Torch compile don't work correctly with divide by scalar #157959
Description
🐛 Describe the bug
When you divide by scalar you get diffrent results in torch.compile. One solution is to put the scalar into tensor with nn.Parameters to solve the issue.
import torch
from torch import nn
class Foo(nn.Module):
def __init__(
self,
use_parameter: bool
) -> None:
super().__init__()
self.b = 101
if use_parameter:
self.b = nn.Parameter(torch.Tensor([self.b]), requires_grad=False)
def forward(self, x: torch.Tensor) -> torch.Tensor:
# return x + self.b
# return x - self.b
return x / self.b
# return x * self.b
torch.manual_seed(42)
x = torch.rand((5, 5))
expected = Foo(False)(x)
models = [
Foo(False),
Foo(True),
torch.compile(Foo(False), fullgraph=True),
torch.compile(Foo(True), fullgraph=True),
]
for m in models:
print((m(x) - expected).sum())Results i got are:
tensor(0.)
tensor(0.)
tensor(-2.6776e-09)
tensor(0.)
Versions
gpytorch==1.14
pytorch-lightning==2.5.2
torch==2.7.1
torchinfo==1.8.0
torchmetrics==1.3.1
cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @chenyang78 @kadeng @muchulee8 @amjames @chauhang @aakhundov