load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

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

# Currently pybind extension shared objects must use only C API headers since
# the C API has static initializers duplicated in the Python bindings. So we
# need a second rule that omits .cc files, in
# tensorflow/python:_pywrap_parallel_device.
filegroup(

       That setting must exist for this script to function correctly.
EOF
  exit 1
fi
TFCI_BAZEL_COMMON_ARGS="$TFCI_BAZEL_COMMON_ARGS --config rbe_$TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX"

# These flags share the user's gcloud credentials with the container, so that bazel
# inside the container can authenticate. Note: TF's CI does not have any credential
# stored here.

TEST(CAPI, LibraryLoadFunctions) {
  // TODO(b/73318067): Fix linking for the GPU test generated by the
  // tf_cuda_cc_test() bazel rule and remove the next line.
  if (!GPUDeviceName().empty()) return;

#if !defined(TENSORFLOW_NO_SHARED_OBJECTS)
  {
    // Load the library.
    TF_Status* status = TF_NewStatus();
    string lib_path = tensorflow::GetDataDependencyFilepath(
        tensorflow::io::JoinPath("tensorflow", "c", "test_op1.so"));

  ~GraphFunction() override;

  // GraphFunction maybe stay alive for the duration of the returned
  // FunctionDef.
  Status GetFunctionDef(const FunctionDef** fdef) override;

  // Returns a shared reference to the wrapped function.
  absl::StatusOr<core::RefCountPtr<FunctionRecord>> GetFunctionRecord()
      override {
    return func_record_.GetNewRef();
  }

  // For LLVM style RTTI.

    -   `set -a` / `set -o allexport` exports the variables from `env` files so
        all scripts can use them.
    -   `utilities/setup_docker.sh` creates a container called `tf` with all
        `TFCI_` variables shared to it.
3.  Top-level scripts (`wheel.sh`, etc.) reference `env` variables and call
    `utilities/` scripts.
    -   The `tfrun` function makes a command run correctly in Docker if Docker

    ],
    extra_copts = if_google(["-DTENSORFLOW_NO_SHARED_OBJECTS=1"]),
    linkopts = select({
        "//tensorflow:macos": ["-headerpad_max_install_names"],
        "//conditions:default": [],
    }),
    # We must ensure that the dependencies can be dynamically linked since
    # the shared library must be able to use core:framework.
    deps = [
        ":c_api",

)

# Crosses between framework_shared_object and a bunch of other configurations
# due to limitations in nested select() statements.
config_setting(
    name = "framework_shared_object",
    define_values = {"framework_shared_object": "true"},
    visibility = ["//visibility:public"],
)

config_setting(
    name = "macos_x86_64_with_framework_shared_object",
    define_values = {

  TFE_OpSetAttrType(op, "dtype", TF_FLOAT);
  TFE_OpSetAttrShape(op, "shape", {}, 0, status);
  TFE_OpSetAttrString(op, "container", "localhost", 0);
  TFE_OpSetAttrString(op, "shared_name", "", 0);
  if (!device_name.empty()) {
    TFE_OpSetDevice(op, device_name.c_str(), status);
  }
  if (TF_GetCode(status) != TF_OK) return nullptr;
  TFE_TensorHandle* var_handle = nullptr;

        deprecated in favor of `tf.keras.layers.DenseFeatures`. v1 feature
        columns have direct analogues in v2 except for
        `shared_embedding_columns`, which are not cross-compatible with v1 and
        v2. Use `tf.feature_column.shared_embeddings` instead.

*   `tf.keras`:

    *   `OMP_NUM_THREADS` is no longer used by the default Keras config. To

# Disable AWS/HDFS support by default
build --define=no_aws_support=true
build --define=no_hdfs_support=true

# TF now has `cc_shared_library` targets, so it needs the experimental flag
# TODO(rostam): Remove when `cc_shared_library` is enabled by default
build --experimental_cc_shared_library

# cc_shared_library ensures no library is linked statically more than once.
build --experimental_link_static_libraries_once=false