},
				CDIDevices: []kubecontainer.CDIDevice{
					{Name: "vendor1.com/class1=device1"},
					{Name: "vendor2.com/class2=device2"},
					{Name: "vendor3.com/class3=device3"},
					{Name: "vendor4.com/class4=device4"},
				},
			},
		},
		{
			description: "duplicate cdi devices are skipped",

      task_and_device = {task, device};
    }
  }

  return topology;
}

// Determine execution devices when topology and device assignment are defined.
// With a topology device coordinate to task and device mapping, device
// assignment device coordinates can then be mapped to task and device for TPU
// devices. The device assignment array is also validated.
//

	needed := required
	// Gets list of devices that have already been allocated.
	// This can happen if a container restarts for example.
	devices := m.podDevices.containerDevices(podUID, contName, resource)
	if devices != nil {
		klog.V(3).InfoS("Found pre-allocated devices for resource on pod", "resourceName", resource, "containerName", contName, "podUID", podUID, "devices", sets.List(devices))
		needed = needed - devices.Len()

			request:     5,
			devices: func() []pluginapi.Device {
				devices := []pluginapi.Device{}
				for i := 0; i < 100; i++ {
					id := fmt.Sprintf("Dev%d", i)
					devices = append(devices, makeNUMADevice(id, 0))
				}
				for i := 100; i < 200; i++ {
					id := fmt.Sprintf("Dev%d", i)
					devices = append(devices, makeNUMADevice(id, 1))
				}
				return devices
			}(),

	resources, exists := containers[contName]
	if !exists {
		return
	}
	for resource, devices := range resources {
		allocatedResources[resource] = allocatedResources[resource].Difference(devices.deviceIds.Devices())
	}
}

// Returns all devices allocated to the pods being tracked, keyed by resourceName.
func (pdev *podDevices) devices() map[string]sets.Set[string] {
	ret := make(map[string]sets.Set[string])
	pdev.RLock()

// A TPU device for execution alongside its associated host CPU device.
struct TPUDeviceAndHost {
  TPUDeviceAndHost() = default;
  TPUDeviceAndHost(llvm::StringRef device, llvm::StringRef host)
      : device(device), host(host) {}

  std::string device;
  std::string host;
};

// TPU devices to be used for execution (e.g. devices for TPUExecute ops) and

		// request size and the list of available devices.
		deviceHints[resource] = m.generateDeviceTopologyHints(resource, available, sets.Set[string]{}, requested)
	}

	return deviceHints
}

func (m *ManagerImpl) deviceHasTopologyAlignment(resource string) bool {
	// If any device has Topology NUMANodes available, we assume they care about alignment.
	for _, device := range m.allDevices[resource] {

// cannot be run on other deviecs):
//
// We will try:
// 1) If we can do some mathmatically equaivalent transformation so this
//   subgraph can be run on other devices.
// 2) We will other apply device-specifics optimizations as well, that includes
//   maybe tensor layout transformation, device specific fusion, etc.
class AlternativeSubgraphPass

                              " device number ", i);
      return status;
    }
    device->SetAllowsSyncOnCompletion(false);
    if (tpu_xla_device_failure_closes_chips_flag) {
      device->SetHandleDeviceErrorCallback(&tpu::TpuNodeContext::CloseTpuHost);
    }

    devices->push_back(std::move(device));
  }

  return absl::OkStatus();
}

    devices.push_back(
        llvm::formatv("/job:worker/replica:0/task:{0}/device:CPU:0", task)
            .str());
    devices.push_back(
        llvm::formatv("/job:worker/replica:0/task:{0}/device:TPU_SYSTEM:0",
                      task)
            .str());
    for (int device = 0; device < num_devices_per_task; ++device)
      devices.push_back(