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TensorFlow Serving on XPU Chart (#359)
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Signed-off-by: tylertitsworth <[email protected]>
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Tyler Titsworth authored Sep 18, 2024
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23 changes: 23 additions & 0 deletions workflows/charts/tensorflow-serving/.helmignore
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# Patterns to ignore when building packages.
# This supports shell glob matching, relative path matching, and
# negation (prefixed with !). Only one pattern per line.
.DS_Store
# Common VCS dirs
.git/
.gitignore
.bzr/
.bzrignore
.hg/
.hgignore
.svn/
# Common backup files
*.swp
*.bak
*.tmp
*.orig
*~
# Various IDEs
.project
.idea/
*.tmproj
.vscode/
42 changes: 42 additions & 0 deletions workflows/charts/tensorflow-serving/Chart.yaml
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# Copyright (c) 2024 Intel Corporation
#
# 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.

apiVersion: v2
name: tensorflow-serving-on-intel
description: TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments. TensorFlow Serving makes it easy to deploy new algorithms and experiments, while keeping the same server architecture and APIs. TensorFlow Serving provides out-of-the-box integration with TensorFlow models, but can be easily extended to serve other types of models and data.

# A chart can be either an 'application' or a 'library' chart.
#
# Application charts are a collection of templates that can be packaged into versioned archives
# to be deployed.
#
# Library charts provide useful utilities or functions for the chart developer. They're included as
# a dependency of application charts to inject those utilities and functions into the rendering
# pipeline. Library charts do not define any templates and therefore cannot be deployed.
maintainers:
- name: tylertitsworth
email: [email protected]
url: https://github.com/tylertitsworth
type: application

# This is the chart version. This version number should be incremented each time you make changes
# to the chart and its templates, including the app version.
# Versions are expected to follow Semantic Versioning (https://semver.org/)
version: 0.1.0

# This is the version number of the application being deployed. This version number should be
# incremented each time you make changes to the application. Versions are not expected to
# follow Semantic Versioning. They should reflect the version the application is using.
# It is recommended to use it with quotes.
appVersion: "1.16.0"
31 changes: 31 additions & 0 deletions workflows/charts/tensorflow-serving/README.md
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# tensorflow-serving-on-intel

![Version: 0.1.0](https://img.shields.io/badge/Version-0.1.0-informational?style=flat-square) ![Type: application](https://img.shields.io/badge/Type-application-informational?style=flat-square) ![AppVersion: 1.16.0](https://img.shields.io/badge/AppVersion-1.16.0-informational?style=flat-square)

TensorFlow Serving is a flexible, high-performance serving system for machine learning models, designed for production environments. TensorFlow Serving makes it easy to deploy new algorithms and experiments, while keeping the same server architecture and APIs. TensorFlow Serving provides out-of-the-box integration with TensorFlow models, but can be easily extended to serve other types of models and data.

## Maintainers

| Name | Email | Url |
| ---- | ------ | --- |
| tylertitsworth | <[email protected]> | <https://github.com/tylertitsworth> |

## Values

| Key | Type | Default | Description |
|-----|------|---------|-------------|
| deploy.env | object | `{"configMapName":"intel-proxy-config","enabled":true}` | Add Environment mapping |
| deploy.image | string | `"intel/intel-extension-for-tensorflow:serving-gpu"` | Intel Extension for Tensorflow Serving image |
| deploy.modelName | string | `""` | Model Name |
| deploy.replicas | int | `1` | Number of pods |
| deploy.resources.limits | object | `{"cpu":"4000m","gpu.intel.com/i915":1,"memory":"1Gi"}` | Maximum resources per pod |
| deploy.resources.limits."gpu.intel.com/i915" | int | `1` | Intel GPU Device Configuration |
| deploy.resources.requests | object | `{"cpu":"1000m","memory":"512Mi"}` | Minimum resources per pod |
| deploy.storage.nfs | object | `{"enabled":false,"path":"nil","readOnly":true,"server":"nil"}` | Network File System (NFS) storage for models |
| fullnameOverride | string | `""` | Full qualified Domain Name |
| nameOverride | string | `""` | Name of the serving service |
| pvc.size | string | `"5Gi"` | Size of the storage |
| service.type | string | `"NodePort"` | Type of service |

