Thank you very much for your support, @supriyar .
I want to quantize entire model, so I used QuantWrapper().
However I couldn’t quantize well and got bellow error.
RuntimeError: Could not run 'aten::add.Tensor' with arguments from the 'QuantizedCPU' backend. 'aten::add.Tensor' is only available for these backends: [CPU, CUDA, MkldnnCPU, SparseCPU, SparseCUDA, Meta, BackendSelect, Named, AutogradOther, AutogradCPU, AutogradCUDA, AutogradXLA, AutogradPrivateUse1, AutogradPrivateUse2, AutogradPrivateUse3, Tracer, Autocast, Batched, VmapMode].

And I tried to insert quant/dequant stub to model by myself.
class QuantizedMobileNetV2(nn.Module):
    def __init__(self, model_fp32):
        super(QuantizedMobileNetV2, self).__init__()
        self.quant = torch.quantization.QuantStub()
        self.dequant = torch.quantization.DeQuantStub()
        self.model_fp32 = model_fp32

    def forward(self, x):
        x = self.quant(x)
        x = self.model_fp32(x)
        x = self.dequant(x)
        return x

But I got same error when I used QuantWrapper().