Source code for sconce.schedules.step

from pprint import pformat as pf
from sconce.schedules.base import Schedule

import numpy as np


[docs]class Step(Schedule): """ A Schedule where the value starts at <initial_value> and changes <num_changes> times over the course of <num_steps> to a final value of <final_value>. Arguments: initial_value (float): the initial value of the hyperparameter. final_value (float): the final value of the hyperparameter. num_changes (int, optional): [1, <num_steps>-1] the number of times the hyperparameter's value will change. Note: The parameter <num_steps> is set during training based on the size of the batch_size and number of samples in the training_feed, and the batch_multiplier value. """ def __init__(self, initial_value, final_value, num_changes=1): self.initial_value = initial_value self.final_value = final_value self.num_changes = num_changes def __repr__(self): return (f'{self.__class__.__name__}(initial_value={pf(self.initial_value)}, ' f'final_value={pf(self.final_value)}, num_changes={pf(self.num_changes)})')
[docs] def set_num_steps(self, num_steps): self.num_steps = num_steps num_regions = self.num_changes + 1 self.region_values = np.linspace(self.initial_value, self.final_value, num_regions) self.indices = [int(i) for i in np.linspace(0, num_regions - 1e-12, num_steps)]
def _get_value(self, step, current_state): return self.region_values[self.indices[step - 1]]