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bad conv in rangeify (#12373)

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* bad conv with broken rangeify

* no maxpool needed

* add empty_like

* typo

* no self

* issue remains for test
This commit is contained in:
George Hotz
2025-10-01 08:56:22 +08:00
committed by GitHub
parent 080b26e7d7
commit 9ef319f349
2 changed files with 14 additions and 0 deletions
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7
test/test_rangeify.py
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@@ -38,6 +38,13 @@ class TestRangeifyOpt(unittest.TestCase):
Xsel, Ysel = X[sel], Y[sel]
Tensor.realize(Xsel, Ysel)
def test_resnetconv(self):
conv1 = nn.Conv2d(3, 8, kernel_size=7, stride=2, bias=False, padding=3)
conv1.weight.replace(conv1.weight.empty_like())
x = Tensor.empty(1, 3, 56, 56)
x = conv1(x).pad([1,1,1,1])+1
x.realize()
@unittest.skipIf(RANGEIFY<1, "tests only for RANGEIFY")
class TestRangeify(unittest.TestCase):
def test_groupnorm(self):

7
tinygrad/tensor.py
View File

@@ -456,6 +456,13 @@ class Tensor(MathTrait):
device = tuple(Device.canonicalize(d) for d in device) if isinstance(device, tuple) else Device.canonicalize(device)
return Tensor(UOp.new_buffer(device, size, dtype), device, dtype, **kwargs).shrink(((0,prod(shape)),)).reshape(shape)
def empty_like(self, **kwargs) -> Tensor:
"""
Creates an empty tensor with the same shape as `self`.
If `dtype` is not specified, the dtype of `self` is used.
"""
return Tensor.empty(self.shape, dtype=kwargs.pop("dtype", self.dtype), device=kwargs.pop("device", self.device), **kwargs)
@staticmethod
def from_blob(ptr:int, shape:tuple[int, ...], **kwargs) -> Tensor:
"""