#include "mlir/IR/Operation.h"  // from @llvm-project
#include "mlir/IR/Region.h"  // from @llvm-project
#include "mlir/IR/Value.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

namespace mlir {
namespace TF {

class ResourceAnalyzer {
 public:

#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "mlir/Transforms/DialectConversion.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"  // IWYU pragma: keep
#include "xla/mlir_hlo/mhlo/IR/hlo_ops.h"

namespace mlir {
namespace odml {

LogicalResult ConvertCustomCallOp::matchAndRewrite(

class LegalizeHashTableOpPattern : public OpRewritePattern<TF::HashTableV2Op> {
 public:
  using OpRewritePattern<TF::HashTableV2Op>::OpRewritePattern;

  LogicalResult matchAndRewrite(TF::HashTableV2Op hashtable_op,
                                PatternRewriter& rewriter) const override {
    auto output_type = RankedTensorType::get(
        {1}, TF::ResourceType::get(rewriter.getContext()));

  auto unknown_loc = mlir::UnknownLoc::get(&context);

  int64_t device_ordinal0 = -1;
  mlir::LogicalResult result0 =
      GetDeviceOrdinalFromDeviceString(unknown_loc, tpu0, &device_ordinal0);
  EXPECT_TRUE(mlir::succeeded(result0));
  EXPECT_EQ(device_ordinal0, 0);

  int64_t device_ordinal1 = -1;
  mlir::LogicalResult result1 =
      GetDeviceOrdinalFromDeviceString(unknown_loc, tpu1, &device_ordinal1);

#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
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "tensorflow/core/framework/versions.pb.h"
#include "tensorflow/core/platform/statusor.h"

namespace tensorflow {

#include "mlir/IR/PatternMatch.h"  // from @llvm-project
#include "mlir/IR/Value.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "stablehlo/dialect/StablehloOps.h"  // from @stablehlo

namespace mlir::odml {

namespace {

// Helper class for parsing operands to a foldable operation.
class FoldAdaptor {

#include "mlir/IR/Value.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "mlir/Transforms/DialectConversion.h"  // from @llvm-project
#include "stablehlo/dialect/ChloOps.h"  // from @stablehlo

#include "mlir/IR/Visitors.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#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_structs.h"

#include "tsl/platform/file_statistics.h"
#include "tsl/platform/status.h"

namespace tensorflow {
namespace tf2xla {
namespace internal {
namespace {

using mlir::DialectRegistry;
using mlir::LogicalResult;
using mlir::MLIRContext;
using mlir::ModuleOp;
using mlir::OwningOpRef;
using mlir::PassManager;
using mlir::func::FuncOp;

std::string TestDataPath() {
  return tensorflow::GetDataDependencyFilepath(

#include <memory>
#include <utility>

#include "mlir/IR/MLIRContext.h"  // from @llvm-project
#include "mlir/Pass/Pass.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "mlir/Support/LogicalResult.h"  // from @llvm-project
#include "mlir/Transforms/GreedyPatternRewriteDriver.h"  // from @llvm-project
#include "mlir/Transforms/Passes.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/lite/transforms/passes.h"