensor([val], dtype=dtypes.float32).cast(dtypes.int32)
t2 = Tensor(val, dtype=dtypes.float32).cast(dtypes.int32)
np.testing.assert_equal(t1.item(), t2.item())

8
test/backend/test_ops.py
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@@ -479,9 +479,9 @@ class TestOps(unittest.TestCase):
helper_test_op(None, torch.maximum, Tensor.maximum, vals=[[1., 0., 3., -4.], 3.])
helper_test_op(None, torch.maximum, Tensor.maximum, vals=[[1., 0., 3., -4.], [-1., -2., 3., 0.]])
helper_test_op(None, torch.maximum, Tensor.maximum,
vals=[[-1234, 0, 1234, dtypes.max(dtypes.int), dtypes.min(dtypes.int)], dtypes.max(dtypes.int)], forward_only=True)
vals=[[-1234, 0, 1234, dtypes.int.max, dtypes.int.min], dtypes.int.max], forward_only=True)
helper_test_op(None, torch.maximum, Tensor.maximum,
vals=[[-1234, 0, 1234, dtypes.max(dtypes.int), dtypes.min(dtypes.int)], dtypes.min(dtypes.int)], forward_only=True)
vals=[[-1234, 0, 1234, dtypes.int.max, dtypes.int.min], dtypes.int.min], forward_only=True)
helper_test_op(None, torch.maximum, Tensor.maximum, vals=[[True, False, False], True], forward_only=True)
helper_test_op(None, torch.maximum, Tensor.maximum, vals=[[True, False, False], [True, True, False]], forward_only=True)
@@ -496,9 +496,9 @@ class TestOps(unittest.TestCase):
helper_test_op(None, torch.minimum, Tensor.minimum, vals=[[1., 0., 3., -4.], 3.])
helper_test_op(None, torch.minimum, Tensor.minimum, vals=[[1., 0., 3., -4.], [-1., -2., 3., 0.]])
helper_test_op(None, torch.minimum, Tensor.minimum,
vals=[[-1234, 0, 1234, dtypes.max(dtypes.int), dtypes.min(dtypes.int)], dtypes.max(dtypes.int)], forward_only=True)
vals=[[-1234, 0, 1234, dtypes.int.max, dtypes.int.min], dtypes.int.max], forward_only=True)
helper_test_op(None, torch.minimum, Tensor.minimum,
vals=[[-1234, 0, 1234, dtypes.max(dtypes.int), dtypes.min(dtypes.int)], dtypes.min(dtypes.int)], forward_only=True)
vals=[[-1234, 0, 1234, dtypes.int.max, dtypes.int.min], dtypes.int.min], forward_only=True)
helper_test_op(None, torch.minimum, Tensor.minimum, vals=[[True, False, False], True], forward_only=True)
helper_test_op(None, torch.minimum, Tensor.minimum, vals=[[True, False, False], [True, True, False]], forward_only=True)

4
test/backend/test_quantize_onnx.py
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@@ -204,13 +204,13 @@ class TestQuantizeOnnx(unittest.TestCase):
W = Tensor(m2:=(np.random.uniform(0, 255, size=(N,N)).astype(wi))).realize()
tg_dtype = dtypes.int8 if xi == np.int8 else dtypes.uint8
out = (X.int().matmul(W.int())//1000)
if clip: out = out.clip(dtypes.min(tg_dtype),dtypes.max(tg_dtype))
if clip: out = out.clip(tg_dtype.min, tg_dtype.max)
out = out.cast(tg_dtype)
opts = [Opt(op=OptOps.UPCAST, axis=1, arg=128), Opt(op=OptOps.UNROLL, axis=0, arg=4)] if opts is None else opts
sexec(out, opts, replace_src, run_count=1)
tout = out.numpy()
mout = ((m1.astype(np.int32) @ m2.astype(np.int32)) // 1000)
if clip: mout = mout.clip(dtypes.min(tg_dtype),dtypes.max(tg_dtype))
if clip: mout = mout.clip(tg_dtype.min, tg_dtype.max)
mout = mout.astype(xi)
print(tout)
print(mout)

2
test/backend/test_renderer_failures.py
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@@ -62,7 +62,7 @@ class TestRendererFailures(unittest.TestCase):
class TestCStyleFailures(unittest.TestCase):
def test_inline_const_alu(self):
# CPU doesn't use the max function
ret = _setup_and_test_alu(Ops.MAX, 1, UOp.const(dtypes.int, dtypes.min(dtypes.int)+1))
ret = _setup_and_test_alu(Ops.MAX, 1, UOp.const(dtypes.int, dtypes.int.min+1))
self.assertEqual(ret[0], 1)
def _test_src_strip_paren(self, op: Ops, should_strip_paren:bool=True):

12
test/null/test_dtype_spec.py
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@@ -75,20 +75,20 @@ class TestHelpers(unittest.TestCase):
def test_dtype_range(self):
for dt in core_dtypes:
if dtypes.is_float(dt):
np.testing.assert_equal(dtypes.min(dt), -math.inf)
np.testing.assert_equal(dtypes.max(dt), math.inf)
np.testing.assert_equal(dt.min, -math.inf)
np.testing.assert_equal(dt.max, math.inf)
np.testing.assert_equal(dt.min, -math.inf)
np.testing.assert_equal(dt.max, math.inf)
elif dtypes.is_int(dt):
info = np.iinfo(_to_np_dtype(dt))
np.testing.assert_equal(dtypes.min(dt), info.min)
np.testing.assert_equal(dtypes.max(dt), info.max)
np.testing.assert_equal(dt.min, info.min)
np.testing.assert_equal(dt.max, info.max)
np.testing.assert_equal(dt.min, info.min)
np.testing.assert_equal(dt.max, info.max)
else:
assert dt == dtypes.bool, dt
np.testing.assert_equal(dtypes.min(dt), False)
np.testing.assert_equal(dtypes.max(dt), True)
np.testing.assert_equal(dt.min, False)
np.testing.assert_equal(dt.max, True)
np.testing.assert_equal(dt.min, False)
np.testing.assert_equal(dt.max, True)

8
test/null/test_uop_vmin_vmax.py
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@@ -64,8 +64,8 @@ class TestVminVmaxProperties(unittest.TestCase):
# negative mask: x & -1 could be anything since -1 has all bits set
uop = x & -1
self.assertEqual(uop.vmin, dtypes.min(dtypes.int32))
self.assertEqual(uop.vmax, dtypes.max(dtypes.int32))
self.assertEqual(uop.vmin, dtypes.int32.min)
self.assertEqual(uop.vmax, dtypes.int32.max)
def test_vmin_vmax_multiplication_with_variable(self):
# vmin and vmax for multiplication with a variable
@@ -136,8 +136,8 @@ class TestVminVmaxProperties(unittest.TestCase):
self.assertEqual(x_bool.vmin, False)
self.assertEqual(x_bool.vmax, True)
x_uint = x.cast(dtypes.uint)
self.assertEqual(x_uint.vmin, dtypes.min(dtypes.uint))
self.assertEqual(x_uint.vmax, dtypes.max(dtypes.uint))
self.assertEqual(x_uint.vmin, dtypes.uint.min)
self.assertEqual(x_uint.vmax, dtypes.uint.max)
def test_vmin_vmax_invalid(self):
i = UOp.invalid()