}
};

}  // namespace

MlrtDialect::MlrtDialect(mlir::MLIRContext *context)
    : mlir::Dialect(/*name=*/"mlrt", context,
                    mlir::TypeID::get<MlrtDialect>()) {
  addTypes<FutureType>();
  addTypes<PromiseType>();
  addTypes<AsyncHandleType>();
  addInterfaces<MlrtInlinerInterface>();

  addOperations<
#define GET_OP_LIST
#include "tensorflow/compiler/mlir/tfrt/ir/mlrt/mlrt_ops.cpp.inc"
      >();
}

namespace tfrt {
namespace fallback {

FallbackDialect::FallbackDialect(MLIRContext *context)
    : Dialect(/*name=*/"tfrt_fallback", context,
              TypeID::get<FallbackDialect>()) {
  addTypes<TFTensorType, TFAllocatorType>();

  addOperations<
#define GET_OP_LIST
#include "tensorflow/compiler/mlir/tfrt/ir/tfrt_fallback.cpp.inc"
      >();
}

/// Parse a type registered to this dialect.

};

}  // namespace

TensorflowMlrtDialect::TensorflowMlrtDialect(mlir::MLIRContext *context)
    : mlir::Dialect(/*name=*/"tf_mlrt", context,
                    mlir::TypeID::get<TensorflowMlrtDialect>()) {
  addTypes<TFTensorType, TFDeviceType>();
  addInterfaces<TensorflowMlrtInlinerInterface>();

  addOperations<
#define GET_OP_LIST
#include "tensorflow/compiler/mlir/tfrt/ir/mlrt/tf_mlrt_ops.cpp.inc"
      >();

#define GET_OP_LIST
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_executor.cc.inc"
      >();

  addInterfaces<TensorFlowExecutorInlinerInterface,
                TensorFlowExecutorDialectFoldInterface>();

  addTypes<ControlType, TokenType>();
}

Type TensorFlowExecutorDialect::parseType(DialectAsmParser &parser) const {
  StringRef data_type;
  if (parser.parseKeyword(&data_type)) return Type();

  // Create the TF op
  const std::string tf_op_full_name = absl::StrCat("tf.", node_def.op());
  mlir::OperationState op_state(loc, tf_op_full_name);
  op_state.addOperands(func.getArguments());
  op_state.addTypes(output_tys);
  op_state.addAttributes(attrs);
  mlir::Operation* tf_op = op_builder.create(op_state);
  op_builder.create<mlir::func::ReturnOp>(loc, tf_op->getResults());

  // Run the decompose passes on the module

    llvm::SmallVector<mlir::Type, 4> output_tys;
    for (int i = 0; i < custom_op.getNumResults(); i++) {
      output_tys.push_back(custom_op.getType(i));
    }
    op_state.addTypes(output_tys);
    op_state.addAttributes(attr);
    auto stablehlo_op = builder.create(op_state);
    custom_op.replaceAllUsesWith(stablehlo_op);
    custom_op.erase();
  });
}

    const std::string tf_op_full_name = llvm::Twine("tf.", tf_op_name).str();

    // Create the TF op
    OperationState op_state(op.getLoc(), tf_op_full_name);
    op_state.addOperands(op.getOperands());
    op_state.addTypes(op.getResultTypes());

    SmallVector<NamedAttribute, 2> attrs;
    std::string parsed_op_name;
    tensorflow::NodeDef node_def;
    if (failed(ParseCustomOption(op.getCustomOption().getValue(), op.getLoc(),

    ) {
        List<TypeSpec> interceptorTypeSpecs = generateInterceptorClasses(requestsClassGroup, onFailure);

        return builder -> builder
            .addModifiers(Modifier.PUBLIC)
            .addTypes(interceptorTypeSpecs);
    }

    @SuppressWarnings("ReturnValueIgnored")

  DCHECK_GE(num_regions, 1);
  for (int i = 0; i < num_regions; ++i) {
    Region* region = state.addRegion();
    region->push_back(new Block);
  }
  state.addTypes(output_types);
}

Block& ParallelExecuteOp::GetRegionBlockWithIndex(unsigned index) {
  return getOperation()->getRegion(index).front();
}

Operation::result_range ParallelExecuteOp::GetRegionOutputs(

    bool WrapsSingleOp();
  }];

  let builders = [
    OpBuilder<(ins "StringAttr":$device, "TypeRange":$result_types),
    [{
      $_state.addAttribute("device", device);
      $_state.addTypes(result_types);
      $_state.addRegion();
    }]>
  ];

  let hasCanonicalizer = 1;
}

def TfDevice_ReturnOp : TfDevice_Op<"return", [Pure, ReturnLike, Terminator]> {
  let summary = [{