#
# Copyright 2018 Analytics Zoo Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from abc import ABC, abstractmethod
[docs]class Trigger(ABC):
[docs] @abstractmethod
def get_trigger(self):
pass
[docs] @staticmethod
def convert_trigger(trigger):
if trigger is None:
return None
if isinstance(trigger, str):
if trigger.lower() == "everyepoch":
return EveryEpoch().get_trigger()
else:
raise ValueError("Only 'EveryEpoch', orca triggers and bigdl triggers are "
"supported now")
elif isinstance(trigger, Trigger):
return trigger.get_trigger()
else:
return trigger
[docs]class EveryEpoch(Trigger):
"""
A trigger specifies a timespot or several timespots during training,
and a corresponding action will be taken when the timespot(s) is reached.
EveryEpoch is a trigger that triggers an action when each epoch finishs.
Could be used as trigger in setvalidation and setcheckpoint in Optimizer,
and also in TrainSummary.set_summary_trigger.
>>> everyEpoch = EveryEpoch()
"""
def __init__(self):
from bigdl.optim.optimizer import EveryEpoch
self.trigger = EveryEpoch()
[docs] def get_trigger(self):
return self.trigger
[docs]class SeveralIteration(Trigger):
"""
A trigger specifies a timespot or several timespots during training,
and a corresponding action will be taken when the timespot(s) is reached.
SeveralIteration is a trigger that triggers an action every "n"
iterations.
Could be used as trigger in setvalidation and setcheckpoint in Optimizer,
and also in TrainSummary.set_summary_trigger.
>>> serveralIteration = SeveralIteration(2)
"""
def __init__(self, interval):
from bigdl.optim.optimizer import SeveralIteration
self.trigger = SeveralIteration(interval)
[docs] def get_trigger(self):
return self.trigger