I am doing int8 quantization and I need to exchanged the mul operation of pytorch.

```
answer = a_tensor * 0.2 * b_tensor
```

I tried to replace the multiplication operations like the below with FloatFunctional’s.

```
self.ff = nn.quantized.FloatFunctional()
d = self.ff.mul_scalar(a_tensor, 0.2)
answer = self.ff.mul(d, b_tensor)
```

But, when calls the torch.jit.trace()

I got the exception below.

```
answer = self.ff.mul(d, b_tensor)
File "/root/.pyenv/versions/3.7.1/lib/python3.7/site-packages/torch/nn/quantized/modules/functional_modules.py", line 160, in mul
r = ops.quantized.mul(x, y, scale=self.scale, zero_point=self.zero_point)
RuntimeError: Mul operands should have same data type.
```

I printed out the dtype.

print("### d.dtype", a.dtype)

print("### b_tensor.dtype", b_tensor.dtype)

I got the below.

### d.dtype torch.quint8

### b_tensor.dtype torch.float32

Any good solution for this situation?