"//tensorflow:tf_exported_symbols.lds",
        "//tensorflow:tf_private_symbols.lds",
        "//tensorflow:tf_version_script.lds",
    ],
    dynamic_deps = select({
        "//tensorflow:macos": ["//tensorflow:libtensorflow_framework.%s.dylib" % VERSION],
        "//conditions:default": ["//tensorflow:libtensorflow_framework.so.%s" % VERSION],
    }),
    exports_filter = [
        "//:__subpackages__",

  ASSERT_TRUE(TF_GraphOperationByName(graph, "scalar") != nullptr);
  Neg(oper, graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  ASSERT_TRUE(TF_GraphOperationByName(graph, "neg") != nullptr);

  // Export to a GraphDef.
  TF_Buffer* graph_def = TF_NewBuffer();
  TF_GraphToGraphDef(graph, graph_def, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Import it, with a prefix, in a fresh graph.

        "@com_google_absl//absl/strings",
        "@local_xla//xla/tsl/c:tsl_status_internal",
    ],
    alwayslink = 1,
)

exports_files(
    [
        "version_script.lds",
        "exported_symbols.lds",
    ],
    visibility = ["//visibility:public"],
)

filegroup(
    name = "checkpoint_reader_hdrs",
    srcs = [
        "checkpoint_reader.h",

    DCHECK_EQ(nullptr, session);
    return nullptr;
  }
}

TF_Session* TF_LoadSessionFromSavedModel(
    const TF_SessionOptions* session_options, const TF_Buffer* run_options,
    const char* export_dir, const char* const* tags, int tags_len,
    TF_Graph* graph, TF_Buffer* meta_graph_def, TF_Status* status) {
// TODO(sjr): Remove the IS_MOBILE_PLATFORM guard. This will require ensuring

}

TF_CAPI_EXPORT extern int TFE_OpGetInputLength(TFE_Op* op,
                                               const char* input_name,
                                               TF_Status* status) {
  int ret = -1;
  status->status = tensorflow::unwrap(op)->InputLength(input_name, &ret);
  return ret;
}

TF_CAPI_EXPORT extern int TFE_OpGetOutputLength(TFE_Op* op,

*   `tf.estimator`:
    *   `Estimator`s now use custom savers included in `EstimatorSpec` scaffolds
        for saving SavedModels during export.
    *   `EstimatorSpec` will now add a default prediction output for export if
        no `export_output` is provided, eliminating the need to explicitly
        include a `PredictOutput` object in the `model_fn` for simple use-cases.

# with ample storage. When this variable is empty (i.e by default), Bazel will
# use the output base directory to run tests.
if [[ "${TFCI_MACOS_BAZEL_TEST_DIR_ENABLE}" == 1 ]]; then
  mkdir -p "${TFCI_MACOS_BAZEL_TEST_DIR_PATH}"
  export TEST_TMPDIR="${TFCI_MACOS_BAZEL_TEST_DIR_PATH}"
fi

# "TFCI_MACOS_INSTALL_BAZELISK_ENABLE" is used to decide if we need to install
# Bazelisk manually. We enable this for macOS x86 builds as those VMs do not

# Update the version numbers for Nightly only
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

# one, checks the filesize, and then ensures the new wheel is installable.
set -euxo pipefail

cd "$TFCI_OUTPUT_DIR"

# Move extra wheel files somewhere out of the way. This script
# expects just one wheel file to exist.
if [[ "$(ls *.whl | wc -l | tr -d ' ')" != "1" ]]; then
  echo "More than one wheel file is present: moving the oldest to"
  echo "$TFCI_OUTPUT_DIR/extra_wheels."

  if (h == nullptr) {
    status->status = tensorflow::errors::InvalidArgument("Invalid handle");
    return -1;
  }
  return tensorflow::unwrap(h)->DeviceId(&status->status);
}

TF_CAPI_EXPORT extern void TFE_TensorHandleGetStatus(TFE_TensorHandle* h,
                                                     TF_Status* status) {
  status->status = tensorflow::unwrap(h)->TensorHandleStatus();
}