Back out "printf -> fmt::print in files inc faiss/IndexBinaryHNSW.cpp" (

facebookresearch#3164)

Summary:
Pull Request resolved: facebookresearch#3164

The original diff breaks the open-source Faiss compiles.

Original commit changeset: 230540b26ec8

Original Phabricator Diff: D51486397

Reviewed By: algoriddle

Differential Revision: D51938993

fbshipit-source-id: a57433c4267493d2fe2249e8f4191612c0f1da59

faiss/IndexBinaryHNSW.cpp

@@ -31,7 +31,6 @@
 #include <faiss/utils/Heap.h>
 #include <faiss/utils/hamming.h>
 #include <faiss/utils/random.h>
-#include <fmt/core.h>
 
 namespace faiss {
 
@@ -52,18 +51,17 @@ void hnsw_add_vertices(
  size_t ntotal = n0 + n;
  double t0 = getmillisecs();
  if (verbose) {
- fmt::print(
- "hnsw_add_vertices: adding {} elements on top of {} "
- "(preset_levels={})\n",
- n,
- n0,
- int(preset_levels));
+ printf("hnsw_add_vertices: adding %zd elements on top of %zd "
+ "(preset_levels=%d)\n",
+ n,
+ n0,
+ int(preset_levels));
  }
 
  int max_level = hnsw.prepare_level_tab(n, preset_levels);
 
  if (verbose) {
- fmt::print(" max_level = {}\n", max_level);
+ printf(" max_level = %d\n", max_level);
  }
 
  std::vector<omp_lock_t> locks(ntotal);
@@ -110,8 +108,7 @@ void hnsw_add_vertices(
  int i0 = i1 - hist[pt_level];
 
  if (verbose) {
- fmt::print(
- "Adding {} elements at level {}\n", i1 - i0, pt_level);
+ printf("Adding %d elements at level %d\n", i1 - i0, pt_level);
  }
 
  // random permutation to get rid of dataset order bias
@@ -138,7 +135,7 @@ void hnsw_add_vertices(
 
  if (prev_display >= 0 && i - i0 > prev_display + 10000) {
  prev_display = i - i0;
- fmt::print(" {} / {}\r", i - i0, i1 - i0);
+ printf(" %d / %d\r", i - i0, i1 - i0);
  fflush(stdout);
  }
  }
@@ -148,7 +145,7 @@ void hnsw_add_vertices(
  FAISS_ASSERT(i1 == 0);
  }
  if (verbose) {
- fmt::print("Done in {:.3f} ms\n", getmillisecs() - t0);
+ printf("Done in %.3f ms\n", getmillisecs() - t0);
  }
 
  for (int i = 0; i < ntotal; i++)

faiss/IndexBinaryHash.cpp

@@ -20,7 +20,6 @@
 #include <faiss/impl/AuxIndexStructures.h>
 #include <faiss/impl/FaissAssert.h>
 #include <faiss/impl/platform_macros.h>
-#include <fmt/core.h>
 
 namespace faiss {
 
@@ -269,12 +268,12 @@ size_t IndexBinaryHash::hashtable_size() const {
 
 void IndexBinaryHash::display() const {
  for (auto it = invlists.begin(); it != invlists.end(); ++it) {
- fmt::print("%" PRId64 ": [", it->first);
+ printf("%" PRId64 ": [", it->first);
  const std::vector<idx_t>& v = it->second.ids;
  for (auto x : v) {
- fmt::print("%" PRId64 " ", x);
+ printf("%" PRId64 " ", x);
  }
- fmt::print("]\n");
+ printf("]\n");
  }
 }
 

faiss/IndexBinaryIVF.cpp

@@ -23,7 +23,6 @@
 #include <faiss/utils/hamming.h>
 #include <faiss/utils/sorting.h>
 #include <faiss/utils/utils.h>
-#include <fmt/core.h>
 
 namespace faiss {
 
@@ -88,11 +87,10 @@ void IndexBinaryIVF::add_core(
  n_add++;
  }
  if (verbose) {
- fmt::print(
- "IndexBinaryIVF::add_with_ids: added "
- "%" PRId64 " / %" PRId64 " vectors\n",
- n_add,
- n);
+ printf("IndexBinaryIVF::add_with_ids: added "
+ "%" PRId64 " / %" PRId64 " vectors\n",
+ n_add,
+ n);
  }
  ntotal += n_add;
 }
@@ -235,17 +233,16 @@ size_t IndexBinaryIVF::remove_ids(const IDSelector& sel) {
 
