HANDLE_TF_REF_TYPE(Int32Ref, INT32_REF, "int32ref")
HANDLE_TF_REF_TYPE(Uint64Ref, UINT64_REF, "uint64ref")
HANDLE_TF_REF_TYPE(Int64Ref, INT64_REF, "int64ref")
HANDLE_TF_REF_TYPE(StringRef, STRING_REF, "stringref")
HANDLE_TF_REF_TYPE(BoolRef, BOOL_REF, "boolref")
HANDLE_TF_REF_TYPE(Quint8Ref, QUINT8_REF, "quint8ref")
HANDLE_TF_REF_TYPE(Qint8Ref, QINT8_REF, "qint8ref")
HANDLE_TF_REF_TYPE(Quint16Ref, QUINT16_REF, "quint16ref")

          TestResourceAliasAnalysis, TF::ResourceAliasAnalysis> {
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(TestResourceAliasAnalysis)

  StringRef getArgument() const final {
    return "tf-test-resource-alias-analysis";
  }

  StringRef getDescription() const final {
    return "Add remarks based on resource alias analysis result, for testing "
           "purpose.";
  }

// passes to work with op attributes.

#ifndef TENSORFLOW_COMPILER_MLIR_LITE_UTILS_LSTM_UTILS_H_
#define TENSORFLOW_COMPILER_MLIR_LITE_UTILS_LSTM_UTILS_H_

#include "llvm/ADT/StringRef.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/Builders.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project

  for (size_t i = 0; i < permutation.size(); ++i) {
    reverse[permutation[i]] = i;
  }
  return reverse;
}

SmallVector<int64_t, 4> GetDataFormatPermutation(StringRef from, StringRef to) {
  if (from == "NHWC" && to == "NCHW") {
    return {0, 3, 1, 2};
  } else if (from == "NCHW" && to == "NHWC") {
    return {0, 2, 3, 1};
  } else {
    return {};
  }
}

                               OperationPass<func::FuncOp>> {
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(DeviceTransformGPUPass)

  llvm::StringRef getArgument() const final {
    return "tfl-device-transform-gpu";
  }
  llvm::StringRef getDescription() const final {
    return "Suitable transformation for gpu only.";
  }
  void getDependentDialects(DialectRegistry& registry) const override {

static constexpr char kArbitraryDeviceName[] = "XLA_CPU_JIT";

namespace {
inline absl::string_view StringRefToView(llvm::StringRef ref) {
  return {ref.data(), ref.size()};
}
}  // namespace

static OwningOpRef<mlir::ModuleOp> GraphdefToMlirTranslateFunction(
    llvm::StringRef input, MLIRContext* context) {
  tensorflow::GraphdefToMlirOptions options{
      debug_info_file,        xla_compile_device_type,

    if (failed(cast_i32)) return failure();

    int32_array.push_back(*cast_i32);
  }
  return int32_array;
}

StringRef GetEntryFunctionName(TF::XlaCallModuleOp op) {
  if (!op->hasAttrOfType<FlatSymbolRefAttr>(
          TF::kStablehloEntryFunctionAttrName)) {
    return StringRef();
  }
  return op
      ->getAttrOfType<FlatSymbolRefAttr>(TF::kStablehloEntryFunctionAttrName)
      .getValue();
}

                               mlir::OperationPass<ModuleOp>> {
 public:
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(FoldConstantsToSubgraphPass)

  llvm::StringRef getArgument() const final {
    return "tfl-fold-constants-to-subgraph";
  }
  llvm::StringRef getDescription() const final {
    return "Fold constants into each subgraph.";
  }
  FoldConstantsToSubgraphPass() = default;

  if (!llvm::isa<CallSiteLoc>(attr)) return false;
  auto callsite_loc = llvm::dyn_cast<CallSiteLoc>(attr);

  if (!mlir::isa<NameLoc>(callsite_loc.getCaller())) return false;
  StringRef caller_name =
      mlir::cast<NameLoc>(callsite_loc.getCaller()).getName().strref();
  return caller_name.starts_with(kQuantizationUnitPrefix) &&
         caller_name.ends_with(kQuantizationUnitSuffix);
}

==============================================================================*/
#include <functional>
#include <memory>

#include <gtest/gtest.h>
#include "absl/strings/string_view.h"
#include "llvm/ADT/StringRef.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/DialectRegistry.h"  // from @llvm-project