Hello,
I am trying to deploy my CNN inpainting model to Android mobile app, so I am following this tutorial.
https://pytorch.org/tutorials/recipes/quantization.html
model = PartialConvUNet()
backend = 'qnnpack'

model.qconfig = torch.quantization.get_default_qconfig(backend)
torch.backends.quantized.engine = backend
model_static_quantized = torch.quantization.prepare(model, inplace=False)
model_static_quantized = torch.quantization.convert(model_static_quantized, inplace=False)
print_size_of_model(model_static_quantized)

And I run this, I get this error.
Traceback (most recent call last):
  File "C:\PycharmProjects\MyCNN\mymodel.py", line 219, in <module>
    torch.backends.quantized.engine = 'qnnpack'
  File "C:\Anaconda3\envs\deeplearning\lib\site-packages\torch\backends\quantized\__init__.py", line 29, in __set__
    torch._C._set_qengine(_get_qengine_id(val))
RuntimeError: quantized engine QNNPACK is not supported

If I set
backend='fbgemm'
It works, but this is the backend for the x86 server, which will not be compatible to Android environment, correct?