additional_attributes.end()) {}

  // Name of the output kernel implementing the contraction fusion.
  std::string output_kernel;

  // Indices of additional arguments that will be forwarded to the fused
  // operation (e.g. forward bias vector if fusing BiasAdd operation).
  SmallVector<int, 4> additional_arguments;

  // Add additional attributes to the fused node.

func fairAlloc(demands []float64, capacity float64) []float64 {
	count := len(demands)
	indices := make([]int, count)
	for i := 0; i < count; i++ {
		indices[i] = i
	}
	sort.Slice(indices, func(i, j int) bool { return demands[indices[i]] < demands[indices[j]] })
	alloc := make([]float64, count)
	var next int
	var prevAlloc float64
	for ; next < count; next++ {

  SmallVector<tf_device::ClusterFuncOp, 4> cluster_funcs;
  ModuleOp module = getOperation();
  module.walk([&](tf_device::ClusterFuncOp cluster_func) {
    // Map resource values to pair of input-output indices.
    llvm::DenseMap<Value, AliasInfo> resource_alias_info_map;
    if (failed(BuildAliasingInfo(cluster_func, resource_alias_info_map)) ||
        resource_alias_info_map.empty()) {
      return;
    }

    const XlaOpRegistry::DeviceRegistration& registration);

// Given a FunctionLibraryRuntime and a `function`, returns this function's body
// in `fbody` as well as the indices of its constant and resource arguments.
// `fbody` is owned by `flr`.
// `constant_arg_indices` and `resource_arg_indices` should be empty vector.
// They are sorted in ascending order on this function's return.

                      is_op_inside_IfRegions)) {
      return_indices_to_keep.push_back(index_and_value.index());
    }
  }
  return return_indices_to_keep;
}

// Return a vector of the return indices.
llvm::SmallVector<llvm::SmallVector<int, 4>> GetReturnIndicesVec(
    const llvm::SmallVector<TF::IfRegionOp, 8>& if_op_segment) {
  llvm::SmallVector<llvm::SmallVector<int, 4>> return_indices_vec;

		buf.WriteByte('.')
		buf.WriteString(x.Sel.Name)

	case *ast.IndexExpr, *ast.IndexListExpr:
		ix := typeparams.UnpackIndexExpr(x)
		WriteExpr(buf, ix.X)
		buf.WriteByte('[')
		writeExprList(buf, ix.Indices)
		buf.WriteByte(']')

	case *ast.SliceExpr:
		WriteExpr(buf, x.X)
		buf.WriteByte('[')
		if x.Low != nil {
			WriteExpr(buf, x.Low)
		}
		buf.WriteByte(':')
		if x.High != nil {

          it.sourceCodePoint1 < codePoint -> -1
          it.sourceCodePoint0 > codePoint -> 1
          else -> 0
        }
      }

    // Code points must be in 0..0x10ffff.
    require(index in mappings.indices) { "unexpected code point: $codePoint" }

    val mapping = mappings[index]
    var result = true

    when (mapping.type) {
      TYPE_IGNORED -> Unit
      TYPE_MAPPED, TYPE_DISALLOWED_STD3_MAPPED -> {

// Returns whether the sharding is replicated. It includes sharding with
// REPLICATED type and replicated OTHER type.
bool IsReplicatedSharding(const xla::OpSharding& sharding);

// Returns a map of dimension indices and number of splits for tiled sharding.
absl::StatusOr<std::map<int, int>> GetDimensionIndicesAndNumSplitsFromSharding(
    const xla::OpSharding& sharding);
}  // namespace tensorflow

  const int num_regions = parallel_execute.getNumRegions();
  llvm::SmallVector<Value, 4> results_to_remap;

  // Go through each region and find AssignVariableOps that can be moved into
  // the parallel_execute region. Result indices by region index are collected,
  // so they can be removed afterwards.
  llvm::SmallVector<llvm::SmallVector<int, 4>, 4> results_to_remove_by_region;
  results_to_remove_by_region.resize(num_regions);

		smap := makeSubstMap(tparams, targs)
		params = check.subst(nopos, params, smap, nil, check.context()).(*Tuple)
	}

	// Unify parameter and argument types for generic parameters with typed arguments
	// and collect the indices of generic parameters with untyped arguments.
	// Terminology: generic parameter = function parameter with a type-parameterized type
	u := newUnifier(tparams, targs, check.allowVersion(pos, go1_21))