# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
source ci/official/envs/linux_x86
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_gpu_linux"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cuda
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow"

# 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

# Test-related settings below this point.
test --build_tests_only --keep_going --test_output=errors --verbose_failures=true
test --test_timeout=500,900,-1,-1
# Give only the list of failed tests at the end of the log
test --test_summary=short

# "nonpip" tests are regular py_test tests.
# Pass --config=nonpip to run the same suite of tests. If you want to run just

## TensorFlow's Official CI and Build/Test Scripts

TensorFlow's official CI jobs run the scripts in this folder. Our internal CI
system, Kokoro, schedules our CI jobs by combining a build script with a file
from the `envs` directory that is filled with configuration options:

-   Nightly jobs (Run nightly on the `nightly` branch)
    -   Uses `wheel.sh`, `libtensorflow.sh`, `code_check_full.sh`
-   Continuous jobs (Run on every GitHub commit)

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
source ci/official/envs/linux_arm64

- Provide links to your updated versions of the above two colab notebooks.
- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.
```

#### Option B: Paste your code here or provide a link to a custom end-to-end colab

```
(You can paste links or attach files by dragging & dropping them below)
- Include code to invoke the TFLite Converter Python API and the errors.

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
source ci/official/envs/macos_x86
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION  --config cross_compile_macos_x86"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=cross_compile_macos_x86
TFCI_MACOS_CROSS_COMPILE_ENABLE=1

        # copybara:uncomment_begin(google-only)
        # "//tensorflow/cc/experimental/tf2:__pkg__",
        # "//tensorflow/cc/experimental/tf2:__subpackages__",
        # copybara:uncomment_end
        "//tensorflow/compiler/mlir/tensorflow/c:__subpackages__",
        "//tensorflow/core/transforms:__subpackages__",
    ],
    deps = [
        ":c_api_macros_hdrs",
        "@local_tsl//tsl/platform:status",

# load("//devtools/copybara/rules:copybara.bzl", "copybara_config_test")
# load("@rules_license//rules:license.bzl", "license")
# # buildifier: enable=out-of-order-load
# copybara:uncomment_end

# copybara:comment_begin(oss-only)
load("@bazel_skylib//rules:copy_file.bzl", "copy_file")
load(
    "//tensorflow/python/tools/api/generator:api_gen.bzl",
    "get_compat_files",
    "get_nested_compat_files",
)

internal communication only. It is not built for use in untrusted environments
or networks.

For performance reasons, the default TensorFlow server does not include any
authorization protocol and sends messages unencrypted. It accepts connections
from anywhere, and executes the graphs it is sent without performing any checks.
Therefore, if you run a `tf.train.Server` in your network, anybody with access