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|
%global _empty_manifest_terminate_build 0
Name: python-bentoutils
Version: 1.1.2
Release: 1
Summary: Utilities for working with BentoML V1.x
License: MIT License
URL: https://github.com/markmo/bentoutils
Source0: https://mirrors.aliyun.com/pypi/web/packages/c3/18/8230cb18ad7c2d3a929999e92ea987f91272e5387eac6bf41d551ed49c9c/bentoutils-1.1.2.tar.gz
BuildArch: noarch
Requires: python3-BentoML
Requires: python3-boto3
Requires: python3-click
Requires: python3-kubernetes
Requires: python3-PyYAML
Requires: python3-stringcase
Requires: python3-text-unidecode
%description
# bentoutils
## Contents
Console scripts for:
1. bentopack - package an existing pretrained model and save to the Model Registry
```
Usage: bentopack [OPTIONS]
Options:
--module TEXT fully qualified module name containing service to package
--clz TEXT class name of service to package
--name TEXT model name
--path TEXT directory path of pretrained model
--help Show this message and exit.
```
Example:
```
bentopack \
--module TopicBentoService \ # python module containing service class
--clz TopicBentoService \ # service class
--name tm_train3_roberta_l_weigh \ # pretrained model name
--path /srv/models/multilabel-topic # local path to pretrained model (excluding name)
```
2. deploy_to_knative - WIP
Uses Kaniko
kaniko is a tool to build container images from a Dockerfile, inside a container or Kubernetes cluster.
kaniko solves two problems with using the Docker-in-Docker build method:
* Docker-in-Docker requires privileged mode to function, which is a significant security concern.
* Docker-in-Docker generally incurs a performance penalty and can be quite slow.
The setting `--isdockerconfig` is required when using a private registry such as Harbor.
We can build a Docker image with kaniko and push it to Docker Hub or any other standard Docker registry.
To push to DockerHub or any other username and password Docker registries we need to mount the Docker config.json file that contains the credentials. Caching will not work for DockerHub as it does not support repositories with more than 2 path sections (acme/myimage/cache), but it will work in Artifactory and maybe other registry implementations.
DOCKER_USERNAME=[...]
DOCKER_PASSWORD=[...]
AUTH=$(echo -n "${DOCKER_USERNAME}:${DOCKER_PASSWORD}" | base64)
cat << EOF > config.json
{
"auths": {
"https://index.docker.io/v1/": {
"auth": "${AUTH}"
}
}
}
EOF
Alternatively, to create a secret to authenticate to Google Cloud Registry, follow these steps:
1. Create a service account in the Google Cloud Console project you want to push the final image to with Storage Admin permissions.
2. Download a JSON key for this service account
3. Rename the key to kaniko-secret.json
4. To create the secret, run:
kubectl create secret generic kaniko-secret --from-file=<path to kaniko-secret.json>
Note: If using a GCS bucket in the same GCP project as a build context, this service account should now also have permissions to read from that bucket.
See https://github.com/GoogleContainerTools/kaniko
%package -n python3-bentoutils
Summary: Utilities for working with BentoML V1.x
Provides: python-bentoutils
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-bentoutils
# bentoutils
## Contents
Console scripts for:
1. bentopack - package an existing pretrained model and save to the Model Registry
```
Usage: bentopack [OPTIONS]
Options:
--module TEXT fully qualified module name containing service to package
--clz TEXT class name of service to package
--name TEXT model name
--path TEXT directory path of pretrained model
--help Show this message and exit.
```
Example:
```
bentopack \
--module TopicBentoService \ # python module containing service class
--clz TopicBentoService \ # service class
--name tm_train3_roberta_l_weigh \ # pretrained model name
--path /srv/models/multilabel-topic # local path to pretrained model (excluding name)
```
2. deploy_to_knative - WIP
Uses Kaniko
kaniko is a tool to build container images from a Dockerfile, inside a container or Kubernetes cluster.
kaniko solves two problems with using the Docker-in-Docker build method:
* Docker-in-Docker requires privileged mode to function, which is a significant security concern.
