for (const auto& attr : state->attributes)
    if (attr.getName().strref() == "n")
      if (auto n_attr = mlir::dyn_cast<IntegerAttr>(attr.getValue()))
        *n = n_attr.getInt();

  if (*n < 2)
    return parser->emitError(loc) << "expects 'n' to be at least 2, got " << *n;

  if (replicated_inputs.empty() && packed_inputs.empty()) return success();

  void runOnOperation() override {
    MLIRContext *context = &getContext();
    ModuleOp module_op = getOperation();
    SmallVector<func::FuncOp, 4> original_func;
    for (auto func_op : module_op.getOps<func::FuncOp>()) {
      original_func.push_back(func_op);
    }
    for (auto func_op : original_func) {
      std::optional<llvm::StringMap<FunctionMetadata>> metadatas =
          GetFunctionMetadatas(func_op);

      bool use_mhlo_const = false) {
    auto module_op = parseSourceString<ModuleOp>(program, ctx_.get());
    CHECK(module_op);
    auto func_op = llvm::dyn_cast<func::FuncOp>(
        *module_op->getBodyRegion().getOps().begin());
    if (!func_op) {
      return absl::InternalError("Input MLIR must have only 1 func");
    }
    if (arguments.size() != func_op.getNumArguments()) {

	}
	if rx != nil && matched == 0 {
		return fmt.Errorf("no matches found for regexp: %s", rx)
	}
	return nil
}

// GetDOT returns a graph suitable for dot processing along with some
// configuration information.
func GetDOT(rpt *Report) (*graph.Graph, *graph.DotConfig) {
	g, origCount, droppedNodes, droppedEdges := rpt.newTrimmedGraph()
	rpt.selectOutputUnit(g)

    SmallVector<int32_t, 4> perm;
    SmallVector<int64_t, 4> output_shape;
    for (int i = 0; i < num_dimensions; ++i) {
      perm.push_back(perm_tensor.getValues<IntegerAttr>()[i].getInt());
      output_shape.push_back(input_shape[perm[i]]);

      // Check that the derived output shape matches the static shape.
      assert(!output_type.hasStaticShape() ||

    @Deprecated("Use layout.buildDirectory instead", ReplaceWith("layout.buildDirectory.get().asFile"))
    override fun getBuildDir(): File =
        @Suppress("DEPRECATION")
        delegate.buildDir

    override fun getAnt(): AntBuilder =
        delegate.ant

    override fun getVersion(): Any =
        delegate.version

    override fun getRootProject(): Project =
        delegate.rootProject

          new_results.push_back(element_op.getOut());
        }
      }
    }
    for (auto res : llvm::zip(op->getResults(), new_results)) {
      auto casted = builder.create<CastOp>(
          op->getLoc(), std::get<0>(res).getType(), std::get<1>(res));
      std::get<0>(res).replaceAllUsesWith(casted.getOut());
    }

    // Copy all the unregisted attributes to the new op.

		}

		// If this not a WORM enabled bucket, we should return right here.
		return mode, retainDate, legalHold, ErrNone
	}

	opts, err := getOpts(ctx, rq, bucket, object)
	if err != nil {
		return mode, retainDate, legalHold, toAPIErrorCode(ctx, err)
	}

	replica := rq.Header.Get(xhttp.AmzBucketReplicationStatus) == replication.Replica.String()

// does the same thing for `Ts`.
template <typename T, typename... Ts>
void DuplicateShapeDeterminingConstants(func::FuncOp func_op) {
  for (auto op : func_op.getOps<typename T::OpType>()) {
    RecursivelyDuplicateConstantsForOperands(
        GetOperands(*op, T::OperandIndices()));
  }

  // Do the same thing for the rest of `Ts`.
  if constexpr (sizeof...(Ts) != 0) {

    q_op->replaceAllUsesWith(new_qcast);
    return success();
  }
};

bool PrepareQuantizePass::ContainsQuantizeOps(func::FuncOp func) {
  for (const auto& op : func.getOps()) {
    if (llvm::isa<quantfork::DequantizeCastOp>(op)) return true;
  }
  return false;
}

using PrepareQuantStats =
    quant::ConvertStatsToQDQs<quantfork::QuantizeCastOp,