clipping the reward for adam optimizer in keras

I would like to clip the reward in keras. I saw it is possible to clip the norm and clip the value is sgd as follows:

sgd = optimizers.SGD(lr=0.01, clipnorm=1.)
sgd = optimizers.SGD(lr=0.01, clipvalue=0.5)


What are clipping the norm and clipping the value?

Also, How it is possible to implement the clipping the reward for Adam? Would you please let me know how I can do this?

Gradient clipping takes two main forms in Keras: gradient norm scaling (clipnorm) and gradient value clipping (clipvalue).

Gradient norm scaling involves changing the derivatives of the loss function to have a given vector norm when the L2 vector norm (sum of the squared values) of the gradient vector exceeds a threshold value. For example, we could specify a norm of 1.0, meaning that if the vector norm for a gradient exceeds 1.0, then the values in the vector will be rescaled so that the norm of the vector equals 1.0.

opt_adam = optimizers.adam(clipnorm=1.)