optimizer

openchem_optimizer

class optimizer.openchem_optimizer.OpenChemOptimizer(params, model_params)

Bases: object

get_lr()

Return the current learning rate.

load_state_dict(state_dict)

Load an optimizer state dict. In general we should prefer the configuration of the existing optimizer instance (e.g., learning rate) over that found in the state_dict. This allows us to resume training from a checkpoint using a new set of optimizer args.

property optimizer

property param_groups

set_lr(lr)

Set the learning rate.

state_dict()

Return the optimizer’s state dict.

step(closure=None)

Performs a single optimization step.

zero_grad()

Clears the gradients of all optimized parameters.

openchem_lr_scheduler

class optimizer.openchem_lr_scheduler.OpenChemLRScheduler(params, optimizer)

Bases: object

property by_iteration

If true, make step every iteration, else every epoch (default)

property scheduler

step()

Performs a single scheduler step.