Question about quantization of batch normalization

Hello, Onnx runtime development team.
Let us ask the question about quantization of batch normalization.
We use onnx runtime 1.9.0, static quantization.

If we use "Network A", Batch Normalization Layer was fused to Convolution layer before quantization.
And, we could quantize fused convolution layer.
[Network A]
Convolution - Batch Normalization - Relu

But if we use "Network B", Batch Normalization Layer was not fused to Convolution layer before quantization.
As a result of quantization, the parameters of batch normalization was not qyuantized.
(We confirmed FP32 parameters of Batch Normalization after quantization.)
[Network B]
Convolution - Relu - Batch Normalization

Do you have any TIPS to quantize Batch Normalization layer?
Or, do you have plan to support quantization of Batch Normalization Layer?

Thank you for your support.