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By the time Courtney graduated, she was an all-state runner and had earned All-American honors as a Nordic skier three times. She was a four-time state champion, and her team acquired two national championships. In 2003, Courtney moved west to Colorado, where she raced collegiately on the Nordic ski team at the University of Denver. Three years in, her DU team won 11 meets and the 2005 NCAA Championship.

If you specify an array of strings or variables, your workflow will execute on any runner that matches all of the specified runs-on values. For example, here the job will only run on a self-hosted runner that has the labels linux, x64, and gpu:

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Note: The -latest runner images are the latest stable images that GitHub provides, and might not be the most recent version of the operating system available from the operating system vendor.

All self-hosted runners have the self-hosted label. Using only this label will select any self-hosted runner. To select runners that meet certain criteria, such as operating system or architecture, we recommend providing an array of labels that begins with self-hosted (this must be listed first) and then includes additional labels as needed. When you specify an array of labels, jobs will be queued on runners that have all the labels that you specify.

Although the self-hosted label is not required, we strongly recommend specifying it when using self-hosted runners to ensure that your job does not unintentionally specify any current or future GitHub-hosted runners.

In this example, a runner group called ubuntu-runners is populated with Ubuntu runners, which have also been assigned the label ubuntu-20.04-16core. The runs-on key combines group and labels so that the job is routed to any available runner within the group that also has a matching label:

A google search revealed nothing specific to gitlab-runner. I checked the gitlab-runner service which does not depend on any other services. So I do not understand the error message. I would appreciate any help I could get.

Runner allows bentoml.Service to parallelizemultiple instances of a bentoml.Runnable class,each on its own Python worker. When a BentoServer is launched, a group of runner workerprocesses will be created, and run method calls made from thebentoml.Service code will be scheduled among those runner workers.

BentoML provides pre-built Runners implemented for each ML framework supported. Thesepre-built runners are carefully configured to work well with each specific ML framework.They handle working with GPU when GPU is available, set the number of threads and numberof workers automatically, and convert the model signatures to corresponding Runnablemethods.

The bentoml.Runnable.method decorator is used for creatingRunnableMethod - the decorated method will be exposed as the runner interfacefor accessing remotely. RunnableMethod can be configured with a signature,which is defined same as the Model signatures.

Runnable class can also take __init__ parameters to customize its behavior fordifferent scenarios. The same Runnable class can also be used to create multiple runnersand used in the same service. For example:

The default Runner name is the Runnable class name. When using the same Runnableclass to create multiple runners and use them in the same service, user must renamerunners by specifying the name parameter when creating the runners. Runnername are a key to configuring individual runner at deploy time and to runner relatedlogging and tracing features.

In Embedded mode, the Runner is embedded within the same process as the API Server. This disables the dispatching layer, which means batchingis not available in this mode. To create an embedded Runner, use .to_runner(embedded=True).

Runners can be both configured individually or in aggregate under the runners configuration key. To configure a specific runner, specify its nameunder the runners configuration key. Otherwise, the configuration will be applied to all runners. The examples below demonstrate boththe configuration for all runners in aggregate and for an individual runner (iris_clf).

If a model or custom runner supports batching, the adaptive batching mechanism is enabled by default.To explicitly disable or control adaptive batching behaviors at runtime, configuration can be specified under the batching key.

Alternatively, a runner can be mapped to a specific set of GPUs. To specify GPU mapping, instead of defining an integer value, a list of device IDscan be specified for the nvidia.com/gpu key. For example, the following configuration maps the configured runners to GPU device 2 and 4.

Same as API server, you can also configure the traffic settings for both all runners and individual runner.Specifcally, traffic.timeout defines the amount of time in seconds that the runner will wait for a response from the model before timing out.traffic.max_concurrency defines the maximum number of concurrent requests the runner will accept before returning an error.

