how we can reproduce your findings. For memory corruption triggerable in
    TensorFlow models, please demonstrate an exploit against one of Alphabet's
    models in <https://tfhub.dev/>
  - An explanation of who can exploit this vulnerability, and what they gain
    when doing so. Write an attack scenario that demonstrates how your issue

How to contribute
=================

Thank you so much for wanting to contribute to Guava! Here are a few important
things you should know about contributing:

1.  API changes require discussion, use cases, etc. Code comes later.
2.  Pull requests are great for small fixes for bugs, documentation, etc.
3.  Pull requests are not merged directly into the master branch.
4.  Code contributions require signing a Google CLA.

API changes
-----------

  // +optional
  optional k8s.io.apimachinery.pkg.apis.meta.v1.ListMeta metadata = 1;

  // items is the list of CronJobs.
  repeated CronJob items = 2;
}

// CronJobSpec describes how the job execution will look like and when it will actually run.
message CronJobSpec {
  // The schedule in Cron format, see https://en.wikipedia.org/wiki/Cron.
  optional string schedule = 1;

    with the API key and integrates that into the OpenAPI documentation. It extracts
    the key value sent in the query parameter automatically and provides it as the
    dependency result. But it doesn't define how to send that API key to the client.

    ## Usage

    Create an instance object and use that object as the dependency in `Depends()`.

    The dependency result will be a string containing the key value.

    Read more about it in the
    [FastAPI docs for Configure Swagger UI](https://fastapi.tiangolo.com/how-to/configure-swagger-ui/)
    and the [FastAPI docs for Custom Docs UI Static Assets (Self-Hosting)](https://fastapi.tiangolo.com/how-to/custom-docs-ui-assets/).
    """
    current_swagger_ui_parameters = swagger_ui_default_parameters.copy()
    if swagger_ui_parameters:

In fact, in some cases, it will even have **two JSON Schemas** in OpenAPI for the same Pydantic model, for input and output, depending on if they have **default values**.

Let's see how that works and how to change it if you need to do that.

## Pydantic Models for Input and Output

Let's say you have a Pydantic model with default values, like this one:

        stale-issue-label: "status:stale"
        days-before-stale: 0
        days-before-close: 30
        remove-stale-when-updated: true

    ],
)

tf_cuda_cc_test(
    name = "c_api_remote_test",
    size = "medium",
    srcs = [
        "c_api_remote_test.cc",
    ],
    # TODO(b/136478427): Figure out how to correctly shut the server down
    args = ["--heap_check="],
    tags = [
        "no_windows",
    ],
    deps = [
        ":c_api",
        ":c_api_experimental",
        ":c_api_internal",

You have been reading here some of the main concepts that you would probably need to keep in mind when deciding how to deploy your application:

* Security - HTTPS
* Running on startup
* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

        stale-issue-label: "status:stale"
        days-before-stale: 0
        days-before-close: 30
        remove-stale-when-updated: true