* Docker-in-Docker generally incurs a performance penalty and can be quite slow.
The setting `--isdockerconfig` is required when using a private registry such as Harbor.
We can build a Docker image with kaniko and push it to Docker Hub or any other standard Docker registry.
To push to DockerHub or any other username and password Docker registries we need to mount the Docker config.json file that contains the credentials. Caching will not work for DockerHub as it does not support repositories with more than 2 path sections (acme/myimage/cache), but it will work in Artifactory and maybe other registry implementations.
DOCKER_USERNAME=[...]
DOCKER_PASSWORD=[...]
AUTH=$(echo -n "${DOCKER_USERNAME}:${DOCKER_PASSWORD}" | base64)
cat << EOF > config.json
{
"auths": {
"https://index.docker.io/v1/": {
"auth": "${AUTH}"
}
}
}
EOF
Alternatively, to create a secret to authenticate to Google Cloud Registry, follow these steps:
1. Create a service account in the Google Cloud Console project you want to push the final image to with Storage Admin permissions.
2. Download a JSON key for this service account
3. Rename the key to kaniko-secret.json
4. To create the secret, run:
kubectl create secret generic kaniko-secret --from-file=<path to kaniko-secret.json>
Note: If using a GCS bucket in the same GCP project as a build context, this service account should now also have permissions to read from that bucket.
See https://github.com/GoogleContainerTools/kaniko
%package help
Summary: Development documents and examples for bentoutils
Provides: python3-bentoutils-doc
%description help
# bentoutils
## Contents
Console scripts for:
1. bentopack - package an existing pretrained model and save to the Model Registry
```
Usage: bentopack [OPTIONS]
Options:
--module TEXT fully qualified module name containing service to package
--clz TEXT class name of service to package
--name TEXT model name
--path TEXT directory path of pretrained model
--help Show this message and exit.
```
Example:
```
bentopack \
--module TopicBentoService \ # python module containing service class
--clz TopicBentoService \ # service class
--name tm_train3_roberta_l_weigh \ # pretrained model name
--path /srv/models/multilabel-topic # local path to pretrained model (excluding name)
```
2. deploy_to_knative - WIP
Uses Kaniko
kaniko is a tool to build container images from a Dockerfile, inside a container or Kubernetes cluster.
kaniko solves two problems with using the Docker-in-Docker build method:
* Docker-in-Docker requires privileged mode to function, which is a significant security concern.
* Docker-in-Docker generally incurs a performance penalty and can be quite slow.
The setting `--isdockerconfig` is required when using a private registry such as Harbor.
We can build a Docker image with kaniko and push it to Docker Hub or any other standard Docker registry.
To push to DockerHub or any other username and password Docker registries we need to mount the Docker config.json file that contains the credentials. Caching will not work for DockerHub as it does not support repositories with more than 2 path sections (acme/myimage/cache), but it will work in Artifactory and maybe other registry implementations.
DOCKER_USERNAME=[...]
DOCKER_PASSWORD=[...]
AUTH=$(echo -n "${DOCKER_USERNAME}:${DOCKER_PASSWORD}" | base64)
cat << EOF > config.json
{
"auths": {
"https://index.docker.io/v1/": {
"auth": "${AUTH}"
}
}
}
EOF
Alternatively, to create a secret to authenticate to Google Cloud Registry, follow these steps:
1. Create a service account in the Google Cloud Console project you want to push the final image to with Storage Admin permissions.
2. Download a JSON key for this service account
3. Rename the key to kaniko-secret.json
4. To create the secret, run:
kubectl create secret generic kaniko-secret --from-file=<path to kaniko-secret.json>
Note: If using a GCS bucket in the same GCP project as a build context, this service account should now also have permissions to read from that bucket.
See https://github.com/GoogleContainerTools/kaniko
%prep
%autosetup -n bentoutils-1.1.2
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-bentoutils -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 1.1.2-1
- Package Spec generated
|
