// tf_device.parallel_execute
//===----------------------------------------------------------------------===//

LogicalResult ParallelExecuteOp::verify() {
  ParallelExecuteOp op = *this;
  const auto& regions = op.getOperation()->getRegions();
  if (regions.empty()) {
    return op.emitOpError() << "must have at least one region.";
  }

  int output_index = 0;
  for (const auto& region_and_index : llvm::enumerate(regions)) {

  explicit ConvertFuncToBfloat16Pass() = default;

 private:
  void runOnOperation() override;
};

void ConvertFuncToBfloat16Pass::runOnOperation() {
  func::FuncOp func_op = getOperation();
  MLIRContext* context = func_op.getContext();
  RewritePatternSet patterns(context);

  BFloat16TypeConverter converter;
  patterns.add<BFloat16TypePattern, BitcastConvertOpPattern>(converter,

          CanonicalizeCompileAndReplicateAttributesPass> {
  void runOnOperation() override;
};

void CanonicalizeCompileAndReplicateAttributesPass::runOnOperation() {
  func::FuncOp func_op = getOperation();
  ModuleOp module_op = func_op->getParentOfType<ModuleOp>();
  mlir::OpBuilder builder(module_op.getContext());

  auto walk_result = func_op->walk([&](mlir::Operation* op) {
    // Convert `_tpu_replicate`.

 public:
  static ::mlir::TypeID resolveTypeID() {
    static ::mlir::SelfOwningTypeID id;
    return id;
  }

 private:
  void runOnOperation() override {
    ModuleOp op = this->getOperation();
    DerivedT& derived = *static_cast<DerivedT*>(this);
    auto& analysis = this->template getAnalysis<AnalysisT>();

    for (auto func : op.getOps<func::FuncOp>())
      if (!func.isExternal())

    registry.insert<TF::TensorFlowDialect>();
  }
  void runOnOperation() override;
};

void DeviceTransformNNAPIPass::runOnOperation() {
  auto func = getOperation();
  auto* ctx = &getContext();
  NNAPIHardware nnapi_hardware;
  RewritePatternSet patterns = nnapi_hardware.GetTransformations(ctx);
  (void)applyPatternsAndFoldGreedily(func, std::move(patterns));
}

 public:
  void runOnOperation() override;
};

void InputMetricsLoweringPass::runOnOperation() {
  bool has_dynamic_op = false;
  Operation* func_op = getOperation();

  func_op->walk([&](Operation* op) {
    auto abstractOp = op->getRegisteredInfo();
    if (!abstractOp) return WalkResult::advance();

    if (mlir::mhlo::IsDynamicPadderOp(abstractOp->getTypeID())) {

      if (failed(layout)) return;

      op->setAttr("layout", layout.value());
    }
  }
};

void InfeedsOpsXlaAdjustLayout::runOnOperation() {
  getOperation().walk(runOnInfeedOp);
}

}  // anonymous namespace

std::unique_ptr<mlir::OperationPass<func::FuncOp>>
CreateInfeedsOpsXlaAdjustLayoutPass() {
  return std::make_unique<InfeedsOpsXlaAdjustLayout>();
}

    : public impl::ConvertLaunchFuncToTFCallPassBase<
          ConvertLaunchFuncToTFCallPass> {
  void runOnOperation() override;
};

void ConvertLaunchFuncToTFCallPass::runOnOperation() {
  ModuleOp module = getOperation();
  module.walk([&](tf_device::LaunchFuncOp launch) {
    OpBuilder builder(launch);
    auto call_op = builder.create<TF::PartitionedCallOp>(
        module.getLoc(), launch.getResultTypes(), launch.getOperands(),

    auto fail = [&](Operation* op, std::string message) {
      op->emitError(message);
      signalPassFailure();
    };

    DenseMap<StringRef, func::FuncOp> entrypoints;
    auto module = getOperation();
    module.walk([&](func::FuncOp op) {
      auto visibility = SymbolTable::getSymbolVisibility(op);
      if (visibility != SymbolTable::Visibility::Public) return;
      entrypoints[op.getSymName()] = op;
    });

					// Ignore context cancelled from webhook metrics
					if !errors.Is(err.Reason, context.Canceled) {
						admissionmetrics.Metrics.ObserveWebhookRejection(ctx, hook.Name, "admit", string(versionedAttr.Attributes.GetOperation()), admissionmetrics.WebhookRejectionCallingWebhookError, int(err.Status.ErrStatus.Code))
					}
				}