==============================================================================*/

#include "mlir/Dialect/Func/Extensions/AllExtensions.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantTypes.h"  // from @llvm-project
#include "mlir/Dialect/SCF/IR/SCF.h"  // from @llvm-project
#include "mlir/Dialect/Shape/IR/Shape.h"  // from @llvm-project
#include "mlir/InitAllDialects.h"  // from @llvm-project

    return *this;
  }

  MlirDumpConfig& emit_dialect(Dialect dialect) {
    this->dialect = dialect;
    return *this;
  }

  // Op printing flags.
  mlir::OpPrintingFlags op_printing_flags = std::nullopt;

  // The target MLIR dialect.
  Dialect dialect = Dialect::kTFG;
};

// Change DumpGraphToFile to dump MLIR textual IR instead of protobuf.

#include "mlir/Dialect/Arith/IR/Arith.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/Dialect/Shape/IR/Shape.h"  // from @llvm-project
#include "mlir/Dialect/Tensor/IR/Tensor.h"  // from @llvm-project
#include "mlir/Transforms/DialectConversion.h"  // from @llvm-project
#include "stablehlo/dialect/ChloOps.h"  // from @stablehlo

  // Re-define publicly the protected addOperations() method from the Dialect
  // class, usually used in a Dialect constructor. This allows hook
  // functions to register operations on the TensorFlow dialect using the
  // same interface.
  template <typename... Args>
  void addOperations() {
    Dialect::addOperations<Args...>();
  }

        // Assign default device to all ops in Tensorflow dialect that do not
        // have device attribute.
        op->setAttr(kDeviceAttr, builder.getStringAttr(default_device_));
      }
    });
  }
};

#define GEN_PASS_DEF_TFDEVICEASSIGNMENTBYFUNCATTRPASS
#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.h.inc"

// A pass to perform device assignment for TF dialect ops that do not

namespace tf_executor {

class TensorFlowExecutorDialect : public Dialect {
 public:
  static StringRef getDialectNamespace() { return "tf_executor"; }
  explicit TensorFlowExecutorDialect(MLIRContext *context);

  // Parses a type registered to this dialect.
  Type parseType(DialectAsmParser &parser) const override;

  // Prints a type registered to this dialect.
  void printType(Type type, DialectAsmPrinter &os) const override;
};

// Creates an instance of the TensorFlow Lite dialect PrepareTF pass.
std::unique_ptr<OperationPass<func::FuncOp>> CreatePrepareTFPass(
    bool unfold_batch_matmul, bool allow_bf16_and_f16_type_legalization,
    bool use_fake_quant_num_bits = false);
std::unique_ptr<OperationPass<func::FuncOp>> CreatePrepareTFPass();

// Creates an instance of the TensorFlow Lite dialect LowerStaticTensorList
// pass.

namespace tensorflow {
namespace tf2xla {
namespace v1 {

// Given the input Module op that's in the Tensorflow Dialect, convert the MLIR
// module in place to the Tensorflow Executor Dialect. Returns an OK Status if
// success, otherwise failure with an error message.
// The Tensorflow Executor Dialect is required to export an MLIR module to a
// Tensorflow GraphDef. This API will add control dependencies and verify that

    "Counts how often a successful export from TF Dialect to Executor Dialect "
    "is",
    "status");

constexpr char kExportSuccess[] = "success";
constexpr char kExportFailed[] = "failed";

namespace {

void AddTfDialectToExecutorPasses(OpPassManager &pm) {
  pm.addPass(mlir::TF::CreateTFRegionControlFlowToFunctional());

  // First, we need to convert from functional, to executor dialect.
  pm.addNestedPass<FuncOp>(

==============================================================================*/
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project  // IWYU pragma: keep
#include "mlir/Dialect/Quant/QuantOps.h"  // from @llvm-project  // IWYU pragma: keep
#include "mlir/Dialect/Quant/QuantTypes.h"  // from @llvm-project  // IWYU pragma: keep
#include "mlir/Dialect/SparseTensor/IR/SparseTensor.h"  // from @llvm-project  // IWYU pragma: keep