return portalHostMap, nil
}

// FindDevicesForISCSILun unsupported returns nil
func (handler *deviceHandler) FindDevicesForISCSILun(targetIqn string, lun int) ([]string, error) {
	devices := []string{}
	return devices, nil

// CHECK-SAME:    sharding={
// CHECK-SAME:    {devices=[1,2]0,1}
// CHECK-SAME:    {maximal device=0}
// CHECK-SAME:    {replicated}
// CHECK-SAME:    }
// CHECK:         get-tuple-element((f32[128,10]{1,0}, f32[10,1024]{1,0}, f32[128,1024]{1,0}) %[[ARG_TUPLE]]), index=0
// CHECK-SAME:    sharding={devices=[1,2]0,1}

// The id of the compiled cluster.
extern const char* const kXlaClusterIdAttr;  // "_xla_compile_id"

[[deprecated("XLA:CPU/GPU devices are deprecated")]] void
RequestXlaDevicesCreation();

[[deprecated("XLA:CPU/GPU devices are deprecated")]] bool
XlaDevicesCreationRequired();

}  // namespace tensorflow

module attributes {tf.versions = {producer = 888 : i32}, tf.devices = ["/job:localhost/replica:0/task:0/device:CPU:0", "/job:localhost/replica:0/task:0/device:TPU_SYSTEM:0", "/job:localhost/replica:0/task:0/device:TPU:0", "/job:localhost/replica:0/task:0/device:TPU:1", "/job:localhost/replica:0/task:0/device:TPU:2", "/job:localhost/replica:0/task:0/device:TPU:3", "/job:localhost/replica:0/task:0/device:TPU:4", "/job:localhost/replica:0/task:0/device:TPU:5", "/job:localhost/replica:0/task:0/device:TPU:6",...

limitations under the License.
*/

package procfs

type FakeProcFS struct{}

// GetFullContainerName gets the container name given the root process id of the container.
// E.g. if the devices cgroup for the container is stored in /sys/fs/cgroup/devices/docker/nginx,
// return docker/nginx. Assumes that the process is part of exactly one cgroup hierarchy.
func (fakePfs *FakeProcFS) GetFullContainerName(pid int) (string, error) {
	return "", nil

}

// getCgroupV1Path gets the file path to the "devices" subsystem of the desired cgroup.
// cgroupPath is the path in the cgroup hierarchy.
func getCgroupV1Path(cgroupPath string) (string, error) {
	cgroupPath = libcontainerutils.CleanPath(cgroupPath)

	mnt, root, err := libcontainercgroups.FindCgroupMountpointAndRoot(cgroupPath, "devices")
	// If we didn't mount the subsystem, there is no point we make the path.

  for (const auto& device_name : device_names) {
    device_count->insert({device_name, 1});
  }

  std::vector<std::unique_ptr<Device>> devices;
  TF_CHECK_OK(DeviceFactory::AddDevices(
      options, "/job:localhost/replica:0/task:0", &devices));
  device_mgr_ = std::make_unique<StaticDeviceMgr>(std::move(devices));

  OptimizerOptions opts;
  lib_def_ = std::make_unique<FunctionLibraryDefinition>(OpRegistry::Global(),

class RuntimeDevices;

// Returns true if at least one GPU device is available at runtime.
bool CanUseGpuDevice(const RuntimeDevices &devices);

// Returns true if all of the GPUs available at runtime support TensorCores
// (NVIDIA compute capability >= 7.0).
bool CanUseTensorCores(const RuntimeDevices &devices);

// Returns true if operation does not have explicit device placement that would
// prevent it from running on GPU device.

// -----

// CHECK-LABEL: func @replicate_with_devices
func.func @replicate_with_devices() {
  tf_device.replicate() {n = 2 : i32, devices = {TPU_REPLICATED_CORE_0 = ["/DEVICE:0", "/DEVICE:1"]}} {
    tf_device.return
  }
  func.return

// CHECK:      tf_device.replicate
// CHECK-SAME: devices = {TPU_REPLICATED_CORE_0 = ["/DEVICE:0", "/DEVICE:1"]}
// CHECK-SAME: n = 2
// CHECK-NEXT:   tf_device.return
}

// -----

		prepared:       false,
	}
	for pluginName, devices := range info.CDIDevices {
		annotations, _ := cdi.GenerateAnnotations(info.ClaimUID, info.DriverName, devices)
		info.annotations[pluginName] = append(info.annotations[pluginName], annotations...)
	}
	return info
}

// setCDIDevices adds a set of CDI devices to the claim info.