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

### 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

  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

        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.