harfbuzz/src/hb-repacker.hh

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/*
* Copyright © 2020 Google, Inc.
*
* This is part of HarfBuzz, a text shaping library.
*
* Permission is hereby granted, without written agreement and without
* license or royalty fees, to use, copy, modify, and distribute this
* software and its documentation for any purpose, provided that the
* above copyright notice and the following two paragraphs appear in
* all copies of this software.
*
* IN NO EVENT SHALL THE COPYRIGHT HOLDER BE LIABLE TO ANY PARTY FOR
* DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES
* ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN
* IF THE COPYRIGHT HOLDER HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH
* DAMAGE.
*
* THE COPYRIGHT HOLDER SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING,
* BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
* FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS
* ON AN "AS IS" BASIS, AND THE COPYRIGHT HOLDER HAS NO OBLIGATION TO
* PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.
*
* Google Author(s): Garret Rieger
*/
#ifndef HB_REPACKER_HH
#define HB_REPACKER_HH
#include "hb-open-type.hh"
#include "hb-map.hh"
#include "hb-priority-queue.hh"
#include "hb-serialize.hh"
#include "hb-vector.hh"
struct graph_t
{
// TODO(garretrieger): add an error tracking system similar to what serialize_context_t
// does.
/*
* A topological sorting of an object graph. Ordered
* in reverse serialization order (first object in the
* serialization is at the end of the list). This matches
* the 'packed' object stack used internally in the
* serializer
*/
graph_t (const hb_vector_t<hb_serialize_context_t::object_t *>& objects)
{
bool removed_nil = false;
for (unsigned i = 0; i < objects.length; i++)
{
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// TODO(grieger): check all links point to valid objects.
// If this graph came from a serialization buffer object 0 is the
// nil object. We don't need it for our purposes here so drop it.
if (i == 0 && !objects[i])
{
removed_nil = true;
continue;
}
auto* copy = objects_.push (*objects[i]);
if (!removed_nil) continue;
for (unsigned i = 0; i < copy->links.length; i++)
// Fix indices to account for removed nil object.
copy->links[i].objidx--;
}
}
~graph_t ()
{
objects_.fini_deep ();
}
/*
* serialize graph into the provided serialization buffer.
*/
void serialize (hb_serialize_context_t* c)
{
c->start_serialize<void> ();
for (unsigned i = 0; i < objects_.length; i++) {
c->push ();
size_t size = objects_[i].tail - objects_[i].head;
char* start = c->allocate_size <char> (size);
if (!start) return;
memcpy (start, objects_[i].head, size);
for (const auto& link : objects_[i].links)
serialize_link (link, start, c);
c->pop_pack (false);
}
c->end_serialize ();
}
/*
* Generates a new topological sorting of graph using Kahn's
* algorithm: https://en.wikipedia.org/wiki/Topological_sorting#Algorithms
*/
void sort_kahn ()
{
if (objects_.length <= 1) {
// Graph of 1 or less doesn't need sorting.
return;
}
hb_vector_t<unsigned> queue;
hb_vector_t<hb_serialize_context_t::object_t> sorted_graph;
hb_vector_t<unsigned> id_map;
id_map.resize (objects_.length);
hb_vector_t<unsigned> edge_count;
incoming_edge_count (&edge_count);
// Object graphs are in reverse order, the first object is at the end
// of the vector. Since the graph is topologically sorted it's safe to
// assume the first object has no incoming edges.
queue.push (objects_.length - 1);
int new_id = objects_.length - 1;
while (queue.length)
{
unsigned next_id = queue[0];
queue.remove(0);
hb_serialize_context_t::object_t& next = objects_[next_id];
sorted_graph.push (next);
id_map[next_id] = new_id--;
for (const auto& link : next.links) {
// TODO(garretrieger): sort children from smallest to largest
edge_count[link.objidx] -= 1;
if (!edge_count[link.objidx])
queue.push (link.objidx);
}
}
if (new_id != -1)
{
// Graph is not fully connected, there are unsorted objects.
// TODO(garretrieger): handle this.
assert (false);
}
remap_obj_indices (id_map, &sorted_graph);
sorted_graph.as_array ().reverse ();
objects_ = sorted_graph;
sorted_graph.fini_deep ();
}
/*
* Generates a new topological sorting of graph ordered by the shortest
* distance to each node.
