Define a number of learnable parameters in Chainer
I read a little and found my answer.
If you need to define a number of parameters in chainer that need to be learned, you should use chainer.links.Scale() function.
for example chainer.links.Scale(axis=1,W_shape=(8,8))
W are the same parameters that are learnable in the network. If the feature map is x, W is multiplied by x and its updated in backpropagation.
I want to define a number of learnable parameters in my model that are multiplied by the feature map in feedforward  and updated when backpropagation.
How can i implement this in the chainer framework?