# limitations under the License.
# ==============================================================================
source ci/official/envs/linux_x86
TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_cpu_linux --config=tpu"
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_tpu
TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_tpu"
TFCI_LIB_SUFFIX="-tpu-linux-x86_64"

		}
	}
}

func init() {
	cli.MakeKubeFactory = func(k kube.CLIClient) cmdutil.Factory {
		tf := cmdtesting.NewTestFactory()
		_, _, codec := cmdtesting.NewExternalScheme()
		tf.UnstructuredClient = &fake.RESTClient{
			NegotiatedSerializer: resource.UnstructuredPlusDefaultContentConfig().NegotiatedSerializer,
			Resp: &http.Response{

    can test it by passing that file's path to
    [tf_doctest.py](https://www.tensorflow.org/code/tensorflow/tools/docs/tf_doctest.py).
    For example:

    ```bash
    python tf_doctest.py --file=<file_path>
    ```

    This will run it using your installed version of TensorFlow. To be sure
    you're running the same code that you're testing:

    *   Use an up to date [tf-nightly](https://pypi.org/project/tf-nightly/)

# 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/...
}

@test "API compatibility test passes, ensuring no unexpected changes to the TF API" {

namespace tensorflow {
namespace tracing {

Status MaybeSetOpName(AbstractOperation* op, const char* op_name) {
  if (isa<TracingOperation>(op)) {
    TF_RETURN_IF_ERROR(dyn_cast<TracingOperation>(op)->SetOpName(op_name));
  }
  if (isa<gradients::TapeOperation>(op)) {
    TF_RETURN_IF_ERROR(MaybeSetOpName(
        dyn_cast<gradients::TapeOperation>(op)->GetBackingOperation(),
        op_name));
  }
  return absl::OkStatus();
}

		}
	}
}

func init() {
	cli.MakeKubeFactory = func(k kube.CLIClient) cmdutil.Factory {
		tf := cmdtesting.NewTestFactory()
		_, _, codec := cmdtesting.NewExternalScheme()
		tf.UnstructuredClient = &fake.RESTClient{
			NegotiatedSerializer: resource.UnstructuredPlusDefaultContentConfig().NegotiatedSerializer,
			Resp: &http.Response{

#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Register the POSIX filesystems statically.
// Return value will be unused
bool StaticallyRegisterLocalFilesystems() {
  TF_FilesystemPluginInfo info;
  TF_InitPlugin(&info);
  Status status = filesystem_registration::RegisterFilesystemPluginImpl(&info);
  if (!status.ok()) {
    VLOG(0) << "Static POSIX filesystem could not be registered: " << status;

if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then
  tfrun python3 tensorflow/tools/ci_build/update_version.py --nightly
  # replace tensorflow to tf_nightly in the wheel name
  export TFCI_BUILD_PIP_PACKAGE_ARGS="$(echo $TFCI_BUILD_PIP_PACKAGE_ARGS | sed 's/tensorflow/tf_nightly/')"
fi

tfrun bazel build $TFCI_BAZEL_COMMON_ARGS //tensorflow/tools/pip_package:wheel $TFCI_BUILD_PIP_PACKAGE_ARGS

		}
	}
}

func init() {
	cli.MakeKubeFactory = func(k kube.CLIClient) cmdutil.Factory {
		tf := cmdtesting.NewTestFactory()
		_, _, codec := cmdtesting.NewExternalScheme()
		tf.UnstructuredClient = &fake.RESTClient{
			NegotiatedSerializer: resource.UnstructuredPlusDefaultContentConfig().NegotiatedSerializer,
			Resp: &http.Response{

    const std::vector<Gradient*>& in_grads, absl::Span<Gradient*> out_grads) {
  /* This function is approximately equivalent to this Python code:

  forwardprop_aids = tf.ones_like(output_tensors)
  with tf.GradientTape() as g:
    g.watch(forwardprop_aids)
    grad = backward_function(forwardprop_aids)
  forward_grads = g.gradient(grad, forwardprop_aids, output_gradients=in_grads)