 void IndexBinaryIVF::train(idx_t n, const uint8_t* x) {
  if (verbose) {
- fmt::print("Training quantizer\n");
+ printf("Training quantizer\n");
  }
 
  if (quantizer->is_trained && (quantizer->ntotal == nlist)) {
  if (verbose) {
- fmt::print("IVF quantizer does not need training.\n");
+ printf("IVF quantizer does not need training.\n");
  }
  } else {
  if (verbose) {
- fmt::print(
- "Training quantizer on %" PRId64 " vectors in {}D\n", n, d);
+ printf("Training quantizer on %" PRId64 " vectors in %dD\n", n, d);
  }
 
  Clustering clus(d, nlist, cp);
@@ -254,9 +251,8 @@ void IndexBinaryIVF::train(idx_t n, const uint8_t* x) {
  IndexFlatL2 index_tmp(d);
 
  if (clustering_index && verbose) {
- fmt::print(
- "using clustering_index of dimension {} to do the clustering\n",
- clustering_index->d);
+ printf("using clustering_index of dimension %d to do the clustering\n",
+ clustering_index->d);
  }
 
  // LSH codec that is able to convert the binary vectors to floats.

faiss/IndexFastScan.cpp

@@ -26,7 +26,6 @@
 #include <faiss/impl/pq4_fast_scan.h>
 #include <faiss/impl/simd_result_handlers.h>
 #include <faiss/utils/quantize_lut.h>
-#include <fmt/core.h>
 
 namespace faiss {
 
@@ -74,7 +73,7 @@ void IndexFastScan::add(idx_t n, const float* x) {
  for (idx_t i0 = 0; i0 < n; i0 += bs) {
  idx_t i1 = std::min(n, i0 + bs);
  if (verbose) {
- fmt::print("IndexFastScan::add {}/{}\n", size_t(i1), size_t(n));
+ printf("IndexFastScan::add %zd/%zd\n", size_t(i1), size_t(n));
  }
  add(i1 - i0, x + i0 * d);
  }

faiss/IndexHNSW.cpp

@@ -33,7 +33,6 @@
 #include <faiss/utils/distances.h>
 #include <faiss/utils/random.h>
 #include <faiss/utils/sorting.h>
-#include <fmt/core.h>
 
 extern "C" {
 
@@ -135,12 +134,11 @@ void hnsw_add_vertices(
  size_t ntotal = n0 + n;
  double t0 = getmillisecs();
  if (verbose) {
- fmt::print(
- "hnsw_add_vertices: adding {} elements on top of {} "
- "(preset_levels={})\n",
- n,
- n0,
- int(preset_levels));
+ printf("hnsw_add_vertices: adding %zd elements on top of %zd "
+ "(preset_levels=%d)\n",
+ n,
+ n0,
+ int(preset_levels));
  }
 
  if (n == 0) {
@@ -150,7 +148,7 @@ void hnsw_add_vertices(
  int max_level = hnsw.prepare_level_tab(n, preset_levels);
 
  if (verbose) {
- fmt::print(" max_level = {}\n", max_level);
+ printf(" max_level = %d\n", max_level);
  }
 
  std::vector<omp_lock_t> locks(ntotal);
@@ -198,8 +196,7 @@ void hnsw_add_vertices(
  int i0 = i1 - hist[pt_level];
 
  if (verbose) {
- fmt::print(
- "Adding {} elements at level {}\n", i1 - i0, pt_level);
+ printf("Adding %d elements at level %d\n", i1 - i0, pt_level);
  }
 
  // random permutation to get rid of dataset order bias
@@ -235,7 +232,7 @@ void hnsw_add_vertices(
 
  if (prev_display >= 0 && i - i0 > prev_display + 10000) {
  prev_display = i - i0;
- fmt::print(" {} / {}\r", i - i0, i1 - i0);
+ printf(" %d / %d\r", i - i0, i1 - i0);
  fflush(stdout);
  }
  if (counter % check_period == 0) {
@@ -254,7 +251,7 @@ void hnsw_add_vertices(
  FAISS_ASSERT(i1 == 0);
  }
  if (verbose) {
- fmt::print("Done in {:.3f} ms\n", getmillisecs() - t0);
+ printf("Done in %.3f ms\n", getmillisecs() - t0);
  }
 
