35 lines
1.1 KiB
Python
35 lines
1.1 KiB
Python
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# -*- coding: utf-8 -*-
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"""Training schedulers.
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This module contains classes implementing schedulers which control the
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evolution of learning rule hyperparameters (such as learning rate) over a
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training run.
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"""
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import numpy as np
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class ConstantLearningRateScheduler(object):
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"""Example of scheduler interface which sets a constant learning rate."""
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def __init__(self, learning_rate):
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"""Construct a new constant learning rate scheduler object.
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Args:
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learning_rate: Learning rate to use in learning rule.
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"""
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self.learning_rate = learning_rate
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def update_learning_rule(self, learning_rule, epoch_number):
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"""Update the hyperparameters of the learning rule.
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Run at the beginning of each epoch.
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Args:
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learning_rule: Learning rule object being used in training run,
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any scheduled hyperparameters to be altered should be
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attributes of this object.
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epoch_number: Integer index of training epoch about to be run.
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"""
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learning_rule.learning_rate = self.learning_rate
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