Updating Pytorch Mobile to 1.8.0 from 1.7.1 causes "Dimension Out of Range" error in the PixelShuffle layer


I have updated the PytorchMobile for my Android application from 1.7.1 to 1.8.0 but doing so caused an error in the inference phase. Somehow the tensor dimensions became not valid anymore for PixelShuffle layer. Here is the error:

    Process: com.example.pytorchtutorial, PID: 14078
    java.lang.RuntimeException: The following operation failed in the TorchScript interpreter.
    Traceback of TorchScript, serialized code (most recent call last):
      File "code/__torch__/CARN_SR/carn_x2/___torch_mangle_86.py", line 130, in forward
        _62 = getattr(self, "prepack_folding._jit_pass_packed_weight_32")
        _63 = ops.prepacked.conv2d_clamp_run(_61, _62)
        out8 = torch.pixel_shuffle(_63, 2)
               ~~~~~~~~~~~~~~~~~~~ <--- HERE
        _64 = getattr(self, "prepack_folding._jit_pass_packed_weight_33")
        out9 = ops.prepacked.conv2d_clamp_run(out8, _64)
    Traceback of TorchScript, original code (most recent call last):
      File "/usr/local/lib/python3.8/site-packages/torch/nn/modules/pixelshuffle.py", line 46, in forward
        def forward(self, input: Tensor) -> Tensor:
            return F.pixel_shuffle(input, self.upscale_factor)
                   ~~~~~~~~~~~~~~~ <--- HERE
    RuntimeError: Dimension out of range (expected to be in range of [-6, 5], but got 4294967290)
        at org.pytorch.NativePeer.forward(Native Method)
        at org.pytorch.Module.forward(Module.java:49)
        at com.example.pytorchtutorial.MainActivity.applySR(MainActivity.java:122)
        at com.example.pytorchtutorial.MainActivity$2.onClick(MainActivity.java:214)
        at android.view.View.performClick(View.java:7448)
        at android.view.View.performClickInternal(View.java:7425)
        at android.view.View.access$3600(View.java:810)
        at android.view.View$PerformClick.run(View.java:28305)
        at android.os.Handler.handleCallback(Handler.java:938)
        at android.os.Handler.dispatchMessage(Handler.java:99)
        at android.os.Looper.loop(Looper.java:223)
        at android.app.ActivityThread.main(ActivityThread.java:7656)
        at java.lang.reflect.Method.invoke(Native Method)
        at com.android.internal.os.RuntimeInit$MethodAndArgsCaller.run(RuntimeInit.java:592)
        at com.android.internal.os.ZygoteInit.main(ZygoteInit.java:947)

When I downgrade the Pytorch Mobile version to 1.7.1 the error disappears. I think the problem is caused in PixelShuffle layer because when I use another model for inference, the error is thrown in that layer as well. For example:

    Traceback of TorchScript, serialized code (most recent call last):
      File "code/__torch__/Models/ESPCN/___torch_mangle_163.py", line 29, in forward
        _10 = (_4).forward(_8, )
        _11 = (_3).forward()
        _12 = (_0).forward((_1).forward((_2).forward(_10, ), ), )
                            ~~~~~~~~~~~ <--- HERE
        _13 = torch.contiguous(_12, memory_format=0)
        return _13
      File "code/__torch__/torch/nn/modules/pixelshuffle/___torch_mangle_160.py", line 8, in forward
      def forward(self: __torch__.torch.nn.modules.pixelshuffle.___torch_mangle_160.PixelShuffle,
        argument_1: Tensor) -> Tensor:
        return torch.pixel_shuffle(argument_1, 2)
               ~~~~~~~~~~~~~~~~~~~ <--- HERE

I would appreciate any help with this. Thanks

EDIT: This issue is now on Github

I’m a bit confused about the error message, as F.pixel_shuffle doesn’t expect a dimension argument, so it might be crashing internally?
Could you create an issue on GitHub so that we could track this issue?

The number looks a lot like -6 mod 2**32, so it might be signedness issue.

Maybe the change to feeding negative numbers to permute in

didn’t go well.
To make things specific, -something.size() seems very dubious in C++:

@jbschlosser , what do you think?

Best regards


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Sure, I opened an issue using the same content here. Thanks

Thank you for opening the issue. It’s generally a good idea to cross link the forum and the issue.

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I edited the first message to include the link to the Github issue. Thanks for the heads up :slight_smile:

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So I’m happy to report that in 1.8.1 this is fixed thanks to your report.
Thank you!

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That is good news! Thank you for the quick fix :slight_smile: