Once learning is done, the weights should be copied back into normal tensors.
Once learning is done, the weights should be copied back into normal tensors.
The weights
The initial step size.
The initial step size. Not too important because line search is performed.
Some optimizers swap out weights with special purpose tensors for e.
Some optimizers swap out weights with special purpose tensors for e.g. efficient scoring while learning.
The weights
Whether the optimizer has converged yet.
Whether the optimizer has converged yet.
Reset the optimizers internal state (such as Hessian approximation, etc.
Reset the optimizers internal state (such as Hessian approximation, etc.)
Updates the weights according to the gradient.
Updates the weights according to the gradient.
The weights
The gradient
The value
A conjugate gradient optimizer. Should not be used unless you know you want it.