def get_config(self):
serialized_optimizer = optimizers.serialize(self._optimizer)
serialized_loss_scale = keras_loss_scale_module.serialize(self._loss_scale)
return {
'optimizer': serialized_optimizer,
'loss_scale': serialized_loss_scale,
}
def get_config(self):
config = {'name': self.name}
if not self._using_default_loss_scale:
# We only include the loss scale if the default loss scale is not used.
# This allows us to change the loss scale config format without breaking
# users who use the default loss scale.
config['loss_scale'] = keras_loss_scale_module.serialize(
self.loss_scale)
return config
def test_serialization(self):
loss_scale = loss_scale_module.DynamicLossScale(
initial_loss_scale=1, increment_period=2, multiplier=3)
config = loss_scale_module.serialize(loss_scale)
loss_scale = loss_scale_module.deserialize(config)
self.evaluate(variables.global_variables_initializer())
self.assertEqual(self.evaluate(loss_scale()), 1)
self.assertEqual(loss_scale.increment_period, 2)
self.assertEqual(loss_scale.multiplier, 3)
def test_serialization(self):
loss_scale = loss_scale_module.DynamicLossScale(initial_loss_scale=1,
increment_period=2,
multiplier=3)
config = loss_scale_module.serialize(loss_scale)
loss_scale = loss_scale_module.deserialize(config)
self.evaluate(variables.global_variables_initializer())
self.assertEqual(self.evaluate(loss_scale()), 1)
self.assertEqual(loss_scale.increment_period, 2)
self.assertEqual(loss_scale.multiplier, 3)
def test_serialization(self):
loss_scale = loss_scale_module.get(123)
config = loss_scale_module.serialize(loss_scale)
loss_scale = loss_scale_module.deserialize(config)
self.assertEqual(self.evaluate(loss_scale()), 123.)
def test_serialization(self): loss_scale = loss_scale_module.get(123) config = loss_scale_module.serialize(loss_scale) loss_scale = loss_scale_module.deserialize(config) self.assertEqual(self.evaluate(loss_scale()), 123.)