*/
void sort_shortest_distance ()
{
if (objects_.length <= 1) {
// Graph of 1 or less doesn't need sorting.
return;
}
hb_vector_t<int64_t> distance_to;
compute_distances (&distance_to);
hb_priority_queue_t queue;
hb_vector_t<hb_serialize_context_t::object_t> sorted_graph;
hb_vector_t<unsigned> id_map;
id_map.resize (objects_.length);
hb_vector_t<unsigned> edge_count;
incoming_edge_count (&edge_count);
// Object graphs are in reverse order, the first object is at the end
// of the vector. Since the graph is topologically sorted it's safe to
// assume the first object has no incoming edges.
queue.insert (objects_.length - 1, add_order(distance_to[objects_.length - 1], 0));
int new_id = objects_.length - 1;
unsigned order = 1;
while (!queue.is_empty ())
{
unsigned next_id = queue.extract_minimum().first;
hb_serialize_context_t::object_t& next = objects_[next_id];
sorted_graph.push (next);
id_map[next_id] = new_id--;
for (const auto& link : next.links) {
edge_count[link.objidx] -= 1;
if (!edge_count[link.objidx])
// Add the order that the links were encountered to the priority.
// This ensures that ties between priorities objects are broken in a consistent
// way. More specifically this is set up so that if a set of objects have the same
// distance they'll be added to the topolical order in the order that they are
// referenced from the parent object.
queue.insert (link.objidx, add_order(distance_to[link.objidx], order++));
}
}
if (new_id != -1)
{
// Graph is not fully connected, there are unsorted objects.
// TODO(garretrieger): handle this.
assert (false);
}
remap_obj_indices (id_map, &sorted_graph);
sorted_graph.as_array ().reverse ();
objects_ = sorted_graph;
sorted_graph.fini_deep ();
}
/*
* Will any offsets overflow on graph when it's serialized?
*/
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bool will_overflow ()
{
hb_vector_t<unsigned> start_positions;
start_positions.resize (objects_.length);
hb_vector_t<unsigned> end_positions;
end_positions.resize (objects_.length);
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unsigned current_pos = 0;
for (int i = objects_.length - 1; i >= 0; i--)
{
start_positions[i] = current_pos;
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current_pos += objects_[i].tail - objects_[i].head;
end_positions[i] = current_pos;
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}
for (unsigned parent_idx = 0; parent_idx < objects_.length; parent_idx++)
{
for (const auto& link : objects_[parent_idx].links)
{
int64_t offset = compute_offset (parent_idx,
link,
start_positions,
end_positions);
if (!is_valid_offset (offset, link)) return true;
}
}
return false;
}
private:
int64_t add_order (int64_t distance, unsigned order)
{
return (distance << 24) | (0x00FFFFFF & order);
}
/*
* Finds the distance too each object in the graph
* from the initial node.
*/
void compute_distances (hb_vector_t<int64_t>* distance_to)
{
// Uses Dijkstra's algorithm to find all of the shortest distances.
// https://en.wikipedia.org/wiki/Dijkstra%27s_algorithm
//
// Implementation Note:
// Since our priority queue doesn't support fast priority decreases
// we instead just add new entries into the queue when a priority changes.
// Redundant ones are filtered out later on by the visited set.
// According to https://www3.cs.stonybrook.edu/~rezaul/papers/TR-07-54.pdf
// for practical performance this is faster then using a more advanced queue
// (such as a fibonaacci queue) with a fast decrease priority.
distance_to->resize (0);
distance_to->resize (objects_.length);
for (unsigned i = 0; i < objects_.length; i++)
{
if (i == objects_.length - 1)
(*distance_to)[i] = 0;
else
(*distance_to)[i] = hb_int_max (int64_t);
}
hb_priority_queue_t queue;
queue.insert (objects_.length - 1, 0);
hb_set_t visited;
while (!queue.is_empty ())
{
unsigned next_idx = queue.extract_minimum ().first;
if (visited.has (next_idx)) continue;
const auto& next = objects_[next_idx];
int64_t next_distance = (*distance_to)[next_idx];
visited.add (next_idx);
for (const auto& link : next.links)
{
if (visited.has (link.objidx)) continue;
const auto& child = objects_[link.objidx];
int64_t child_weight = child.tail - child.head +
(!link.is_wide ? (1 << 16) : ((int64_t) 1 << 32));
int64_t child_distance = next_distance + child_weight;
if (child_distance < (*distance_to)[link.objidx])
{
(*distance_to)[link.objidx] = child_distance;
queue.insert (link.objidx, child_distance);
}
}
}
// TODO(garretrieger): Handle this. If anything is left, part of the graph is disconnected.
