scheduler.py

import tensorflow as tf

# class CustomScheduleC10(tf.keras.optimizers.schedules.LearningRateSchedule):
#     def __init__(self, initial_learning_rate):
#         self.initial_learning_rate = initial_learning_rate
#
#     def __call__(self, step):
#         if step > 25040: #31280:
#             lr = 0.001
#         elif step > 12520: #15640:
#             lr = 0.01
#         else:
#             lr = 0.1
#         return lr

class CustomScheduleC10(tf.keras.optimizers.schedules.LearningRateSchedule):
    def __init__(self, initial_learning_rate):
        self.initial_learning_rate = initial_learning_rate

    def __call__(self, step):
        if step > 31280:
            lr = 0.001
        if step > 15640:
            lr = 0.01
        else:
            lr = 0.1
        return lr

# class CustomScheduleC100(tf.keras.optimizers.schedules.LearningRateSchedule):
#     def __init__(self, initial_learning_rate):
#         self.initial_learning_rate = initial_learning_rate
#
#     def __call__(self, step):
#         if step > 37560: #46920:
#             lr = 0.001
#         elif step > 25040: #31280:
#             lr = 0.01
#         else:
#             lr = 0.1
#         return lr

class CustomScheduleC100(tf.keras.optimizers.schedules.LearningRateSchedule):
    def __init__(self, initial_learning_rate):
        self.initial_learning_rate = initial_learning_rate

    def __call__(self, step):
        if step > 46920:
            lr = 0.001
        elif step > 31280:
            lr = 0.01
        else:
            lr = 0.1
        return lr