'Update the parameters associated with this layer.
Update the bias.
Args:
step: Training step.'

def UpdateLayerParams(self, layer, step):

    layer.gradient.add_sums(layer.deriv, axis=1, mult=(1.0 / layer.batchsize))
    if layer.tied_to:
        layer.tied_to.gradient.add(layer.gradient)
        layer.gradient.assign(0)
        layer = layer.tied_to
    layer.num_grads_received += 1
    if (layer.num_grads_received == layer.num_shares):
        layer.Update('bias', step, no_reg=True)
