def test_reduce_lr_on_plateau_integration(self):
train_gen = some_data_generator(OptimizerCheckpointTest.batch_size)
valid_gen = some_data_generator(OptimizerCheckpointTest.batch_size)
reduce_lr = ReduceLROnPlateau(monitor='loss', patience=3)
checkpointer = LRSchedulerCheckpoint(reduce_lr,
self.checkpoint_filename,
period=1)
self.model.fit_generator(train_gen,
valid_gen,
epochs=OptimizerCheckpointTest.epochs,
steps_per_epoch=5,
callbacks=[checkpointer])
def test_any_scheduler_integration(self):
train_gen = some_data_generator(OptimizerCheckpointTest.batch_size)
valid_gen = some_data_generator(OptimizerCheckpointTest.batch_size)
lr_scheduler = ExponentialLR(gamma=0.01)
checkpointer = LRSchedulerCheckpoint(lr_scheduler,
self.checkpoint_filename,
period=1)
self.model.fit_generator(train_gen,
valid_gen,
epochs=OptimizerCheckpointTest.epochs,
steps_per_epoch=5,
callbacks=[checkpointer])
def test_reduce_lr_checkpoints(self):
reduce_lr = ReduceLROnPlateau(monitor='loss', patience=3)
checkpointer = LRSchedulerCheckpoint(reduce_lr,
self.checkpoint_filename,
period=1)
self._test_checkpointer(checkpointer, reduce_lr)
def test_any_scheduler_checkpoints(self):
lr_scheduler = ExponentialLR(gamma=0.01)
checkpointer = LRSchedulerCheckpoint(lr_scheduler,
self.checkpoint_filename,
period=1)
self._test_checkpointer(checkpointer, lr_scheduler)