if v < 0 {
		return false
	}
	if (v & 0xFFF) == 0 {
		v >>= 12
	}
	return v <= 0xFFF
}

// setPos sets the position of v to pos, then returns true.
// Useful for setting the result of a rewrite's position to
// something other than the default.
func setPos(v *Value, pos src.XPos) bool {
	v.Pos = pos
	return true

  && a.Val() == 0
  && c.Val() == 0
  && setPos(v, x.Pos)
  && clobber(x)
  => (MOVOstoreconst [makeValAndOff(0,a.Off())] {s} p0 mem)
(MOVQstoreconst [a] {s} p0 x:(MOVQstoreconst [c] {s} p1 mem))
  && config.useSSE
  && x.Uses == 1
  && sequentialAddresses(p0, p1, int64(a.Off()+8-c.Off()))
  && a.Val() == 0
  && c.Val() == 0
  && setPos(v, x.Pos)
  && clobber(x)

    return CartesianSet.create(sets);
  }

  /**
   * Returns every possible list that can be formed by choosing one element from each of the given
   * sets in order; the "n-ary <a href="http://en.wikipedia.org/wiki/Cartesian_product">Cartesian
   * product</a>" of the sets. For example:
   *
   * <pre>{@code
   * Sets.cartesianProduct(

    return CartesianSet.create(sets);
  }

  /**
   * Returns every possible list that can be formed by choosing one element from each of the given
   * sets in order; the "n-ary <a href="http://en.wikipedia.org/wiki/Cartesian_product">Cartesian
   * product</a>" of the sets. For example:
   *
   * <pre>{@code
   * Sets.cartesianProduct(

          if (TF::TensorListSetItemOp set_op =
                  llvm::dyn_cast<TF::TensorListSetItemOp>(use.getOwner())) {
            element_shape = rewriter.create<TF::ShapeOp>(
                op.getLoc(),
                tensorflow::GetTypeFromTFTensorShape({-1}, shape_dtype),
                set_op.getItem());
            element_shape_acquired = true;

func (l *Loader) SymGot(s Sym) int32 {
	if v, ok := l.got[s]; ok {
		return v
	}
	return -1
}

// SetGot sets the GOT offset of symbol i.
func (l *Loader) SetGot(i Sym, v int32) {
	if i >= Sym(len(l.objSyms)) || i == 0 {
		panic("bad symbol for SetGot")
	}
	if v == -1 {
		delete(l.got, i)
	} else {
		l.got[i] = v
	}
}

    bool reuse_existing_functions, FunctionLibraryDefinition* library) {
  // name_in is copied here because name may be modified below if
  // rewrite_subgraph_fn is true.
  string name = name_in;
  call_node_def_.set_op(name);
  call_node_def_.set_name(name);
  call_node_def_.set_device(device_);

  if (rewrite_subgraph_fn) {
    std::vector<OutputTensor> arg_source_tensors(args_by_src_.size());

        if (usePipeline) {
            return updateByIdWithScript(index, id, field, value);
        }
        try {
            final Result result = client.prepareUpdate().setIndex(index).setId(id).setDoc(field, value).execute()
                    .actionGet(ComponentUtil.getFessConfig().getIndexIndexTimeout()).getResult();
            return result == Result.CREATED || result == Result.UPDATED;

  *flib_def.add_function() = std::move(func);
  TF_ASSERT_OK(root.graph()->AddFunctionLibrary(flib_def));
  NodeDef call_node;
  call_node.set_name("fn_call");
  call_node.set_op("Stateful_func");
  Status status;
  Node* call = root.graph()->AddNode(call_node, &status);
  TF_ASSERT_OK(status);

  Output shape = Output(call, 0);
  Output reshape_input =

    EXPECT_FALSE(TF_TensorIsAligned(a));
  }
  TF_DeleteTensor(a);
}

TEST(CAPI, MessageBufferConversion) {
  NodeDef node_in, node_out;
  node_in.set_name("Test name");
  node_in.set_op("Test op");

  TF_Buffer* buffer = TF_NewBuffer();
  TF_CHECK_OK(MessageToBuffer(node_in, buffer));
  TF_CHECK_OK(BufferToMessage(buffer, &node_out));
  TF_DeleteBuffer(buffer);