mlir::IntegerAttr op_key;
  mlir::IntegerAttr cost;
  mlir::StringAttr device;
  mlir::StringAttr op_name;
  mlir::SymbolRefAttr f;
  llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand, 4> in_chains;
  llvm::SmallVector<mlir::OpAsmParser::UnresolvedOperand, 4> operands;
  mlir::NamedAttrList op_attrs;
  mlir::NamedAttrList op_func_attrs;
  auto loc = parser.getNameLoc();

  if (options.has_chain &&

#include "llvm/ADT/SmallVector.h"

namespace tensorflow {

llvm::SmallVector<int64_t> ConvertTFShapeToMlir(
    llvm::ArrayRef<int64_t> shapes) {
  return llvm::to_vector(llvm::map_range(shapes, [](int64_t shape) {
    return shape == kTFDynamicSize ? mlir::ShapedType::kDynamic : shape;
  }));
}

llvm::SmallVector<int64_t> ConvertMlirShapeToTF(
    llvm::ArrayRef<int64_t> shapes) {

def Size1InputRange : NativeCodeCall<
  "SmallVector<Value, 1>{$0}">;

def Size2InputRange : NativeCodeCall<
  "SmallVector<Value, 2>{$0, $1}">;

def Size3InputRange : NativeCodeCall<
  "SmallVector<Value, 3>{$0, $1, $2}">;

def EmptyCustomOptions : NativeCodeCall<
  "TFL::ConstBytesAttr::get($_builder.getContext(), \"\")">;

void FindCustomAggregatorOps(
    Region& region,
    const std::unordered_set<std::string>& aggregator_ops_to_ignore,
    SmallVector<Value>& statistics_outputs, SmallVector<StringRef>& ids,
    SmallVector<int32_t>& calibration_methods) {
  for (auto op : region.getOps<TF::CustomAggregatorOp>()) {
    if (aggregator_ops_to_ignore.count(op.getId().str())) continue;

#define TENSORFLOW_COMPILER_MLIR_QUANTIZATION_COMMON_LIFT_AS_FUNCTION_CALL_H_

#include "absl/base/nullability.h"
#include "absl/status/statusor.h"
#include "llvm/ADT/SmallVector.h"
#include "mlir/Bytecode/BytecodeOpInterface.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/Attributes.h"  // from @llvm-project

limitations under the License.
==============================================================================*/

// This pass remove Cluster ops by inlining Cluster ops.

#include "llvm/ADT/SmallVector.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_device.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"

          if (func && reachable_funcs.insert(func).second)
            funcs_to_visit.push_back(func);
        });
      };

  SmallVector<func::FuncOp, 4> funcs_to_visit;
  collect_reachable_funcs(region, funcs_to_visit);

  while (!funcs_to_visit.empty()) {
    SmallVector<func::FuncOp, 4> new_funcs_to_visit;
    for (func::FuncOp func_to_visit : funcs_to_visit) {
      if (!func_to_visit.getCallableRegion()) continue;

    ArrayRef<int64_t> transpose_perm = transpose_op.getPermutation();
    SmallVector<int64_t> new_padding_low =
        InvertPermutationToVector(pad_op.getEdgePaddingLow(), transpose_perm);
    SmallVector<int64_t> new_padding_high =
        InvertPermutationToVector(pad_op.getEdgePaddingHigh(), transpose_perm);
    SmallVector<int64_t> new_padding_interrier =

        return $_op.getDataFormat();
    }]>,
    InterfaceMethod<
      [{Returns indices of layout dependent arguments.}],
      "SmallVector<unsigned, 4>", "GetLayoutDependentArgs", (ins)
    >,
    InterfaceMethod<
      [{Returns indices of layout dependent results.}],
      "SmallVector<unsigned, 4>", "GetLayoutDependentResults", (ins)
    >,
    InterfaceMethod<

#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_UTILS_DYNAMIC_SHAPE_UTILS_H_

#include "mlir/IR/BuiltinTypes.h"  // from @llvm-project

namespace tensorflow {

llvm::SmallVector<int64_t> ConvertTFShapeToMlir(llvm::ArrayRef<int64_t> shapes);

llvm::SmallVector<int64_t> ConvertMlirShapeToTF(llvm::ArrayRef<int64_t> shape);

static constexpr int64_t kTFDynamicSize = -1;