fi

tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS build $TFCI_BAZEL_COMMON_ARGS --config=cuda_wheel //tensorflow/tools/pip_package:wheel $TFCI_BUILD_PIP_PACKAGE_BASE_ARGS $TFCI_BUILD_PIP_PACKAGE_WHEEL_NAME_ARG --verbose_failures

tfrun "$TFCI_FIND_BIN" ./bazel-bin/tensorflow/tools/pip_package -iname "*.whl" -exec cp {} $TFCI_OUTPUT_DIR \;
tfrun mkdir -p ./dist
tfrun cp $TFCI_OUTPUT_DIR/*.whl ./dist

///

## **FastAPI** Tools { #fastapi-utilities }

FastAPI stellt für jedes dieser Sicherheitsschemas im Modul `fastapi.security` verschiedene Tools bereit, die die Verwendung dieser Sicherheitsmechanismen vereinfachen.

your changes by running the command:

```bash
tensorflow/tools/ci_build/ci_build.sh CPU tensorflow/tools/ci_build/ci_sanity.sh
```

This will catch most license, Python coding style and BUILD file issues that
may exist in your changes.

#### Running unit tests

There are two ways to run TensorFlow unit tests.

1.  Using tools and libraries installed directly on your system.

    Refer to the

But in most of the cases where we need to do something like this, we want the model just to **filter/remove** some of the data as in this example.

And in those cases, we can use classes and inheritance to take advantage of function **type annotations** to get better support in the editor and tools, and still get the FastAPI **data filtering**.

  <description>Test the use of a system scoped dependency to a (fake) tools.jar.</description>

  <dependencies>
    <dependency>
      <groupId>com.sun</groupId>
      <artifactId>tools</artifactId>
      <version>1.4.2</version>
      <scope>system</scope>
      <systemPath>${jre.home}/../lib/tools.jar</systemPath>
    </dependency>
  </dependencies>

  <build>
    <plugins>
      <plugin>

  rm -rf "${tmp_dir}"
}

DIR=$1
mkdir -p "$DIR"
TARBALL_SUFFIX=$2

if [[ $(uname -s) != MSYS_NT* ]]; then
  cp bazel-bin/tensorflow/tools/lib_package/libtensorflow.tar.gz "${DIR}/libtensorflow${TARBALL_SUFFIX}.tar.gz"
  cp bazel-bin/tensorflow/tools/lib_package/libtensorflow_jni.tar.gz "${DIR}/libtensorflow_jni${TARBALL_SUFFIX}.tar.gz"
  cp bazel-bin/tensorflow/java/libtensorflow.jar "${DIR}"

[pip-compile](https://pypi.org/project/pip-tools/) under the hood):

```
bazel run //ci/official/requirements_updater:requirements.update --repo_env=HERMETIC_PYTHON_VERSION=3.12
```

where `3.12` is the `Python` version you wish to update.

Note, since it is still `pip` and `pip-compile` tools used under the hood, so
most of the command line arguments and features supported by those tools will be

   *
   * [rfc_7468]: https://tools.ietf.org/html/rfc7468
   */
  fun certificatePem(): String = certificate.certificatePem()

  /**
   * Returns the private key encoded in [PKCS #8][rfc_5208] [PEM format][rfc_7468].
   *
   * [rfc_5208]: https://tools.ietf.org/html/rfc5208
   * [rfc_7468]: https://tools.ietf.org/html/rfc7468
   */
  fun privateKeyPkcs8Pem(): String =

///

## **FastAPI** utilities { #fastapi-utilities }

FastAPI provides several tools for each of these security schemes in the `fastapi.security` module that simplify using these security mechanisms.

In the next chapters you will see how to add security to your API using those tools provided by **FastAPI**.

name: Gopls bugs or feature requests
description: Issues or feature requests for the Go language server (gopls)
title: "x/tools/gopls: issue title"
labels: ["gopls", "Tools"]
body:
  - type: markdown
    attributes:
      value: "Please answer these questions before submitting your issue. Thanks!"
  - type: textarea
    id: gopls-version
    attributes:
      label: "gopls version"
      description: "Output of `gopls -v version` on the command line"