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tf.contrib.constrained_optimization.ConstrainedOptimizer

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Base class representing a constrained optimizer.

A ConstrainedOptimizer wraps a tf.compat.v1.train.Optimizer (or more than one), and applies it to a ConstrainedMinimizationProblem. Unlike a tf.compat.v1.train.Optimizer, which takes a tensor to minimize as a parameter to its minimize() method, a constrained optimizer instead takes a ConstrainedMinimizationProblem.

optimizer tf.compat.v1.train.Optimizer, used to optimize the ConstraintedMinimizationProblem.

optimizer Returns the tf.compat.v1.train.Optimizer used for optimization.

Methods

minimize

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Returns an Operation for minimizing the constrained problem.

This method combines the functionality of minimize_unconstrained and minimize_constrained. If global_step < unconstrained_steps, it will perform an unconstrained update, and if global_step >= unconstrained_steps, it will perform a constrained update.

The reason for this functionality is that it may be best to initialize the constrained optimizer with an approximate optimum of the unconstrained problem.

Args
minimization_problem ConstrainedMinimizationProblem, the problem to optimize.
unconstrained_steps int, number of steps for which we should perform unconstrained updates, before transitioning to constrained updates.
global_step as in tf.compat.v1.train.Optimizer's minimize method.
var_list as in tf.compat.v1.train.Optimizer's minimize method.
gate_gradients as in tf.compat.v1.train.Optimizer's minimize method.
aggregation_method as in tf.compat.v1.train.Optimizer's minimize method.
colocate_gradients_with_ops as in tf.compat.v1.train.Optimizer's minimize method.
name as in tf.compat.v1.train.Optimizer's minimize method.
grad_loss as in tf.compat.v1.train.Optimizer's minimize method.

Returns
Operation, the train_op.

Raises
ValueError If unconstrained_steps is provided, but global_step is not.

minimize_constrained

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Returns an Operation for minimizing the constrained problem.

Unlike minimize_unconstrained, this function attempts to find a solution that minimizes the objective portion of the minimization problem while satisfying the constraints portion.

Args
minimization_problem ConstrainedMinimizationProblem, the problem to optimize.
global_step as in tf.compat.v1.train.Optimizer's minimize method.
var_list as in tf.compat.v1.train.Optimizer's minimize method.
gate_gradients as in tf.compat.v1.train.Optimizer's minimize method.
aggregation_method as in tf.compat.v1.train.Optimizer's minimize method.
colocate_gradients_with_ops as in tf.compat.v1.train.Optimizer's minimize method.
name as in tf.compat.v1.train.Optimizer's minimize method.
grad_loss as in tf.compat.v1.train.Optimizer's minimize method.

Returns
Operation, the train_op.

minimize_unconstrained

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Returns an Operation for minimizing the unconstrained problem.

Unlike minimize_constrained, this function ignores the constraints (and proxy_constraints) portion of the minimization problem entirely, and only minimizes objective.

Args
minimization_problem ConstrainedMinimizationProblem, the problem to optimize.
global_step as in tf.compat.v1.train.Optimizer's minimize method.
var_list as in tf.compat.v1.train.Optimizer's minimize method.
gate_gradients as in tf.compat.v1.train.Optimizer's minimize method.
aggregation_method as in tf.compat.v1.train.Optimizer's minimize method.
colocate_gradients_with_ops as in tf.compat.v1.train.Optimizer's minimize method.
name as in tf.compat.v1.train.Optimizer's minimize method.
grad_loss as in tf.compat.v1.train.Optimizer's minimize method.

Returns
Operation, the train_op.