libcufft-12-3
libcurand-12-3
libcusolver-dev-12-3
libcusparse-dev-12-3
libcublas-12-3
libcublas-dev-12-3
libnccl-dev=2.19.3-1+cuda12.3
libnccl2=2.19.3-1+cuda12.3
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn9-dev-cuda-12=9.1.1.17-1

            ${{ matrix.java }}
            24
          distribution: 'temurin'
          cache: 'maven'
      - name: 'Install'
        shell: bash
        run: ./mvnw -B -Dorg.slf4j.simpleLogger.log.org.apache.maven.cli.transfer.Slf4jMavenTransferListener=warn -Dtoolchain.skip install -U -DskipTests=true -f $ROOT_POM
      - name: 'Test'
        shell: bash

## Get started

In this document we will explain in detail on how to configure admin users.

### 1. Prerequisites

- Install mc - [MinIO Client Quickstart Guide](https://docs.min.io/community/minio-object-store/reference/minio-mc.html#quickstart)
- Install MinIO - [MinIO Quickstart Guide](https://docs.min.io/community/minio-object-store/operations/deployments/baremetal-deploy-minio-on-redhat-linux.html)

Regression Test
===============

A gradle module for running Regression tests on a device, emulator or JVM.

1. Add an Emulator named `pixel5`, if you don't already have one

```
$ sdkmanager --install "system-images;android-29;google_apis;x86"
$ echo "no" | avdmanager --verbose create avd --force --name "pixel5" --device "pixel" --package "system-images;android-29;google_apis;x86" --tag "google_apis" --abi "x86"
```

    /**
     * Shortcut for {@code getService(ArtifactInstaller.class).install(...)}.
     *
     * @param artifacts the artifacts to install
     * @throws org.apache.maven.api.services.ArtifactInstallerException if the artifacts installation failed
     *
     * @see org.apache.maven.api.services.ArtifactInstaller#install(Session, Collection)
     */
    void installArtifacts(@Nonnull ProducedArtifact... artifacts);

opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch

libcufft-12-8
libcurand-12-8
libcusolver-dev-12-8
libcusparse-dev-12-8
libcublas-12-8
libcublas-dev-12-8
libnccl-dev=2.25.1-1+cuda12.8
libnccl2=2.25.1-1+cuda12.8
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn9-dev-cuda-12=9.8.0.87-1

libcufft-13-0
libcurand-13-0
libcusolver-dev-13-0
libcusparse-dev-13-0
libcublas-13-0
libcublas-dev-13-0
libnccl-dev=2.27.7-1+cuda13.0
libnccl2=2.27.7-1+cuda13.0
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn9-dev-cuda-13=9.12.0.46-1

# FastAPI CLI { #fastapi-cli }

**FastAPI CLI** is a command line program that you can use to serve your FastAPI app, manage your FastAPI project, and more.

When you install FastAPI (e.g. with `pip install "fastapi[standard]"`), it includes a package called `fastapi-cli`, this package provides the `fastapi` command in the terminal.

To run your FastAPI app for development, you can use the `fastapi dev` command:

<div class="termy">

```console

        sessionScope.enter();
        try {
            sessionScope.seed(MavenSession.class, mock(MavenSession.class));

            String artifactBasedir = new File(getBasedir(), "src/test/resources/artifact-install").getAbsolutePath();

            Artifact artifact = createArtifact("artifact", "1.0");

            File file = new File(artifactBasedir, "artifact-1.0.jar");