Module: tfp.optimizer  |  TensorFlow Probability (original) (raw)

TensorFlow Probability Optimizer python package.

Modules

convergence_criteria module: TensorFlow Probability convergence criteria for optimizations.

linesearch module: Line-search optimizers package.

Classes

class StochasticGradientLangevinDynamics: An optimizer module for stochastic gradient Langevin dynamics.

class VariationalSGD: An optimizer module for constant stochastic gradient descent.

Functions

bfgs_minimize(...): Applies the BFGS algorithm to minimize a differentiable function.

converged_all(...): Condition to stop when all batch members have converged or failed.

converged_any(...): Condition to stop when any batch member converges, or all have failed.

differential_evolution_minimize(...): Applies the Differential evolution algorithm to minimize a function.

differential_evolution_one_step(...): Performs one step of the differential evolution algorithm.

lbfgs_minimize(...): Applies the L-BFGS algorithm to minimize a differentiable function.

nelder_mead_minimize(...): Minimum of the objective function using the Nelder Mead simplex algorithm.

nelder_mead_one_step(...): A single iteration of the Nelder Mead algorithm.

proximal_hessian_sparse_minimize(...): Minimize using Hessian-informed proximal gradient descent.

proximal_hessian_sparse_one_step(...): One step of (the outer loop of) the minimization algorithm.