feed2_ = Placeholder(graph_, s_, "feed2");
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

    constant_ = ScalarConst(10, graph_, s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

    desc_ = TF_NewOperation(graph_, "AddN", "add");
    TF_Output inputs[] = {{feed1_, 0}, {constant_, 0}};
    TF_AddInputList(desc_, inputs, TF_ARRAYSIZE(inputs));
  }

  ~CApiColocationTest() override {

FROM ubuntu:20.04 as builder
################################################################################

# Install devtoolset build dependencies
COPY setup.packages.sh setup.packages.sh
COPY builder.packages.txt builder.packages.txt
RUN /setup.packages.sh /builder.packages.txt
RUN update-ca-certificates
# Install devtoolset-9 in /dt10 with glibc 2.17 and libstdc++ 4.8, for building
# manylinux2014-compatible packages.

py_repositories()

load("@rules_python//python:repositories.bzl", "python_register_multi_toolchains")  # buildifier: disable=same-origin-load
load("@rules_python//python/pip_install:repositories.bzl", "pip_install_dependencies")

default_python_version = "3.10"

load(
    "//:updater_config_repository.bzl",
    "updater_config_repository",  # @unused
)

# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn8=8.9.6.50-1+cuda12.2
libcudnn8-dev=8.9.6.50-1+cuda12.2

# This can be removed once NVIDIA publishes a cuda-12.3.2 Docker image.
# For now it ensures that we install at least version 12.3.107 of PTXAS,
# since 12.3.103 has a bug.

  // Check if the remote task is alive.
  virtual Status CheckRemoteAlive(const std::string& remote_task_name,
                                  bool* is_alive) = 0;

  // Get pointer to the coordination service agent instance.
  virtual tsl::CoordinationServiceAgent* GetCoordinationServiceAgent() = 0;
};
}  // namespace tensorflow

Changes to TensorFlow C++ code should conform to
[Google C++ Style Guide](https://google.github.io/styleguide/cppguide.html).

Use `clang-tidy` to check your C/C++ changes. To install `clang-tidy` on ubuntu:16.04, do:

```bash
apt-get install -y clang-tidy
```

You can check a C/C++ file by doing:


```bash
clang-format <my_cc_file> --style=google > /tmp/my_cc_file.cc
diff <my_cc_file> /tmp/my_cc_file.cc

    annotations = NUMPY_ANNOTATIONS,
    python_interpreter_target = interpreter,
    requirements = "//:requirements_lock_" + TF_PYTHON_VERSION.replace(".", "_") + ".txt",
)

load("@pypi//:requirements.bzl", "install_deps")

install_deps()

# Initialize the TensorFlow repository and all dependencies.
#
# The cascade of load() statements and tf_workspace?() calls works around the

  ls -sh *.whl
  exit 2
fi

# Quick install checks
venv=$(mktemp -d)
"python${TFCI_PYTHON_VERSION}" -m venv "$venv"
python="$venv/bin/python3"
"$python" -m pip install *.whl $TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS
if [[ "$TFCI_WHL_IMPORT_TEST_ENABLE" == "1" ]]; then
  "$python" -c 'import tensorflow as tf; t1=tf.constant([1,2,3,4]); t2=tf.constant([5,6,7,8]); print(tf.add(t1,t2).shape)'

  TensorFlow's `tf-nightly` package will soon be updated to TensorFlow 2.0.

  Please upgrade your code to TensorFlow 2.0:
    * https://www.tensorflow.org/guide/migrate

  Or install the latest stable TensorFlow 1.X release:
    * `pip install -U "tensorflow==1.*"`

  Otherwise your code may be broken by the change.

  """)

# Make sure directory containing top level submodules is in

    srcs = ["c_api_test.cc"],
    data = [
        ":test_op1.so",
        "//tensorflow/cc/saved_model:saved_model_half_plus_two",
    ],
    linkopts = select({
        "//tensorflow:macos": ["-headerpad_max_install_names"],
        "//conditions:default": [],
    }),
    tags = [
        "no_cuda_asan",  # TODO(b/181771536)
        "no_windows",  # TODO(b/155444728)
    ],