intermediate changes

ref:cde9a383711a11544ce7e107a78147fb96cc4029

1 files changed, 220 insertions, 0 deletions

diff --git a/contrib/libs/hyperscan/src/nfagraph/ng_netflow.cpp b/contrib/libs/hyperscan/src/nfagraph/ng_netflow.cpp
new file mode 100644
index 0000000000..780a319f5d
--- /dev/null
+++ b/contrib/libs/hyperscan/src/nfagraph/ng_netflow.cpp
@@ -0,0 +1,220 @@
+/*
+ * Copyright (c) 2015-2017, Intel Corporation
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions are met:
+ *
+ *  * Redistributions of source code must retain the above copyright notice,
+ *    this list of conditions and the following disclaimer.
+ *  * Redistributions in binary form must reproduce the above copyright
+ *    notice, this list of conditions and the following disclaimer in the
+ *    documentation and/or other materials provided with the distribution.
+ *  * Neither the name of Intel Corporation nor the names of its contributors
+ *    may be used to endorse or promote products derived from this software
+ *    without specific prior written permission.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+ * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+ * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
+ * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+ * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+ * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+ * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+ * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+ * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+ * POSSIBILITY OF SUCH DAMAGE.
+ */
+
+/** \file
+ * \brief Network flow (min flow, max cut) algorithms.
+ */
+#include "ng_netflow.h"
+
+#include "ng_holder.h"
+#include "ng_literal_analysis.h"
+#include "ng_util.h"
+#include "ue2common.h"
+#include "util/container.h"
+#include "util/graph_range.h"
+#include "util/graph_small_color_map.h"
+
+#include <algorithm>
+#include <boost/graph/boykov_kolmogorov_max_flow.hpp>
+
+using namespace std;
+using boost::default_color_type;
+
+namespace ue2 {
+
+static
+void addReverseEdge(const NGHolder &g, vector<NFAEdge> &reverseEdge,
+                    NFAEdge fwd, NFAEdge rev) {
+    u32 fwdIndex = g[fwd].index;
+    u32 revIndex = g[rev].index;
+
+    // Make sure our vector is big enough.
+    size_t sz = max(fwdIndex, revIndex) + 1;
+    if (reverseEdge.size() < sz) {
+        reverseEdge.resize(sz);
+    }
+
+    // Add entries to list.
+    reverseEdge[fwdIndex] = rev;
+    reverseEdge[revIndex] = fwd;
+}
+
+/** Add temporary reverse edges to the graph \p g, as they are required by the
+ * BGL's boykov_kolmogorov_max_flow algorithm. */
+static
+void addReverseEdges(NGHolder &g, vector<NFAEdge> &reverseEdge,
+                     vector<u64a> &capacityMap) {
+    // We're probably going to need space for 2x edge count.
+    const size_t numEdges = num_edges(g);
+    reverseEdge.reserve(numEdges * 2);
+    capacityMap.reserve(numEdges * 2);
+
+    // To avoid walking the graph for _ages_, we build a temporary map of all
+    // edges indexed by vertex pair for existence checks.
+    map<pair<size_t, size_t>, NFAEdge> allEdges;
+    for (const auto &e : edges_range(g)) {
+        NFAVertex u = source(e, g), v = target(e, g);
+        size_t uidx = g[u].index, vidx = g[v].index;
+        allEdges[make_pair(uidx, vidx)] = e;
+    }
+
+    // Now we walk over all edges and add their reverse edges to the reverseEdge
+    // vector, also adding them to the graph when they don't already exist.
+    for (const auto &m : allEdges) {
+        const NFAEdge &fwd = m.second;
+        const size_t uidx = m.first.first, vidx = m.first.second;
+
+        auto it = allEdges.find(make_pair(vidx, uidx));
+        if (it == allEdges.end()) {
+            // No reverse edge, add one.
+            NFAVertex u = source(fwd, g), v = target(fwd, g);
+            NFAEdge rev = add_edge(v, u, g);
+            it = allEdges.insert(make_pair(make_pair(vidx, uidx), rev)).first;
+            // Add to capacity map.
+            u32 revIndex = g[rev].index;
+            if (capacityMap.size() < revIndex + 1) {
+                capacityMap.resize(revIndex + 1);
+            }
+            capacityMap[revIndex] = 0;
