typing_extensions == 4.8.0
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.4.0, < 0.5.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch
keras-nightly ~= 3.0.0.dev
tb-nightly ~= 2.18.0.a
# Test dependencies

"""Merge all JUnit test.xml files in one directory into one.

Usage: squash_testlogs.py START_DIRECTORY OUTPUT_FILE

Example: squash_testlogs.py /tf/pkg/testlogs /tf/pkg/merged.xml

Recursively find all the JUnit test.xml files in one directory, and merge any
of them that contain failures into one file. The TensorFlow DevInfra team

            CACHEBUSTER=${{ steps.tf-version.outputs.DATE }}
          tags: |
            tensorflow/build:latest-${{ matrix.python-version }}
            tensorflow/build:${{ steps.tf-version.outputs.TF_VERSION }}-${{ matrix.python-version }}
            gcr.io/tensorflow-sigs/build:latest-${{ matrix.python-version }}
            gcr.io/tensorflow-sigs/build:${{ steps.tf-version.outputs.TF_VERSION }}-${{ matrix.python-version }}

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

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.:

TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow"
TFCI_DOCKER_ENABLE=1
TFCI_DOCKER_IMAGE=us-central1-docker.pkg.dev/tensorflow-sigs/tensorflow/build-arm64:tf-2-18-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

		}
	}
}

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{

		}

		for j, tf := range v.tests {
			switch tf := tf.(type) {
			case testRead:
				b := make([]byte, tf.cnt)
				n, err := fr.Read(b)
				if got := string(b[:n]); got != tf.wantStr || err != tf.wantErr {
					t.Errorf("test %d.%d, Read(%d):\ngot  (%q, %v)\nwant (%q, %v)", i, j, tf.cnt, got, err, tf.wantStr, tf.wantErr)
				}
			case testWriteTo:

2)  Reference [TensorFlow Lite Model Colab](https://colab.research.google.com/gist/ymodak/0dfeb28255e189c5c48d9093f296e9a8/tensorflow-lite-debugger-colab.ipynb): Demonstrate how to convert your TF model to a TF Lite model (with quantization, if used) and run TFLite Inference (if possible).

```

cat <<EOF
IMPORTANT: These tests ran under docker. This script does not clean up the
container for you! You can delete the container with:

$ docker rm -f tf

You can also execute more commands within the container with e.g.:

$ docker exec tf bazel clean
$ docker exec -it tf bash
EOF

	"k8s.io/kubectl/pkg/cmd/util"

	"istio.io/istio/pkg/kube"
)

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