----------------------------------------------
Autogenerated from chart metadata using [helm-docs v1.14.2](https://github.com/norwoodj/helm-docs/releases/v1.14.2)
19 changes: 19 additions & 0 deletions workflows/charts/tensorflow-serving/templates/NOTES.txt
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1. Get the application URL by running these commands:
{{- if contains "NodePort" .Values.service.type }}
export NODE_PORT=$(kubectl get --namespace {{ .Release.Namespace }} -o jsonpath="{.spec.ports[0].nodePort}" services {{ include "tensorflow-serving.fullname" . }})
export NODE_IP=$(kubectl get nodes --namespace {{ .Release.Namespace }} -o jsonpath="{.items[0].status.addresses[0].address}")
echo http://$NODE_IP:$NODE_PORT
{{- else if contains "LoadBalancer" .Values.service.type }}
NOTE: It may take a few minutes for the LoadBalancer IP to be available.
You can watch its status by running 'kubectl get --namespace {{ .Release.Namespace }} svc -w {{ include "tensorflow-serving.fullname" . }}'
export SERVICE_IP=$(kubectl get svc --namespace {{ .Release.Namespace }} {{ include "tensorflow-serving.fullname" . }} --template "{{"{{ range (index .status.loadBalancer.ingress 0) }}{{.}}{{ end }}"}}")
echo http://$SERVICE_IP:{{ .Values.service.port }}
{{- else if contains "ClusterIP" .Values.service.type }}
export POD_NAME=$(kubectl get pods --namespace {{ .Release.Namespace }} -l "app.kubernetes.io/name={{ include "tensorflow-serving.name" . }},app.kubernetes.io/instance={{ .Release.Name }}" -o jsonpath="{.items[0].metadata.name}")
export CONTAINER_PORT=$(kubectl get pod --namespace {{ .Release.Namespace }} $POD_NAME -o jsonpath="{.spec.containers[0].ports[0].containerPort}")
echo "Visit http://127.0.0.1:8080 to use your application"
kubectl --namespace {{ .Release.Namespace }} port-forward $POD_NAME 8080:$CONTAINER_PORT
{{- end }}
2. Make a prediction
curl http://$NODE_IP:$NODE_PORT/v1/models/{{ .Values.deploy.modelName }}
curl -X POST http://$NODE_IP:$NODE_PORT/v1/models/{{ .Values.deploy.modelName }}:predict -d '{"data": []}'
51 changes: 51 additions & 0 deletions workflows/charts/tensorflow-serving/templates/_helpers.tpl
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{{/*
Expand the name of the chart.
*/}}
{{- define "tensorflow-serving.name" -}}
{{- default .Chart.Name .Values.nameOverride | trunc 63 | trimSuffix "-" }}
{{- end }}

{{/*
Create a default fully qualified app name.
We truncate at 63 chars because some Kubernetes name fields are limited to this (by the DNS naming spec).
If release name contains chart name it will be used as a full name.
*/}}
{{- define "tensorflow-serving.fullname" -}}
{{- if .Values.fullnameOverride }}
{{- .Values.fullnameOverride | trunc 63 | trimSuffix "-" }}
{{- else }}
{{- $name := default .Chart.Name .Values.nameOverride }}
{{- if contains $name .Release.Name }}
{{- .Release.Name | trunc 63 | trimSuffix "-" }}
{{- else }}
{{- printf "%s-%s" .Release.Name $name | trunc 63 | trimSuffix "-" }}
{{- end }}
{{- end }}
{{- end }}

{{/*
Create chart name and version as used by the chart label.
*/}}
{{- define "tensorflow-serving.chart" -}}
{{- printf "%s-%s" .Chart.Name .Chart.Version | replace "+" "_" | trunc 63 | trimSuffix "-" }}
{{- end }}

{{/*
Common labels
*/}}
{{- define "tensorflow-serving.labels" -}}
helm.sh/chart: {{ include "tensorflow-serving.chart" . }}
{{ include "tensorflow-serving.selectorLabels" . }}
{{- if .Chart.AppVersion }}
app.kubernetes.io/version: {{ .Chart.AppVersion | quote }}
{{- end }}
app.kubernetes.io/managed-by: {{ .Release.Service }}
{{- end }}

