commands.

*Nightly binaries are available for testing using the
[tf-nightly](https://pypi.python.org/pypi/tf-nightly) and
[tf-nightly-cpu](https://pypi.python.org/pypi/tf-nightly-cpu) packages on PyPi.*

#### *Try your first TensorFlow program*

```shell
$ python
```

```python
>>> import tensorflow as tf
>>> tf.add(1, 2).numpy()
3
>>> hello = tf.constant('Hello, TensorFlow!')
>>> hello.numpy()
b'Hello, TensorFlow!'

# This bazelrc can build a CPU-supporting TF package.

# Convenient cache configurations
# Use a cache directory mounted to /tf/cache. Very useful!
build:sigbuild_local_cache --disk_cache=/tf/cache
# Use the public-access TF DevInfra cache (read only)
build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false

# despite lacking Nvidia CUDA support.
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-2-16-multi-python
TFCI_DOCKER_PULL_ENABLE=1
TFCI_DOCKER_REBUILD_ARGS="--target=tf ci/official/containers/linux_arm64"
TFCI_INDEX_HTML_ENABLE=1
TFCI_LIB_SUFFIX="-cpu-linux-arm64"
TFCI_OUTPUT_DIR=build_output
TFCI_WHL_AUDIT_ENABLE=1

# Experimental windows filesystem plugin.
load("//tensorflow:tensorflow.bzl", "get_win_copts", "tf_cc_shared_object")
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

# Filesystem implementation for Windows environment
tf_cc_shared_object(
    name = "windows_filesystem.dll",
    framework_so = [],

RUN groupadd -g 1001 buildslave && useradd -m -u 1001 -g buildslave buildslave
RUN mkdir -p /tf/venv
RUN chown -R buildslave:buildslave /tf
RUN dpkg -i /patchelf/patchelf_0.14.3-1_arm64.deb

# All lines past this point are reset when $CACHEBUSTER is set. We need this
# for Python specifically because we install some nightly packages which are

# ==============================================================================

setup_file() {
    cd /tf/tensorflow
    bazel version  # Start the bazel server
    # Without this, git errors if /tf/tensorflow directory owner is different
    git config --global --add safe.directory /tf/tensorflow
    # Note that you could generate a list of all the affected targets with e.g.:

-   type: dropdown id: source attributes: label: Source description: Tensorflow

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_cpu_linux"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cpu
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_cpu"
TFCI_DOCKER_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"

# of as a "repository". They can't be valid on Linux because Linux can't do
# anything with a Windows-only toolchain, and bazel errors if trying to build
# that directory.
@test "bazel nobuild passes on all of TF except TF Lite and win toolchains" {
    bazel build --experimental_cc_shared_library --nobuild --keep_going -- //tensorflow/... -//tensorflow/lite/... -//tensorflow/tools/toolchains/win/... -//tensorflow/tools/toolchains/win_1803/...
}