returnn.frontend.stepwise_scheduler
¶
Stepwise scheduler, e.g. for learning rate or other hyperparameters.
All these modules will accept any args/kwargs but leave them unused,
and instead uses get_run_ctx()
to get the current train step from the current run context.
- class returnn.frontend.stepwise_scheduler.PiecewiseLinearStepwiseScheduler(points: Dict[int | float, float | Tensor])[source]¶
Piecewise linear scheduler based on the current global train step.
Example:
scheduler = PiecewiseLinearStepwiseScheduler( {0: 1.0, 10000: 0.1, 20000: 0.01} )
This will start with 1.0, and then linearly decay to 0.1 at step 10000, and then to 0.01 at step 20000.
- Parameters:
points – dict of key -> value pairs.