// given name, of type nameType. The argument parsedName contains the parsed
// form of name, suitable for passing to the match function. The total number
// of comparisons is tracked in the given count and should not exceed the given
// limit.
func (c *Certificate) checkNameConstraints(count *int,
	maxConstraintComparisons int,
	nameType string,
	name string,
	parsedName any,

#include "tensorflow/core/util/device_name_utils.h"

namespace mlir {
namespace TF {
namespace {

using DeviceNameUtils = ::tensorflow::DeviceNameUtils;
using ParsedName = ::tensorflow::DeviceNameUtils::ParsedName;

constexpr const char *kHostAttr = "host";
constexpr const char *kDeviceAttr = "device";
constexpr const char *kTFDeviceAttr = "tf.device";

  // LINT.IfChange
  auto device_id = StringAttr::get(call->getContext(), "device");
  auto caller_device = call->getAttrOfType<StringAttr>(device_id);
  if (!caller_device) return;

  DeviceNameUtils::ParsedName caller_parsed_device;
  if (!DeviceNameUtils::ParseFullName(caller_device.getValue().str(),
                                      &caller_parsed_device))
    return;

  MLIRContext *context = call->getContext();

  // Find and return a function record added by its name.
  virtual core::RefCountPtr<FunctionRecord> FindRecord(
      const string& name) const = 0;

  // Return the ParsedName of Host CPU device.
  virtual const DeviceNameUtils::ParsedName& HostCPUParsedName() const = 0;
  virtual const string& HostCPUName() const = 0;

  // Configure soft device placement policy.
  virtual void SetAllowSoftPlacement(bool enable) = 0;

constexpr char kTPUReplicatedHost[] = "TPU_REPLICATED_HOST";
constexpr char kBadIntArrayElementMsg[] =
    "bad '{0}' attribute at index {1}, not an int";

using ParsedDevice = DeviceNameUtils::ParsedName;
using ParsedDevices = llvm::ArrayRef<DeviceNameUtils::ParsedName>;

namespace {
// Find matching devices in `devices` based on pattern `spec`.
llvm::SmallVector<ParsedDevice, 8> FindMatchingDevices(
    ParsedDevices devices, const ParsedDevice& spec) {

  }
  result.emplace(std::move(per_device_outputs));
  return result;
}

std::vector<std::string> ParallelDevice::SummarizeDeviceNames() const {
  std::vector<DeviceNameUtils::ParsedName> parsed_components(
      underlying_devices_.size());
  for (int component_index = 0; component_index < underlying_devices_.size();
       ++component_index) {

    } else {
      device = alias.getDefiningOp()->getAttrOfType<StringAttr>(kDeviceAttr);
    }

    if (!device) return false;
    tensorflow::DeviceNameUtils::ParsedName parsed_device;
    if (!tensorflow::DeviceNameUtils::ParseFullName(device.getValue().str(),
                                                    &parsed_device)) {
      return false;
    }

//       replica_device_ids: 3
//       replica_device_ids: 7
//     }
//   }
absl::StatusOr<TPUDeviceAssignment> GetTPUCompilationAndExecutionDevices(
    llvm::ArrayRef<DeviceNameUtils::ParsedName> devices, int num_replicas,
    int num_cores_per_replica, llvm::StringRef topology_attr,
    llvm::ArrayRef<int64_t> device_assignment_attr);

DLDevice GetDlContext(TFE_TensorHandle* h, TF_Status* status) {
  DLDevice ctx;
  const char* device_name =
      tensorflow::unwrap(h)->BackingDeviceName(&status->status);
  DeviceNameUtils::ParsedName parsed_name;
  tensorflow::DeviceNameUtils::ParseFullName(device_name, &parsed_name);
  std::string device_type = parsed_name.type;
  int device_id = 0;
  if (parsed_name.has_id) {
    device_id = parsed_name.id;

    string name;
    // Only consider nodes being compiled.
    if (!TryGetNodeAttr(n->attrs(), kXlaClusterIdAttr, &name)) continue;
    // Early return for any node with a device that is not a CPU or GPU.
    DeviceNameUtils::ParsedName parsed;
    if (DeviceNameUtils::ParseFullName(n->requested_device(), &parsed)) {
      if (parsed.type != DEVICE_CPU && parsed.type != DEVICE_GPU) {
        return false;
      }
    }
  }
  return true;
}