flax.optim.GradientDescent

class flax.optim.GradientDescent(learning_rate=None)[source]

Gradient descent optimizer.

__init__(learning_rate=None)[source]

Constructor for the GradientDescent optimizer.

Parameters

learning_rate – the step size used to update the parameters.

Methods

__init__([learning_rate])

Constructor for the GradientDescent optimizer.

apply_gradient(hyper_params, params, state, ...)

Applies a gradient for a set of parameters.

apply_param_gradient(step, hyper_params, ...)

Apply a gradient for a single parameter.

create(target[, focus])

Creates a new optimizer for the given target.

init_param_state(param)

Initializes the state for a parameter.

init_state(params)

restore_state(opt_target, opt_state, state_dict)

Restore the optimizer target and state from the state dict.

state_dict(target, state)

update_hyper_params(**hyper_param_overrides)

Updates the hyper parameters with a set of overrides.