def METHOD_NAME(self):
    fmodel = QuantModel().eval()
    fmodel = torch.ao.quantization.fuse_modules(fmodel, [
        ["core.layer1", "core.relu1"],
        ["core.layer2", "core.relu2"],
    ])
    fmodel.qconfig = torch.ao.quantization.get_default_qconfig("qnnpack")
    prepped = torch.ao.quantization.prepare(fmodel)
    prepped(torch.randn(2, 16))
    qmodel = torch.ao.quantization.convert(prepped)
    return qmodel