BlockArgument block_arg) {
  assert(block_arg.getOwner() == &GetBody());

  unsigned arg_number = block_arg.getArgNumber();
  unsigned num_replicated_args = GetNumReplicatedBlockArguments();
  int32_t num_replicas = getNAttr().getInt();
  MutableArrayRef<OpOperand> operands = getOperation()->getOpOperands();

  // All replicated arguments are before packed arguments so return replicated

LogicalResult SmuggleOp(Operation* op, PatternRewriter& rewriter) {
  auto call_target =
      rewriter.getNamedAttr("call_target_name", op->getName().getIdentifier());
  SmallVector<NamedAttribute> attrs{op->getAttrs()};
  attrs.push_back(call_target);
  auto custom_call = rewriter.create<mlir::stablehlo::CustomCallOp>(
      op->getLoc(), op->getResultTypes(), op->getOperands(), attrs);
  rewriter.replaceOp(op, custom_call.getResults());

  auto spec = std::make_unique<OpQuantSpec>();
  if (auto call_op = dyn_cast<TF::PartitionedCallOp>(op)) {
    StringRef function_name =
        mlir::cast<FlatSymbolRefAttr>(call_op.getFAttr()).getValue();
    if (!function_name.starts_with("composite_")) {
      return spec;
    }
    if (function_name.contains("depthwise_conv2d")) {
      spec->coeff_op_quant_dim[1] = 3;

}

impl::NodeMatcherProperties impl::Attr(std::pair<string, AttrValue> attr) {
  impl::NodeMatcherProperties props;
  props.set_attr(std::move(attr));
  return props;
}

impl::NodeMatcherProperties impl::Attr(string name) {
  impl::NodeMatcherProperties props;
  props.set_attr({std::move(name), std::nullopt});
  return props;
}

NodeMatcherProperties ConstantValue(

		TableConvertor: printerstorage.TableConvertor{TableGenerator: printers.NewTableGenerator().With(printersinternal.AddHandlers)},
	}
	options := &generic.StoreOptions{RESTOptions: optsGetter, AttrFunc: podschedulingcontext.GetAttrs}
	if err := store.CompleteWithOptions(options); err != nil {
		return nil, nil, err
	}

	statusStore := *store
	statusStore.UpdateStrategy = podschedulingcontext.StatusStrategy

  }

  LogicalResult matchAndRewrite(TF::PartitionedCallOp op,
                                PatternRewriter& rewriter) const override {
    const auto f_attr = mlir::dyn_cast<FlatSymbolRefAttr>(op.getFAttr());
    StringRef function_name = f_attr.getValue();
    if (!function_name.starts_with(kDequantizeFunctionName)) return failure();

    llvm::SmallVector<Operation*> users(op->getUsers().begin(),

  SymbolTableCollection symbol_table;
  OpBuilder builder(module.getContext());

  OwningOpRef<ModuleOp> pruned =
      builder.create<ModuleOp>(module->getLoc());
  (*pruned)->setAttrs(module->getAttrs());
  builder.setInsertionPointToEnd(pruned->getBody());

  llvm::SmallDenseSet<func::FuncOp> added;
  for (const llvm::StringRef function_name : function_names) {
    auto func =

                                PatternRewriter& rewriter) const override {
    auto input_op = op.getArg().getDefiningOp();
    if (auto q = llvm::dyn_cast_or_null<quantfork::QuantizeCastOp>(input_op)) {
      if (!q->getAttr(kVolatileOpAttrName)) return failure();

      // If the quantize op is a requantize op, it is being used in other scale
      // adjustments and should be kept. Instead, move dequantize op before the

    if operation_id in operation_ids:
        message = (
            f"Duplicate Operation ID {operation_id} for function "
            + f"{route.endpoint.__name__}"
        )
        file_name = getattr(route.endpoint, "__globals__", {}).get("__file__")
        if file_name:
            message += f" at {file_name}"
        warnings.warn(message, stacklevel=1)
    operation_ids.add(operation_id)

    auto *new_ewise_op =
        rewriter.create(op->getLoc(), op->getName().getIdentifier(),
                        {tpose_arg1.getOperand(0), tpose_arg2.getOperand(0)},
                        new_out_type, op->getAttrs());

    // Apply original tranpose to output of ewise op.
    auto out_tpose_op = rewriter.create<TFL::TransposeOp>(
        new_ewise_op->getLoc(), op->getResult(0).getType(),