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Description
I would like to add support for the torch.heaviside operation in the Torch dialect of Torch-MLIR.
I tested with the torch.heaviside using fx.export_and_import and the reproduced error is
Minimal Reproduction
def run(f):
print(f"{f.__name__}")
print("-" * len(f.__name__))
f()
print()
@run
def test_heaviside():
class HeavisideModule(nn.Module):
def __init__(self):
super().__init__()
def forward(self,x):
input,values=x
return torch.heaviside(input,values)
exported=fx.export_and_import(HeavisideModule(),(torch.randn(1,2),torch.randn(1)),output_type='torch')
print(exported)
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