Dear Altruists,
I want to run my pytorch model in android with gpu.
I have cloned the example app from this github repository 2 suggested by this blog 5 from PyTorch.
When I try to build the app I get the following error.
A problem occurred configuring project ':pytorch_android'.
> Could not create task ':pytorch_android:processDebugManifest'.
   > 'org.gradle.api.file.RegularFileProperty org.gradle.api.file.ProjectLayout.fileProperty(org.gradle.api.provider.Provider)'

I have made following changes.

Put VULKAN traced the model file mnet.pt in ./android/test_app/app/src/main/assets/ folder
Updated the gradle version from 3.3.2 to 3.5.1 in line 28 of ./android/build.gradle file
Updated the ./android/settings.gradle file keeping only these liines required to run the test_app project

include ':test_app'
project(':test_app').projectDir = file('test_app/app')


Set the USE_VULKAN_DEVICE flag to true adding the following line after line 66 of ./android/test_app/app/build.gradle file
buildConfigField("boolean", "USE_VULKAN_DEVICE", 'true')


With step 1, 2 and 3 the example app builds and runs successfully on my mobile device Samsung A71 but I get BuildConfig.USE_VULKAN_DEVICE = false  in ./android/test_app/app/src/main/java/org/pytorch/testapp/MainActivity.java file.
When I set the flag USE_VULKAN_DEVICE true with step 4, I get the following error.
2021-05-23 17:01:12.001 16511-16896/? E/AndroidRuntime: FATAL EXCEPTION: pytorch-mnet_bg
    Process: org.pytorch.testapp.mnet, PID: 16511
    java.lang.RuntimeException: The following operation failed in the TorchScript interpreter.
    Traceback of TorchScript, serialized code (most recent call last):
      File "code/__torch__/torchvision/models/mobilenetv2.py", line 11, in forward
      def forward(self: __torch__.torchvision.models.mobilenetv2.MobileNetV2,
        x: Tensor) -> Tensor:
        return (self)._forward_impl(x, )
                ~~~~~~~~~~~~~~~~~~~ <--- HERE
      def _forward_impl(self: __torch__.torchvision.models.mobilenetv2.MobileNetV2,
        x: Tensor) -> Tensor:
      File "code/__torch__/torchvision/models/mobilenetv2.py", line 15, in _forward_impl
        x: Tensor) -> Tensor:
        _0 = __torch__.torch.nn.functional.adaptive_avg_pool2d
        x0 = (self.features).forward(x, )
              ~~~~~~~~~~~~~~~~~~~~~~ <--- HERE
        x1 = torch.reshape(_0(x0, [1, 1], ), [(torch.size(x0))[0], -1])
        return (self.classifier).forward(x1, )
      File "code/__torch__/torch/nn/modules/container/___torch_mangle_80.py", line 46, in forward
        _17 = getattr(self, "17")
        _18 = getattr(self, "18")
        input0 = (_0).forward(input, )
                  ~~~~~~~~~~~ <--- HERE
        input1 = (_1).forward(input0, )
        input2 = (_2).forward(input1, )
      File "code/__torch__/torchvision/models/mobilenetv2.py", line 32, in forward
        _2 = getattr(self, "1")
        _3 = getattr(self, "2")
        input0 = (_1).forward(input, )
                  ~~~~~~~~~~~ <--- HERE
        input1 = (_2).forward(input0, )
        return (_3).forward(input1, )
      File "code/__torch__/torch/nn/modules/conv.py", line 21, in forward
      def forward(self: __torch__.torch.nn.modules.conv.Conv2d,
        input: Tensor) -> Tensor:
        _0 = (self)._conv_forward(input, self.weight, self.bias, )
              ~~~~~~~~~~~~~~~~~~~ <--- HERE
        return _0
      def _conv_forward(self: __torch__.torch.nn.modules.conv.Conv2d,
      File "code/__torch__/torch/nn/modules/conv.py", line 27, in _conv_forward
        weight: Tensor,
        bias: Optional[Tensor]) -> Tensor:
        _1 = torch.conv2d(input, weight, bias, [2, 2], [1, 1], [1, 1], 1)
             ~~~~~~~~~~~~ <--- HERE
        return _1
    
    Traceback of TorchScript, original code (most recent call last):
      File "/home/tigerit/miniconda3/envs/torch-vulkan/lib/python3.8/site-packages/torchvision/models/mobilenetv2.py", line 198, in forward
        def forward(self, x: Tensor) -> Tensor:
            return self._forward_impl(x)
                   ~~~~~~~~~~~~~~~~~~ <--- HERE
      File "/home/tigerit/miniconda3/envs/torch-vulkan/lib/python3.8/site-packages/torch/nn/modules/container.py", line 119, in forward
        def forward(self, input):
            for module in self:
                input = module(input)
                        ~~~~~~ <--- HERE
            return input
      File "/home/tigerit/miniconda3/envs/torch-vulkan/lib/python3.8/site-packages/torch/nn/modules/container.py", line 119, in forward
        def forward(self, input):
            for module in self:
                input = module(input)
                        ~~~~~~ <--- HERE
            return input
      File "/home/tigerit/miniconda3/envs/torch-vulkan/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 399, in forward
        def forward(self, input: Tensor) -> Tensor:
            return self._conv_forward(input, self.weight, self.bias)
                   ~~~~~~~~~~~~~~~~~~ <--- HERE
      File "/home/tigerit/miniconda3/envs/torch-vulkan/lib/python3.8/site-packages/torch/nn/modules/conv.py", line 395, in _conv_forward
                                weight, bias, self.stride,
                                _pair(0), self.dilation, self.groups)
            return F.conv2d(input, weight, bias, self.stride,
                   ~~~~~~~~ <--- HERE
                            self.padding, self.dilation, self.groups)
    RuntimeError: expected scalar type Float but found UNKNOWN_SCALAR
    
        at org.pytorch.NativePeer.forward(Native Method)
        at org.pytorch.Module.forward(Module.java:49)
        at org.pytorch.testapp.MainActivity.doModuleForward(MainActivity.java:142)
2021-05-23 17:01:12.002 16511-16896/? E/AndroidRuntime:     at org.pytorch.testapp.MainActivity$1.run(MainActivity.java:44)
        at android.os.Handler.handleCallback(Handler.java:938)
        at android.os.Handler.dispatchMessage(Handler.java:99)
        at android.os.Looper.loop(Looper.java:246)
        at android.os.HandlerThread.run(HandlerThread.java:67)
2021-05-23 17:01:12.036 16511-16896/? I/Process: Sending signal. PID: 16511 SIG: 9