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Describe the bug
If a model contains the QNN ElementWiseSelect operation, equivalent to torch.where(), it converts successfully but the graph fails to finalize on device or in the emulator.
You can create an equivalent model in Pytorch with
class Where(nn.Module):
def __init__(self):
super(Where, self).__init__()
self.conv1 = nn.Conv2d(3, 3, kernel_size=3, padding=1)
def forward(self, x):
mask = x > 0.5
y = x - 1.0
x = torch.where(mask, x, y)
x = self.conv1(x)
return x
x = torch.rand(1, 3, 16, 16)
y = Where()(x)
Expected behavior
After conversion, the model should run on the emulator and device as expected.
Additional context
As a heads-up: The operation also fails to finalize when converting through the qnn-pytorch-converter or going creating the model "manually" in C++.
The text was updated successfully, but these errors were encountered:
Describe the bug
If a model contains the QNN
ElementWiseSelect
operation, equivalent totorch.where()
, it converts successfully but the graph fails to finalize on device or in the emulator.To Reproduce
Steps to reproduce the behavior:
Expected behavior
After conversion, the model should run on the emulator and device as expected.
Stack trace
Output from
qnn-net-run
:Host configuration:
Additional context
As a heads-up: The operation also fails to finalize when converting through the
qnn-pytorch-converter
or going creating the model "manually" in C++.The text was updated successfully, but these errors were encountered: