// 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

def TfExecutor_Dialect : Dialect {
  let name = "tf_executor";

  let description = [{
    The TensorFlow Executor dialect.

    This dialect models the TensorFlow executor semantics and can represent
    arbitrary TensorFlow graphs. As such it follows the existing execution model
    that includes deadness propagation, concurrent semantics, and control
    dependencies.

  auto walk_result = func_op->walk([&](Operation* op) {
    if (!tensorflow::tf2xla::internal::IsInBridgeAcceptableDialects(op)) {
      std::string error = "op is in dialect " +
                          op->getDialect()->getNamespace().str() +
                          " which is not an accepted dialect";
      op->emitError() << error;
      return WalkResult::interrupt();
    }

    if (IsTfDeviceClusterFuncOp(op)) {
      std::string error =

  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`.

  let summary = "Legalize TensorFlow variables to TensorFlow Lite dialect.";
  let constructor = "CreateLegalizeVariablesPass()";
  let dependentDialects = ["TFL::TensorFlowLiteDialect"];
}

def LiftTfliteFlexOpsPass : Pass<"tfl-lift-tflite-flex-ops", "mlir::func::FuncOp"> {
  let summary = "Lifts TFLite Custom ops into TF dialect operations.";
  let constructor = "CreateLiftTfliteFlexOpsPass()";

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

// This file defines the attributes used in the TensorFlow dialect.

#ifndef TENSORFLOW_COMPILER_MLIR_TENSORFLOW_IR_TF_ATTRIBUTES_H_
#define TENSORFLOW_COMPILER_MLIR_TENSORFLOW_IR_TF_ATTRIBUTES_H_

#include "tensorflow/core/ir/types/dialect.h"

namespace mlir {
namespace TF {

// This all moved under tensorflow/core/ir/types and these using declaration are

limitations under the License.
==============================================================================*/

include "mlir/IR/OpBase.td"
include "mlir/IR/PatternBase.td"
include "mlir/Dialect/Func/IR/FuncOps.td"
include "mlir/Dialect/Arith/IR/ArithOps.td"
include "tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.td"
include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td"

limitations under the License.
==============================================================================*/

include "mlir/IR/OpBase.td"
include "mlir/IR/PatternBase.td"
include "mlir/Dialect/Func/IR/FuncOps.td"
include "mlir/Dialect/Arith/IR/ArithOps.td"
include "tensorflow/compiler/mlir/quantization/common/attrs_and_constraints.td"
include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.td"

#include "mlir/IR/BuiltinAttributes.h"  // from @llvm-project
#include "mlir/Transforms/DialectConversion.h"  // from @llvm-project
#include "stablehlo/dialect/StablehloOps.h"  // from @stablehlo

namespace mlir::quant::stablehlo {

// Checks if an op is from StableHLO dialect.
inline bool IsStablehloOp(Operation* op) {
  return op->getDialect()->getNamespace() ==
         mlir::stablehlo::StablehloDialect::getDialectNamespace();
}

func.func @testNotTfDialect(%arg0: tensor<1x32x10x32xi32>, %arg1: tensor<32xi32>) -> tensor<1x32x10x32xi32> {
 // expected-error@below {{op is in dialect chlo not in tf functional dialect}}
  %0 = "chlo.broadcast_add"(%arg0, %arg1) {broadcast_dimensions = array<i64: 3>} : (tensor<1x32x10x32xi32>, tensor<32xi32>) -> tensor<1x32x10x32xi32>
  func.return %0 : tensor<1x32x10x32xi32>
}

// -----