To create this pattern, we will work from the center of the runner outward alternating trellis and iris sections to create the first half of the runner. The second panel will be worked off of the foundation chain row of the first to complete the other half. This is so that the detail of the iris stitch is running toward each end of the table. You will work in turned rows using turning chains, which count as a stitch only when noted. Stitch counts can be found in ( ) at the end of row instructions.

The goal of the Runner Friendly Community designation is to shine a national spotlight on communities that standout as runner friendly and to provide incentive and ideas for communities to work towards becoming runner friendly communities.

Ruff Runner & Yappy Hour, presented by Epic Plumbing, is a pet-themed race for all ages. The run will feature a 5K for avid runners, while the featuring a Kids 1K and 3K options will continue with the paw-pular opportunity to run with or without a four-legged friend.

When I arrive where do I park? Parking is available at Independence Park and is first come, first serve. Vehicles must be parked by 7:30 a.m. and will not be able to move their vehicle until all runners have cleared the route and Pearland Police has reopened the roads for vehicle traffic. Please note the following IMPORTANT ROAD CLOSURES. Independence Park, Pearland Parkway north bound lanes, and John Lizer will close to vehicle traffic at 7:30 a.m. We encourage everyone to arrive early or you will not be allowed to enter and park onsite.

Drone runners poll the server for workloads to execute. There are different types of runners optimized for different use cases and runtime environments. You can install one or many runners, of one or many types.

The test-runner is a standalone, framework-agnostic utility that runs parallel to your Storybook. You will need to take some additional steps to set it up properly. Detailed below is our recommendation to configure and execute it.

Test runner offers zero-config support for Storybook. However, you can run test-storybook --eject for more fine-grained control. It generates a test-runner-jest.config.js file at the root of your project, which you can modify. Additionally, you can extend the generated configuration file and provide testEnvironmentOptions as the test runner also uses jest-playwright under the hood.

The test-runner is powered by Jest and accepts a subset of its CLI options (for example, --watch, --maxWorkers).If you're already using any of those flags in your project, you should be able to migrate them into Storybook's test-runner without any issues. Listed below are all the available flags and examples of using them.

By default, the test-runner assumes that you're running it against a locally served Storybook on port 6006. If you want to define a target URL to run against deployed Storybooks, you can use the --url flag or set the TARGET_URL environment variable. For example:

You can use your CI provider (for example, GitHub Actions, GitLab Pipelines, CircleCI) to build and run the test runner against your built Storybook. Here's a recipe that relies on third-party libraries, that is to say, concurrently, http-server, and wait-on to build Storybook and run tests with the test-runner.

Chromatic is a cloud-based service that runs visual and interaction tests (and soon accessibility tests) without setting up the test runner. It also syncs with your git provider and manages access control for private projects.

The test-runner renders a story and executes its play function if one exists. However, certain behaviors are impossible to achieve via the play function, which executes in the browser. For example, if you want the test-runner to take visual snapshots for you, this is possible via Playwright/Jest but must be executed in Node.

The test-runner exports test hooks that can be overridden globally to enable use cases like visual or DOM snapshots. These hooks give you access to the test lifecycle before and after the story is rendered.Listed below are the available hooks and an overview of how to use them.

When you run the test-runner on Storybook, it tests every story by default. However, if you want to filter the tests, you can use the tags configuration option. Storybook originally introduced this feature to generate automatic documentation for stories. But it can be further extended to configure the test-runner to run tests according to the provided tags using a similar configuration option or via CLI flags (e.g., --includeTags, --excludeTags, --skipTags), only available with the latest stable release (0.15 or higher). Listed below are the available options and an overview of how to use them.

If you want to prevent specific stories from being tested by the test-runner, you can configure your story with a custom tag, enable it to the test-runner configuration file or run the test-runner with the --excludeTags CLI flag and exclude them from testing. This is helpful when you want to exclude stories that are not yet ready for testing or are irrelevant to your tests. For example: ff782bc1db