+        }
+
+        addReverseEdge(g, reverseEdge, fwd, it->second);
+    }
+}
+
+/** Remove all edges with indices >= \p idx. */
+static
+void removeEdgesFromIndex(NGHolder &g, vector<u64a> &capacityMap, u32 idx) {
+    remove_edge_if([&](const NFAEdge &e) { return g[e].index >= idx; }, g);
+    capacityMap.resize(idx);
+    renumber_edges(g);
+}
+
+/** A wrapper around boykov_kolmogorov_max_flow, returns the max flow and
+ * colour map (from which we can find the min cut). */
+static
+u64a getMaxFlow(NGHolder &h, const vector<u64a> &capacityMap_in,
+                decltype(make_small_color_map(NGHolder())) &colorMap) {
+    vector<u64a> capacityMap = capacityMap_in;
+    NFAVertex src = h.start;
+    NFAVertex sink = h.acceptEod;
+
+    // netflow relies on these stylised edges, as all starts should be covered
+    // by our source and all accepts by our sink.
+    assert(edge(h.start, h.startDs, h).second);
+    assert(edge(h.accept, h.acceptEod, h).second);
+
+    // The boykov_kolmogorov_max_flow algorithm requires us to have reverse
+    // edges for all edges in the graph, so we create them here (and remove
+    // them after the call).
+    const unsigned int numRealEdges = num_edges(h);
+    vector<NFAEdge> reverseEdges;
+    addReverseEdges(h, reverseEdges, capacityMap);
+
+    const unsigned int numTotalEdges = num_edges(h);
+    const unsigned int numVertices = num_vertices(h);
+
+    vector<u64a> edgeResiduals(numTotalEdges);
+    vector<NFAEdge> predecessors(numVertices);
+    vector<s32> distances(numVertices);
+
+    auto v_index_map = get(vertex_index, h);
+    auto e_index_map = get(edge_index, h);
+
+    u64a flow = boykov_kolmogorov_max_flow(h,
+         make_iterator_property_map(capacityMap.begin(), e_index_map),
+         make_iterator_property_map(edgeResiduals.begin(), e_index_map),
+         make_iterator_property_map(reverseEdges.begin(), e_index_map),
+         make_iterator_property_map(predecessors.begin(), v_index_map),
+         colorMap,
+         make_iterator_property_map(distances.begin(), v_index_map),
+         v_index_map,
+         src, sink);
+
+    // Remove reverse edges from graph.
+    removeEdgesFromIndex(h, capacityMap, numRealEdges);
+    assert(num_edges(h) == numRealEdges);
+
+    DEBUG_PRINTF("flow = %llu\n", flow);
+    return flow;
+}
+
+/** Returns a min cut (in \p cutset) for the graph in \p h. */
+vector<NFAEdge> findMinCut(NGHolder &h, const vector<u64a> &scores) {
+    assert(hasCorrectlyNumberedEdges(h));
+    assert(hasCorrectlyNumberedVertices(h));
+
+    auto colors = make_small_color_map(h);
+    u64a flow = getMaxFlow(h, scores, colors);
+
+    vector<NFAEdge> picked_white;
+    vector<NFAEdge> picked_black;
+    u64a observed_black_flow = 0;
+    u64a observed_white_flow = 0;
+
+    for (const auto &e : edges_range(h)) {
+        NFAVertex from = source(e, h);
+        NFAVertex to = target(e, h);
+        u64a ec = scores[h[e].index];
+        if (ec == 0) {
+            continue; // skips, among other things, reverse edges
+        }
+
+        auto fromColor = get(colors, from);
+        auto toColor = get(colors, to);
+
+        if (fromColor != small_color::white && toColor == small_color::white) {
+            assert(ec <= INVALID_EDGE_CAP);
+            DEBUG_PRINTF("found white cut edge %zu->%zu cap %llu\n",
+                     h[from].index, h[to].index, ec);
+            observed_white_flow += ec;
+            picked_white.push_back(e);
+        }
+        if (fromColor == small_color::black && toColor != small_color::black) {
+            assert(ec <= INVALID_EDGE_CAP);
+            DEBUG_PRINTF("found black cut edge %zu->%zu cap %llu\n",
+                     h[from].index, h[to].index, ec);
+            observed_black_flow += ec;
+            picked_black.push_back(e);
+        }
+    }
+
+    DEBUG_PRINTF("min flow = %llu b flow = %llu w flow %llu\n", flow,
+                 observed_black_flow, observed_white_flow);
+    if (min(observed_white_flow, observed_black_flow) != flow) {
+        DEBUG_PRINTF("bad cut\n");
+    }
+
+    if (observed_white_flow < observed_black_flow) {
+        return picked_white;
+    } else {
+        return picked_black;
+    }
+}
+
+} // namespace ue2