using ::tensorflow::quantization::PyFunctionLibrary;

bool IsControlFlowV1Op(Operation* op) {
  return mlir::isa<mlir::tf_executor::SwitchOp, mlir::tf_executor::MergeOp,
                   mlir::tf_executor::EnterOp, mlir::tf_executor::ExitOp,
                   mlir::tf_executor::NextIterationSinkOp,
                   mlir::tf_executor::NextIterationSourceOp>(op);
}

mlir::LogicalResult IsValidGraph(mlir::ModuleOp module) {

    tbl_outs = [
        (
            ["-gen-op-decls"],
            "ir/tf_executor.h.inc",
        ),
        (
            ["-gen-op-defs"],
            "ir/tf_executor.cc.inc",
        ),
        (
            [
                "-gen-dialect-doc",
                "-dialect=tf_executor",
            ],
            "g3doc/tf_executor.md",
        ),
    ],
    tblgen = "@llvm-project//mlir:mlir-tblgen",

        // `tf.TPUPartitionedInput`. For example, we have the follow pseudocode:
        // %0 = tf_executor.island wraps "tf.OpA" (){_replication_info = 'c'}
        // %1 = tf_executor.island wraps "tf.Identity(%0)
        // %2 = tf_executor.island wraps "tf.TPUReplicatedInput"(%1)

        if (!isa<TF::TPUReplicatedInputOp, TF::TPUPartitionedInputOp,

#include "mlir/Support/DebugStringHelper.h"  // from @llvm-project
#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_attributes.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_executor.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_types.h"
#include "tensorflow/compiler/mlir/tensorflow/utils/convert_tensor.h"

#include "mlir/Support/LLVM.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_executor.h"
#include "tensorflow/compiler/mlir/tensorflow/transforms/passes.h"
#include "tensorflow/core/platform/logging.h"

namespace mlir {
namespace tf_executor {

namespace {

//===----------------------------------------------------------------------===//
// Analysis

  // like a TF v2 module. We can then run the usual pipeline on this nested
  // module. Afterward we inline back in the parent module and delete the
  // nested one.
  pm.addPass(mlir::tf_executor::CreateTFExecutorTPUV1IslandCoarseningPass());
  pm.addPass(mlir::tf_executor::CreateTFExecutorTPUV1IslandOutliningPass());
}

// Run the TF XLA Bridge based on the input pipeline, which can be either TPU
// bridge pipeline or non TPU bridge pipeline.

  pm.addNestedPass<mlir::func::FuncOp>(
      mlir::TF::CreateDropWhileShapeInvariantPass());
  pm.addNestedPass<mlir::func::FuncOp>(
      mlir::tf_executor::CreateTFExecutorGraphPruningPass());
  pm.addNestedPass<mlir::func::FuncOp>(
      mlir::tf_executor::CreateTFExecutorIslandCoarseningPass());
  pm.addPass(mlir::TF::CreateTFFunctionalControlFlowToRegions());
  pm.addPass(mlir::createInlinerPass());

  while (Operation* op = value.getDefiningOp()) {
    int res_index = mlir::cast<OpResult>(value).getResultNumber();
    if (auto graph = dyn_cast<tf_executor::GraphOp>(op)) {
      value = graph.GetFetch().getOperand(res_index);
    } else if (auto island = dyn_cast<tf_executor::IslandOp>(op)) {
      // Control output is generated by the IslandOp, not the yield in
      // in the Island body.

#include "mlir/Tools/mlir-translate/Translation.h"  // from @llvm-project
#include "stablehlo/dialect/StablehloOps.h"  // from @stablehlo
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_executor.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/translate/mlir_roundtrip_flags.h"
#include "tensorflow/compiler/mlir/tensorflow/translate/tf_mlir_translate_cl.h"

#include "mlir/Dialect/Shape/IR/Shape.h"  // from @llvm-project
#include "mlir/IR/OperationSupport.h"  // from @llvm-project
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_device.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_executor.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/translate/export_graphdef.h"
#include "tensorflow/compiler/mlir/tensorflow/translate/import_model.h"