# 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.
from sedna.datasources import BaseDataSource
from sedna.common.class_factory import ClassFactory, ClassType
from .base_unseen_sample_re_recognition import BaseSampleReRegonition
__all__ = ('SampleReRegonitionDefault', )
@ClassFactory.register(ClassType.UTD)
[docs]class SampleReRegonitionDefault(BaseSampleReRegonition):
# TODO: to be completed
'''
Divide labeled unseen samples into seen tasks and unseen tasks.
Parameters
----------
task_index: str or Dict
knowledge base index which includes indexes
of tasks, samples, models, etc.
'''
def __init__(self, task_index, **kwargs):
super(SampleReRegonitionDefault, self).__init__(task_index)
[docs] def __call__(self, samples: BaseDataSource):
'''
Parameters
----------
samples: training samples
Returns
-------
seen_task_samples: BaseDataSource
unseen_task_samples: BaseDataSource
'''
sample_num = int(len(samples.x) / 2)
seen_task_samples = BaseDataSource(data_type=samples.data_type)
seen_task_samples.x = samples.x[:sample_num]
seen_task_samples.y = samples.y[:sample_num]
unseen_task_samples = BaseDataSource(data_type=samples.data_type)
unseen_task_samples.x = samples.x[sample_num:]
unseen_task_samples.y = samples.y[sample_num:]
return seen_task_samples, unseen_task_samples