variant.getOutgoing().artifacts(
            getSourceSet().getAllSource().getSourceDirectories().getElements().flatMap(e -> project.provider(() -> e)),
            artifact -> artifact.setType(ArtifactTypeDefinition.DIRECTORY_TYPE)
        );
    }

    private Configuration dependencyScope(String kind, String suffix, boolean create, boolean warnOnDuplicate) {

          mlir::tf_saved_model::GlobalTensorOp>(func, i, symbol_table);
      if (global_tensor) {
        auto old_type = arg.getType();
        auto new_type =
            mlir::tf_saved_model::GetBoundInputArgTypeFor(global_tensor);
        arg.setType(new_type);
        if (global_tensor.getIsMutable()) {
          auto arg_with_original_type = builder.create<mlir::TF::CastOp>(

	// signal to the symtab() phase that it needs to be grouped in with
	// other similar symbols (gcdata, etc); the dodata() phase will
	// eventually switch the type back to SRODATA.
	inlTreeSym.SetType(sym.SGOFUNC)
	ldr.SetAttrReachable(its, true)
	ldr.SetSymAlign(its, 4) // it has 32-bit fields
	ninl := fi.NumInlTree()
	for i := 0; i < int(ninl); i++ {
		call := fi.InlTree(i)

        if (!attribute) {
          attribute =
              compose_func.getArgAttr(arg.index(), kAttrArgumentDefaultAttr);
        }
        if (!attribute && attr_name.getValue() == "out_type") {
          auto type = op->getResult(0).getType();
          if (mlir::isa<TensorType>(type)) {
            type = mlir::cast<TensorType>(type).getElementType();
          }
          attribute = TypeAttr::get(type);
        }

  sources.reserve(output_tensors.size());
  for (const TapeTensor& output_tensor : output_tensors) {
    // Ownership of `aid` transferred to CallBackwardFunction below.
    Gradient* aid;
    if (output_tensor.GetDType() == tensorflow::DT_VARIANT) {
      // Note: Needs to be zeros rather than ones since there's currently no
      // ones_like for variants.
      aid = output_tensor.ZerosLike();
    } else {

        return generatorsByLanguage.get(language);
    }

    @Option(option = "type", description = "Set the type of project to generate.")
    public void setType(String type) {
        this.type = type;
    }

    @OptionValues("type")
    public List<String> getAvailableBuildTypes() {
        return getProjectLayoutRegistry().getAllTypes();
    }

    /**

  handle_ = other.handle_;
  handle_->Ref();
}
TapeTensor::~TapeTensor() { handle_->Unref(); }

int64_t TapeTensor::GetID() const { return ToId(handle_); }

tensorflow::DataType TapeTensor::GetDType() const {
  return handle_->DataType();
}
AbstractTensorHandle* TapeTensor::GetHandle() const { return handle_; }

AbstractTensorHandle* TapeTensor::ZerosLike() const { return nullptr; }

class TapeVSpace

        return ai;
    }

    private ProxyInfo proxyInfo(ArtifactRepository repository) {
        ProxyInfo proxyInfo = new ProxyInfo();
        proxyInfo.setHost(repository.getProxy().getHost());
        proxyInfo.setType(repository.getProxy().getProtocol());
        proxyInfo.setPort(repository.getProxy().getPort());
        proxyInfo.setNonProxyHosts(repository.getProxy().getNonProxyHosts());

		// compare against the itab address directly?
		var eqtype ir.Node
		tab := ir.NewUnaryExpr(base.Pos, ir.OITAB, l)
		rtyp := reflectdata.CompareRType(base.Pos, n)
		if l.Type().IsEmptyInterface() {
			tab.SetType(types.NewPtr(types.Types[types.TUINT8]))
			tab.SetTypecheck(1)
			eqtype = ir.NewBinaryExpr(base.Pos, eq, tab, rtyp)
		} else {
			nonnil := ir.NewBinaryExpr(base.Pos, brcom(eq), typecheck.NodNil(), tab)

    //                          String nonProxyHosts )
    //    {
    //        ProxyInfo proxyInfo = new ProxyInfo();
    //        proxyInfo.setHost( host );
    //        proxyInfo.setType( protocol );
    //        proxyInfo.setPort( port );
    //        proxyInfo.setNonProxyHosts( nonProxyHosts );
    //        proxyInfo.setUserName( username );
    //        proxyInfo.setPassword( password );
    //