let name = "tf_saved_model";

  let summary = "Dialect used to represent TensorFlow SavedModel in MLIR.";

  let description = [{
    This dialect's main responsibility is to represent the additional
    information present in the SavedModel's SavedObjectGraph, which
    describes the public interface of this SavedModel.

    Module's using this dialect should have the module attribute
    `tf_saved_model.semantics`.

// TensorFlowSavedModelDialect Dialect
//===----------------------------------------------------------------------===//

TensorFlowSavedModelDialect::TensorFlowSavedModelDialect(MLIRContext *context)
    : Dialect(/*name=*/"tf_saved_model", context,
              TypeID::get<TensorFlowSavedModelDialect>()) {
  // The TensorFlow Dialect is needed in the verifier and other routines

// This file implements logic for lowering TensorFlow dialect's collective
// ops (TF/XLA) to the HLO dialect.

#include <numeric>
#include <string>
#include <utility>

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

  if (attr_name == "_handle_dtypes" || attr_name == "_handle_shapes")
    return attr_value.value_case() == AttrValue::kList;
  return false;
}

void LoadImporterDialects(mlir::MLIRContext& context) {
  // Load dialects involved in the conversion
  mlir::DialectRegistry registry;
  mlir::RegisterAllTensorFlowDialectsImpl(registry, false);
  context.appendDialectRegistry(registry);
  for (llvm::StringRef name : registry.getDialectNames())

#include "mlir/Dialect/Arith/IR/Arith.h"  // from @llvm-project
#include "mlir/Dialect/Func/Extensions/AllExtensions.h"  // from @llvm-project
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/Dialect/Quant/QuantOps.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/IR/Dialect.h"  // from @llvm-project
#include "mlir/IR/OpDefinition.h"  // from @llvm-project
#include "mlir/IR/Value.h"  // from @llvm-project
#include "mlir/Interfaces/ControlFlowInterfaces.h"  // from @llvm-project
#include "mlir/Interfaces/SideEffectInterfaces.h"  // from @llvm-project

namespace mlir {
namespace tf_device {

// The TensorFlow Device dialect.
//

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

namespace tensorflow {
namespace tf2xla {
namespace v2 {

// 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

// CHECK-NEXT: return
// CHECK: func{{.*}}dialect = "x"
// CHECK-NEXT: x.a
// CHECK: func{{.*}}dialect = "y"
// CHECK-NEXT: y.a
// CHECK: func{{.*}}dialect = "z"
// CHECK-NEXT: z.a
// CHECK: func{{.*}}dialect = "x"
// CHECK-NEXT: x.b
// CHECK: func{{.*}}dialect = "y"
// CHECK-NEXT: y.b
// CHECK: func{{.*}}dialect = "z"
// CHECK-NEXT: z.b
// CHECK: func{{.*}}dialect = "x"
// CHECK-NEXT: x.c

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

#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