If the conv layer has a kernel shape of 1x1 and expects in_channels=1, you could reshape the scalar value into a tensor with the shape [batch_size, 1, 1, 1] and feed it directly to the conv layer.
If that’s not the case, you won’t be able to directly feed a scalar value to it and would need to either add/copy/subtract/etc. it to another input or use another layer.