TFCI_ARTIFACT_STAGING_GCS_URI="gs://tensorflow-ci-staging/staging/nightly/$(git rev-parse HEAD)/"

# 2. The internal version numbers get changed
TFCI_NIGHTLY_UPDATE_VERSION_ENABLE=1

# 3. Push results to public build cache (unique cache for MacOS)
if [[ $(uname -s) == "Darwin" ]]; then
  TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_macos_cache_push"
else
  TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_cache_push"

# ---
*.sw[nop]

# Emacs
# -----
*~
\#*\#
.\#*

# Textmate
# --------
.textmate

# Sublime Text
# ------------
*.sublime-*

# jEnv
# ----
.java-version

# macOS
# ----
.DS_Store

# HPROF
# -----
*.hprof

# Work dirs
# ---------
/incoming-distributions
/intTestHomeDir

# Logs
# ----
/*.log

# Thread dumps for troubleshooting

# limitations under the License.
# ==============================================================================
# Sourcing this enables Bazel remote cache (public, read-only)
# The cache configs are different for MacOS and Linux
if [[ $(uname -s) == "Darwin" ]]; then
  TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_macos_cache"
else
  TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config tf_public_cache"

# ==============================================================================
# Sourcing this enables local disk cache
if [[ $(uname -s) == "Darwin" ]]; then
  echo "Please note that using disk cache on macOS is not recommended because the"
  echo "cache can end up being pretty big and make the build process inefficient."
fi

  postgres:
    strategy:
      matrix:
        dbversion: ['postgres:latest', 'postgres:15', 'postgres:14', 'postgres:13']
        go: ['1.22', '1.21', '1.20']
        platform: [ubuntu-latest] # can not run in macOS and Windows
    runs-on: ${{ matrix.platform }}

    services:
      postgres:
        image: ${{ matrix.dbversion }}
        env:
          POSTGRES_PASSWORD: gorm
          POSTGRES_USER: gorm

### GNU/Linux and macOS

```sh
docker-compose pull
docker-compose up
```

or

```sh
docker stack deploy --compose-file docker-compose.yaml minio
```

### Windows

```sh
docker-compose.exe pull

        get() = false

    val buildSpecs: List<FlameGraphGenerationBuildSpec>
        get() = scenarios.flatMap { scenario ->
            Os.values().flatMap { os ->
                val arch = if (os == Os.MACOS) Arch.AARCH64 else Arch.AMD64
                if (os == Os.WINDOWS) {
                    listOf("jprofiler")
                } else {
                    listOf("async-profiler", "async-profiler-heap")

  val safari12iOS = sslLabsClients.first { it.userAgent == "Safari" && it.platform == "iOS 12.3.1" }
  val safari12Osx =
    sslLabsClients.first { it.userAgent == "Safari" && it.platform == "MacOS 10.14.6 Beta" }

  val okhttp = currentOkHttp(ianaSuitesNew)

  val okHttp_4_10 = historicOkHttp("4.10")
  val okHttp_3_14 = historicOkHttp("3.14")
  val okHttp_3_13 = historicOkHttp("3.13")

## Managing hermetic Python

To make sure that TensorFlow's build is reproducible, behaves uniformly across
supported platforms (Linux, Windows, MacOS) and is properly isolated from
specifics of a local system, we rely on hermetic Python (see
[rules_python](https://github.com/bazelbuild/rules_python)) for all build
and test commands executed via Bazel. This means that your system Python
installation will be ignored during the build and Python interpreter itself

 * [okhttp-system-keystore](https://github.com/charleskorn/okhttp-system-keystore): Use trusted certificates from the operating system keystore (Keychain on macOS, Certificate Store on Windows).
 * ⬜️ [Okio](https://github.com/square/okio/): A modern I/O API for Java.