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https://github.com/kubernetes/kubernetes.git
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00e1a2e9a2
Replace the TensorFlow-based wide-deep workload with the PyTorch implementation. This change: - Adds pytorchWideDeepWorkload using the new pytorch-wide-deep image (1.0.0) - Removes tfWideDeepWorkload and tf-wide-deep image references - Enables arm64 support (PyTorch image is multi-arch) - Uses the same log parsing (time -p output format) Signed-off-by: Davanum Srinivas <davanum@gmail.com>
53 lines
1.9 KiB
Go
53 lines
1.9 KiB
Go
/*
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Copyright 2018 The Kubernetes Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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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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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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*/
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package workloads
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import (
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"time"
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v1 "k8s.io/api/core/v1"
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kubeletconfig "k8s.io/kubernetes/pkg/kubelet/apis/config"
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)
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// NodePerfWorkload provides the necessary information to run a workload for
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// node performance testing.
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type NodePerfWorkload interface {
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// Name of the workload.
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Name() string
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// PodSpec used to run this workload.
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PodSpec() v1.PodSpec
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// Timeout provides the expected time to completion
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// for this workload.
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Timeout() time.Duration
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// KubeletConfig specifies the Kubelet configuration
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// required for this workload.
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KubeletConfig(old *kubeletconfig.KubeletConfiguration) (new *kubeletconfig.KubeletConfiguration, err error)
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// PreTestExec is used for defining logic that needs
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// to be run before restarting the Kubelet with the new Kubelet
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// configuration required for the workload.
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PreTestExec() error
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// PostTestExec is used for defining logic that needs
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// to be run after the workload has completed.
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PostTestExec() error
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// ExtractPerformanceFromLogs is used get the performance of the workload
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// from pod logs. Currently, we support only performance reported in
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// time.Duration format.
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ExtractPerformanceFromLogs(logs string) (perf time.Duration, err error)
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}
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// NodePerfWorkloads is the collection of all node performance testing workloads.
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var NodePerfWorkloads = []NodePerfWorkload{npbISWorkload{}, npbEPWorkload{}, pytorchWideDeepWorkload{}}
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