Facebook sync (#504)

* Facebook sync

* Update swig wrappers.

* Fix comment.

tests/test_binary_flat.cpp

@@ -0,0 +1,65 @@
+/**
+ * Copyright (c) 2015-present, Facebook, Inc.
+ * All rights reserved.
+ *
+ * This source code is licensed under the BSD+Patents license found in the
+ * LICENSE file in the root directory of this source tree.
+ */
+
+#include <cstdio>
+#include <cstdlib>
+
+#include <gtest/gtest.h>
+
+#include <faiss/IndexBinaryFlat.h>
+#include <faiss/hamming.h>
+
+TEST(BinaryFlat, accuracy) {
+  // dimension of the vectors to index
+  int d = 64;
+
+  // size of the database we plan to index
+  size_t nb = 1000;
+
+  // make the index object and train it
+  faiss::IndexBinaryFlat index(d);
+
+  srand(35);
+
+  std::vector<uint8_t> database(nb * (d / 8));
+  for (size_t i = 0; i < nb * (d / 8); i++) {
+    database[i] = rand() % 0x100;
+  }
+
+  { // populating the database
+    index.add(nb, database.data());
+  }
+
+  int nq = 200;
+
+  { // searching the database
+
+    std::vector<uint8_t> queries(nq * (d / 8));
+    for (size_t i = 0; i < nq * (d / 8); i++) {
+      queries[i] = rand() % 0x100;
+    }
+
+    int k = 5;
+    std::vector<faiss::IndexBinary::idx_t> nns(k * nq);
+    std::vector<int>                     dis(k * nq);
+
+    index.search(nq, queries.data(), k, dis.data(), nns.data());
+
+    for (size_t i = 0; i < nq; ++i) {
+      faiss::HammingComputer8 hc(queries.data() + i * (d / 8), d / 8);
+      hamdis_t dist_min = hc.hamming(database.data());
+      for (size_t j = 1; j < nb; ++j) {
+        hamdis_t dist = hc.hamming(database.data() + j * (d / 8));
+        if (dist < dist_min) {
+          dist_min = dist;
+        }
+      }
+      EXPECT_EQ(dist_min, dis[k * i]);
+    }
+  }
+}