dffc15184d
It runs now, just need to debug it to reach performance parity with SRGAN. Sweet.
66 lines
2.4 KiB
Python
66 lines
2.4 KiB
Python
import math
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from matplotlib import pyplot as plt
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# Base class for weight schedulers. Holds weight at a fixed initial value.
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class WeightScheduler:
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def __init__(self, initial_weight):
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self.initial_weight = initial_weight
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def get_weight_for_step(self, step):
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return self.initial_weight
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class LinearDecayWeightScheduler(WeightScheduler):
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def __init__(self, initial_weight, steps_to_decay, lower_bound, initial_step=0):
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super(LinearDecayWeightScheduler, self).__init__(initial_weight)
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self.steps_to_decay = steps_to_decay
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self.lower_bound = lower_bound
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self.initial_step = initial_step
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self.decrease_per_step = (initial_weight - lower_bound) / self.steps_to_decay
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def get_weight_for_step(self, step):
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step = step - self.initial_step
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if step < 0:
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return self.initial_weight
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return max(self.lower_bound, self.initial_weight - step * self.decrease_per_step)
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class SinusoidalWeightScheduler(WeightScheduler):
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def __init__(self, upper_weight, lower_weight, period_steps, initial_step=0):
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super(SinusoidalWeightScheduler, self).__init__(upper_weight)
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self.center = (upper_weight + lower_weight) / 2
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self.amplitude = (upper_weight - lower_weight) / 2
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self.period = period_steps
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self.initial_step = initial_step
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def get_weight_for_step(self, step):
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step = step - self.initial_step
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if step < 0:
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return self.initial_weight
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# Use cosine because it starts at y=1 for x=0.
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return math.cos(step * math.pi * 2 / self.period) * self.amplitude + self.center
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def get_scheduler_for_opt(opt):
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if opt['type'] == 'fixed':
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return WeightScheduler(opt['weight'])
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elif opt['type'] == 'linear_decay':
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return LinearDecayWeightScheduler(opt['initial_weight'], opt['steps'], opt['lower_bound'], opt['start_step'])
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elif opt['type'] == 'sinusoidal':
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return SinusoidalWeightScheduler(opt['upper_weight'], opt['lower_weight'], opt['period'], opt['start_step'])
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else:
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raise NotImplementedError
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# Do some testing.
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if __name__ == "__main__":
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#sched = SinusoidalWeightScheduler(1, .1, 50, 10)
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sched = LinearDecayWeightScheduler(1, 150, .1, 20)
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x = []
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y = []
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for s in range(200):
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x.append(s)
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y.append(sched.get_weight_for_step(s))
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plt.plot(x, y)
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plt.show() |