# Usage: Go to
# https://github.com/tensorflow/tensorflow/actions/workflows/release-branch-cherrypick.yml
# and click "Run Workflow." Leave "Use Workflow From" set to "master", then
# input the branch name and paste the cherry-pick commit and click Run. A PR
# will be created.

name: Release Branch Cherrypick
on:
  workflow_dispatch:
    inputs:
      # We use this instead of the "run on branch" argument because GitHub looks

then verify that requests were made as expected.

Because it exercises your full HTTP stack, you can be confident that you're
testing everything. You can even copy & paste HTTP responses from your real web
server to create representative test cases. Or test that your code survives in
awkward-to-reproduce situations like 500 errors or slow-loading responses.


### Example

  scheme: http
  static_configs:
  - targets: ['localhost:9000']
```

### 4. Update `scrape_configs` section in prometheus.yml

To authorize every scrape request, copy and paste the generated `scrape_configs` section in the prometheus.yml and restart the Prometheus service.

### 5. Start Prometheus

Start (or) Restart Prometheus service by running

```sh

      ) ?: return null

    // If we coalesced our connection, remember the replaced connection's route. That way if the
    // coalesced connection later fails we don't waste a valid route.
    if (planToReplace != null) {
      nextRouteToTry = planToReplace.route
      planToReplace.closeQuietly()
    }

    connectionUser.connectionAcquired(result)

![Swagger UI](https://fastapi.tiangolo.com/img/index/index-03-swagger-02.png)

* Klicken Sie auf die Taste „Try it out“, damit können Sie die Parameter ausfüllen und direkt mit der API interagieren:

![Swagger UI Interaktion](https://fastapi.tiangolo.com/img/index/index-04-swagger-03.png)

  bazel cquery --keep_going 'kind(py_test, //tensorflow/python/...) - attr("tags", "no_pip|manual", //tensorflow/python/...)' | grep -v -f $BATS_TEST_TMPDIR/ignore_deps_for_these_packages | paste -sd "+" - > $BATS_TEST_TMPDIR/deps
  # Find all one-step dependencies of those tests which are from //tensorflow
  # (since external deps will come from Python-level pip dependencies),

    That's because it is using the same name as in the OpenAPI spec. So that if you need to investigate more about any of these security schemes you can just copy and paste it to find more information about it.

The `oauth2_scheme` variable is an instance of `OAuth2PasswordBearer`, but it is also a "callable".

It could be called as:

```Python
oauth2_scheme(some, parameters)

```

But right at the moment Python compares the first `j` in `johndoe` to the first `s` in `stanleyjobson`, it will return `False`, because it already knows that those two strings are not the same, thinking that "there's no need to waste more computation comparing the rest of the letters". And your application will say "Incorrect username or password".

But then the attackers try with username `stanleyjobsox` and password `love123`.

   * uniform, the actual concurrency observed may vary. Ideally, you should choose a value to
   * accommodate as many threads as will ever concurrently modify the table. Using a significantly
   * higher value than you need can waste space and time, and a significantly lower value can lead
   * to thread contention. But overestimates and underestimates within an order of magnitude do not

  // `backward_function_deleter`) to compute jvps for this operation. If
  // `forward_function` is null, a GradientTape is used on the backward function
  // to compute the jvp, which will waste computation when executing eagerly.
  //
  // Unlike GradientTape::RecordOperation, Accumulate runs gradient computation
  // immediately. It stores the results, which feed into Accumulate for future