TEST(PermutationTest, PermuteEmptyArray) {
  const SmallVector<int> permutation_result =
      Permute<int>(SmallVector<int>{}, SmallVector<int64_t>{});
  EXPECT_THAT(permutation_result, IsEmpty());
}

TEST(PermutationTest, PermuteOneElement) {
  const SmallVector<int> single_element_array = {8};
  const SmallVector<int64_t> permutation = {0};

  const SmallVector<int> permutation_result =

func::FuncOp createMaxUnpoolingFunc(
    mlir::Builder* builder, const SmallVector<int64_t, 4>& input_shape,
    const SmallVector<int64_t, 4>& output_shape) {
  auto input_type = RankedTensorType::get(input_shape, builder->getF32Type());
  auto indices_type = RankedTensorType::get(input_shape, builder->getI64Type());
  auto output_type = RankedTensorType::get(output_shape, builder->getF32Type());
  SmallVector<mlir::Type, 2> input_types{input_type, indices_type};

namespace mlir::quant {
namespace {

void PackOperandTestHelper(
    const llvm::SmallVector<int64_t>& unpacked_shape,
    const llvm::SmallVector<int8_t>& unpacked_values, int pack_dim,
    const llvm::SmallVector<int64_t>& expected_packed_shape,
    const llvm::SmallVector<int8_t>& expected_packed_values) {
  MLIRContext context;
  OwningOpRef<ModuleOp> module(ModuleOp::create(UnknownLoc::get(&context)));

// of the index path attribute.
SmallVector<NamedAttribute> ReplaceBoundInputAttrWithIndexPathAttr(
    const ArrayRef<NamedAttribute> arg_attrs, const StringRef index_path,
    Builder& builder) {
  // Keep all other attributes except the tf_saved_model.bound_input attribute,
  // as we are replacing it with tf_saved_model.index_path.
  SmallVector<NamedAttribute> new_arg_attrs;
  for (auto arg_attr : arg_attrs) {

SmallVector<TF::AssignVariableOp> GetTailWritesToReplicateInvariantResourceVars(
    tf_device::ReplicateOp replicate_op) {
  SmallVector<TF::AssignVariableOp, 16> tail_assign_variable_ops;
  llvm::SmallDenseSet<Value, 16> visited_resources;
  for (auto& op :
       llvm::reverse(replicate_op.getRegion().front().getOperations())) {
    SmallVector<Value> op_accessed_resources = GetAccessedResources(op);

    // and input devices, variables used by this function.
    llvm::SmallVector<llvm::StringRef, 4> input_names;
    llvm::SmallVector<
        std::pair<tensorflow::DataType, tensorflow::PartialTensorShape>, 4>
        input_specs;
    llvm::SmallVector<llvm::StringRef, 4> input_devices;
    llvm::SmallVector<mlir::Operation*, 4> bound_inputs;
    for (unsigned i = 0, e = func.getNumArguments(); i != e; ++i) {

#include "mlir/Support/LLVM.h"  // from @llvm-project

namespace mlir {
namespace TF {

SmallVector<int64_t, 4> ReversePermutation(ArrayRef<int64_t> permutation) {
  SmallVector<int64_t, 4> reverse(permutation.size());
  for (size_t i = 0; i < permutation.size(); ++i) {
    reverse[permutation[i]] = i;
  }
  return reverse;
}

SmallVector<int64_t, 4> GetDataFormatPermutation(StringRef from, StringRef to) {

      for (Operation& op : nested_block->getOperations()) update_from_op(&op);
    });
  }
  return SmallVector<Value>(results.getArrayRef());
}

llvm::SmallVector<Value> AccumulateResultsDefinedWithin(
    const llvm::SetVector<Operation*>& partition_ops) {
  llvm::SmallVector<Value> values_for_results;
  for (Operation* op : partition_ops) {
    if (IsConstantOrNone(op)) {
      continue;
    }

namespace mlir {
namespace quant {
namespace {

// Folds the operation recursively and return the results.
LogicalResult FoldOperation(OpBuilder& builder, Operation* op,
                            SmallVector<Value>& results) {
  SmallVector<ElementsAttr> inputs;
  for (auto operand : op->getOperands()) {
    auto preceding_const_op = operand.getDefiningOp<TF::ConstOp>();
    if (preceding_const_op) {

  builder->create<tf_device::ReturnOp>(loc, op->getResults());

  // Move op inside cluster.
  op->moveBefore(launch.GetBody().getTerminator());
}

llvm::SmallVector<Operation*, 4> GetResourceOpsUsingCompositeArgsInReplicate(
    tf_device::ReplicateOp replicate) {
  llvm::SmallVector<Operation*, 4> resource_users;
  const auto add_resource_op_to_list = [&resource_users](Operation* op) {