# 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
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# Unless required by applicable law or agreed to in writing, software
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import numpy as np
from sedna.datasources import BaseDataSource
from sedna.common.class_factory import ClassFactory, ClassType
from .base_task_allocation import BaseTaskAllocation
# TODO: this class is just for demonstrate
@ClassFactory.register(ClassType.STP)
[docs]class TaskAllocationStream(BaseTaskAllocation):
"""
Corresponding to `TaskDefinitionByOrigin`
Parameters
----------
task_extractor : Dict
used to predict target tasks for each inference sample
origins: List[Metadata]
metadata is usually a class feature
label with a finite values.
"""
def __init__(self, task_extractor, **kwargs):
super(TaskAllocationStream, self).__init__(task_extractor)
[docs] def __call__(self, samples: BaseDataSource):
allocations = [np.random.randint(0, 1)
for _ in range(samples.num_examples())]
return samples, allocations