assert (queue.is_empty ());
}
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int64_t compute_offset (
unsigned parent_idx,
const hb_serialize_context_t::object_t::link_t& link,
const hb_vector_t<unsigned>& start_positions,
const hb_vector_t<unsigned>& end_positions)
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{
unsigned child_idx = link.objidx;
int64_t offset = 0;
switch ((hb_serialize_context_t::whence_t) link.whence) {
case hb_serialize_context_t::whence_t::Head:
offset = start_positions[child_idx] - start_positions[parent_idx]; break;
case hb_serialize_context_t::whence_t::Tail:
offset = start_positions[child_idx] - end_positions[parent_idx]; break;
case hb_serialize_context_t::whence_t::Absolute:
offset = start_positions[child_idx]; break;
}
assert (offset >= link.bias);
offset -= link.bias;
return offset;
}
bool is_valid_offset (int64_t offset,
const hb_serialize_context_t::object_t::link_t& link)
{
if (link.is_signed)
{
if (link.is_wide)
return offset >= -((int64_t) 1 << 31) && offset < ((int64_t) 1 << 31);
else
return offset >= -(1 << 15) && offset < (1 << 15);
}
else
{
if (link.is_wide)
return offset >= 0 && offset < ((int64_t) 1 << 32);
else
return offset >= 0 && offset < (1 << 16);
}
}
/*
* Updates all objidx's in all links using the provided mapping.
*/
void remap_obj_indices (const hb_vector_t<unsigned>& id_map,
hb_vector_t<hb_serialize_context_t::object_t>* sorted_graph)
{
for (unsigned i = 0; i < sorted_graph->length; i++)
{
for (unsigned j = 0; j < (*sorted_graph)[i].links.length; j++)
{
auto& link = (*sorted_graph)[i].links[j];
link.objidx = id_map[link.objidx];
}
}
}
/*
* Creates a map from objid to # of incoming edges.
*/
void incoming_edge_count (hb_vector_t<unsigned>* out)
{
out->resize (0);
out->resize (objects_.length);
for (const auto& o : objects_)
{
for (const auto& l : o.links)
{
(*out)[l.objidx] += 1;
}
}
}
template <typename O> void
serialize_link_of_type (const hb_serialize_context_t::object_t::link_t& link,
char* head,
hb_serialize_context_t* c)
{
OT::Offset<O>* offset = reinterpret_cast<OT::Offset<O>*> (head + link.position);
*offset = 0;
c->add_link (*offset,
// serializer has an extra nil object at the start of the
// object array. So all id's are +1 of what our id's are.
link.objidx + 1,
(hb_serialize_context_t::whence_t) link.whence,
link.bias);
}
void serialize_link (const hb_serialize_context_t::object_t::link_t& link,
char* head,
hb_serialize_context_t* c)
{
if (link.is_wide)
{
if (link.is_signed)
{
serialize_link_of_type<OT::HBINT32> (link, head, c);
} else {
serialize_link_of_type<OT::HBUINT32> (link, head, c);
}
} else {
if (link.is_signed)
{
serialize_link_of_type<OT::HBINT16> (link, head, c);
} else {
serialize_link_of_type<OT::HBUINT16> (link, head, c);
}
}
}
public:
hb_vector_t<hb_serialize_context_t::object_t> objects_;
};
/*
* Re-serialize the provided object graph into the serialization context
* using BFS (Breadth First Search) to produce the topological ordering.
*/
inline void
hb_resolve_overflows (const hb_vector_t<hb_serialize_context_t::object_t *>& packed,
hb_serialize_context_t* c) {
graph_t sorted_graph (packed);
sorted_graph.sort_kahn ();
if (sorted_graph.will_overflow ()) {
sorted_graph.sort_shortest_distance ();
// TODO(garretrieger): try additional offset resolution strategies
// - Dijkstra sort of weighted graph.
// - Promotion to extension lookups.
// - Table duplication.
// - Table splitting.
}
sorted_graph.serialize (c);
}
#endif /* HB_REPACKER_HH */