# tensorflow/python:_pywrap_parallel_device.
filegroup(
    name = "lib_headers",
    srcs = ["parallel_device_lib.h"],
)

filegroup(
    name = "lib_sources",
    srcs = ["parallel_device_lib.cc"],
)

filegroup(
    name = "device_headers",
    srcs = ["parallel_device.h"],
)

filegroup(
    name = "device_sources",
    srcs = ["parallel_device.cc"],
)

filegroup(
    name = "headers",

        "//tensorflow/core:test_main",
        "@com_google_absl//absl/strings",
    ],
)

cc_library(
    name = "custom_device_testutil",
    testonly = True,
    srcs = ["custom_device_testutil.cc"],
    hdrs = ["custom_device_testutil.h"],
    visibility = ["//tensorflow:internal"],
    deps = [
        ":c_api",
        ":c_api_experimental",
        ":c_api_test_util",

    srcs = ["c_api_experimental_test.cc"],
    data = [
        "testdata/tf_record",
        "//tensorflow/c/experimental/stream_executor/test:test_pluggable_device.so",
        "//tensorflow/core/common_runtime/next_pluggable_device/c:test_next_pluggable_device_plugin.so",
    ],
    extra_copts = if_google(["-DTENSORFLOW_NO_SHARED_OBJECTS=1"]),
    linkopts = select({
        "//tensorflow:macos": ["-headerpad_max_install_names"],

)

# Config setting that is satisfied when CUDA device code should be compiled
# with clang. It does not imply that CUDA support has been enabled.
alias(
    name = "is_cuda_compiler_clang",
    actual = if_oss(
        "@local_config_cuda//:is_cuda_compiler_clang",
        "@local_config_cuda//cuda:TRUE",
    ),
)

# Config setting that is satisfied when CUDA device code should be compiled

# Handling Errors

There are many situations in which you need to notify an error to a client that is using your API.

This client could be a browser with a frontend, a code from someone else, an IoT device, etc.

You could need to tell the client that:

* The client doesn't have enough privileges for that operation.
* The client doesn't have access to that resource.
* The item the client was trying to access doesn't exist.
* etc.

*   The following APIs are not longer experimental:
    `tf.config.list_logical_devices`, `tf.config.list_physical_devices`,
    `tf.config.get_visible_devices`, `tf.config.set_visible_devices`,
    `tf.config.get_logical_device_configuration`,
    `tf.config.set_logical_device_configuration`.
*   `tf.config.experimentalVirtualDeviceConfiguration` has been renamed to

  // +optional
  optional string clusterIP = 3;

  // ClusterIPs is a list of IP addresses assigned to this service, and are
  // usually assigned randomly.  If an address is specified manually, is
  // in-range (as per system configuration), and is not in use, it will be
  // allocated to the service; otherwise creation of the service will fail.

- Kubeadm: fixed a bug during kubeadm upgrade, where it is not possible to mount a new device and create a symbolic link for /etc/kubernetes (or a sub-directory) so that kubeadm stores its information on the mounted device. ([#123406](https://github.com/kubernetes/kubernetes/pull/123406), [@SataQiu](https://github.com/SataQiu))

- During device plugin allocation, resources requested by the pod can only be allocated if the device plugin has registered itself to kubelet AND healthy devices are present on the node to be allocated. If these conditions are not sattsfied, the pod would fail with `UnexpectedAdmissionError` error. ([#116376](https://github.com/kuber...

- During device plugin allocation, resources requested by the pod can only be allocated if the device plugin has registered itself to kubelet AND healthy devices are present on the node to be allocated. If these conditions are not sattisfied, the pod would fail with `UnexpectedAdmissionError` error. ([#116337](https://github.com/kube...