{{/*
Selector labels
*/}}
{{- define "tensorflow-serving.selectorLabels" -}}
app.kubernetes.io/name: {{ include "tensorflow-serving.name" . }}
app.kubernetes.io/instance: {{ .Release.Name }}
{{- end }}
84 changes: 84 additions & 0 deletions workflows/charts/tensorflow-serving/templates/deployment.yaml
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# Copyright (c) 2024 Intel Corporation
#
# 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.
{{- $name := .Values.deploy.modelName | required ".Values.deploy.modelName is required." -}}
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: {{ include "tensorflow-serving.fullname" . }}
labels:
{{- include "tensorflow-serving.labels" . | nindent 4 }}
spec:
replicas: {{ .Values.deploy.replicas }}
selector:
matchLabels:
{{- include "tensorflow-serving.selectorLabels" . | nindent 6 }}
template:
metadata:
labels:
{{- include "tensorflow-serving.labels" . | nindent 8 }}
spec:
securityContext:
fsGroup: 1000
runAsUser: 1000
containers:
- name: tensorflow-serving
image: {{ .Values.deploy.image }}
{{- if eq .Values.deploy.env.enabled true }}
envFrom:
- configMapRef:
name: {{ .Values.deploy.env.configMapName }}
{{- end }}
env:
- name: MODEL_NAME
value: {{ .Values.deploy.modelName }}
ports:
- name: rest
containerPort: 8500
protocol: TCP
- name: grpc
containerPort: 8501
protocol: TCP
readinessProbe:
tcpSocket:
port: rest
initialDelay: 15
timeoutSeconds: 1
volumeMounts:
- mountPath: /dev/shm
name: dshm
{{- if .Values.deploy.storage.nfs.enabled }}
- name: model
mountPath: /models/{{ .Values.deploy.modelName }}
{{- else }}
- name: model
mountPath: /models/{{ .Values.deploy.modelName }}
{{- end }}
resources:
{{- toYaml .Values.deploy.resources | nindent 12 }}
volumes:
- name: dshm
emptyDir:
medium: Memory
{{- if .Values.deploy.storage.nfs.enabled }}
- name: model
nfs:
server: {{ .Values.deploy.storage.nfs.server }}
path: {{ .Values.deploy.storage.nfs.path }}
readOnly: {{ .Values.deploy.storage.nfs.readOnly }}
{{- else }}
- name: model
persistentVolumeClaim:
claimName: {{ include "tensorflow-serving.fullname" . }}-model-dir
{{- end }}
29 changes: 29 additions & 0 deletions workflows/charts/tensorflow-serving/templates/pvc.yaml
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# Copyright (c) 2024 Intel Corporation
#
# 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.

---
{{- if not .Values.deploy.storage.nfs.enabled }}
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
name: {{ include "tensorflow-serving.fullname" . }}-model-dir
labels:
{{- include "tensorflow-serving.labels" . | nindent 4 }}
spec:
accessModes:
- ReadWriteMany
resources:
requests:
storage: {{ .Values.pvc.size }}
{{- end }}
31 changes: 31 additions & 0 deletions workflows/charts/tensorflow-serving/templates/service.yaml
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# Copyright (c) 2024 Intel Corporation
#
# 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.

apiVersion: v1
kind: Service
metadata:
name: {{ include "tensorflow-serving.fullname" . }}
labels:
{{- include "tensorflow-serving.labels" . | nindent 4 }}
spec:
type: {{ .Values.service.type }}
ports:
- name: rest
port: 8500
targetPort: rest
- name: grpc
port: 8501
targetPort: grpc
selector:
{{- include "tensorflow-serving.selectorLabels" . | nindent 4 }}
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# Copyright (c) 2024 Intel Corporation
#
# 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.

apiVersion: v1
kind: Pod
metadata:
name: "{{ include "tensorflow-serving.fullname" . }}-test-connection"
labels:
{{- include "tensorflow-serving.labels" . | nindent 4 }}
annotations:
"helm.sh/hook": test
spec:
containers:
- name: info
image: curlimages/curl
command: ['sh', '-c']
args: ['curl -f {{ include "tensorflow-serving.fullname" . }}:8501/v1/models/{{ .Values.deploy.modelName}}']
restartPolicy: OnFailure
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