Could you explain your concern a bit?
Usually the bias is removed in conv layers before a batch norm layer, as the batch norm’s beta parameter (bias of nn.BatchNorm) will have the same effect and the bias of the conv layer might be canceled out by the mean subtraction.
From the batch norm paper:
Note that, since we normalize Wu+b, the bias b can be ignored since its effect will be canceled by the subsequent mean subtraction (the role of the bias is subsumed by β in Alg. 1).