# Copyright 2023 The KubeEdge 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.
'''
Mining tasks of inference unseen sample
base on unseen task attribute extractor
Parameters
----------
samples ： infer unseen sample,
see `sedna.datasources.BaseDataSource` for more detail.
Returns
-------
allocations : tasks that assigned to each sample
'''
from sedna.datasources import BaseDataSource
[docs]class BaseUnseenTaskAllocation:
# TODO: to be completed
"""
Task allocation for unseen data
Parameters
----------
task_extractor : Dict
used to match target tasks
"""
def __init__(self, task_extractor, **kwargs):
self.task_extractor = task_extractor
[docs] def __call__(self, samples: BaseDataSource):
'''
Parameters
----------
samples: samples to be allocated
Returns
-------
samples: BaseDataSource
grouped samples based on allocations
allocations: List
allocation decision for actual inference
'''
raise NotImplementedError