  for (int i = 0; i < ntotal; i++) {
@@ -541,13 +538,13 @@ void IndexHNSW::init_level_0_from_entry_points(
  *dis, pt_id, nearest, (*dis)(nearest), 0, locks.data(), vt);
 
  if (verbose && i % 10000 == 0) {
- fmt::print(" {} / {}\r", i, n);
+ printf(" %d / %d\r", i, n);
  fflush(stdout);
  }
  }
  }
  if (verbose) {
- fmt::print("\n");
+ printf("\n");
  }
 
  for (int i = 0; i < ntotal; i++)
@@ -589,7 +586,7 @@ void IndexHNSW::reorder_links() {
 }
 
 void IndexHNSW::link_singletons() {
- fmt::print("search for singletons\n");
+ printf("search for singletons\n");
 
  std::vector<bool> seen(ntotal);
 
@@ -614,12 +611,10 @@ void IndexHNSW::link_singletons() {
  }
  }
 
- fmt::print(
- " Found {} / %" PRId64
- " singletons ({} appear in a level above)\n",
- n_sing,
- ntotal,
- n_sing_l1);
+ printf(" Found %d / %" PRId64 " singletons (%d appear in a level above)\n",
+ n_sing,
+ ntotal,
+ n_sing_l1);
 
  std::vector<float> recons(singletons.size() * d);
  for (int i = 0; i < singletons.size(); i++) {

faiss/IndexIVF.cpp

@@ -28,7 +28,6 @@
 #include <faiss/impl/CodePacker.h>
 #include <faiss/impl/FaissAssert.h>
 #include <faiss/impl/IDSelector.h>
-#include <fmt/core.h>
 
 namespace faiss {
 
@@ -63,19 +62,18 @@ void Level1Quantizer::train_q1(
  size_t d = quantizer->d;
  if (quantizer->is_trained && (quantizer->ntotal == nlist)) {
  if (verbose)
- fmt::print("IVF quantizer does not need training.\n");
+ printf("IVF quantizer does not need training.\n");
  } else if (quantizer_trains_alone == 1) {
  if (verbose)
- fmt::print("IVF quantizer trains alone...\n");
+ printf("IVF quantizer trains alone...\n");
  quantizer->train(n, x);
  quantizer->verbose = verbose;
  FAISS_THROW_IF_NOT_MSG(
  quantizer->ntotal == nlist,
  "nlist not consistent with quantizer size");
  } else if (quantizer_trains_alone == 0) {
  if (verbose)
- fmt::print(
- "Training level-1 quantizer on {} vectors in {}D\n", n, d);
+ printf("Training level-1 quantizer on %zd vectors in %zdD\n", n, d);
 
  Clustering clus(d, nlist, cp);
  quantizer->reset();
@@ -88,11 +86,10 @@ void Level1Quantizer::train_q1(
  quantizer->is_trained = true;
  } else if (quantizer_trains_alone == 2) {
  if (verbose) {
- fmt::print(
- "Training L2 quantizer on {} vectors in {}D{}\n",
- n,
- d,
- clustering_index ? "(user provided index)" : "");
+ printf("Training L2 quantizer on %zd vectors in %zdD%s\n",
+ n,
+ d,
+ clustering_index ? "(user provided index)" : "");
  }
  // also accept spherical centroids because in that case
  // L2 and IP are equivalent
@@ -108,11 +105,11 @@ void Level1Quantizer::train_q1(
  clus.train(n, x, *clustering_index);
  }
  if (verbose) {
- fmt::print("Adding centroids to quantizer\n");
+ printf("Adding centroids to quantizer\n");
  }
  if (!quantizer->is_trained) {
  if (verbose) {
- fmt::print("But training it first on centroids table...\n");
+ printf("But training it first on centroids table...\n");
  }
  quantizer->train(nlist, clus.centroids.data());
  }
@@ -213,10 +210,9 @@ void IndexIVF::add_core(
  for (idx_t i0 = 0; i0 < n; i0 += bs) {
  idx_t i1 = std::min(n, i0 + bs);
  if (verbose) {
- fmt::print(
- " IndexIVF::add_with_ids %" PRId64 ":%" PRId64 "\n",
- i0,
- i1);
+ printf(" IndexIVF::add_with_ids %" PRId64 ":%" PRId64 "\n",
+ i0,
+ i1);
  }
  add_core(
  i1 - i0,
@@ -265,11 +261,10 @@ void IndexIVF::add_core(
  }
 
  if (verbose) {
- fmt::print(
- " added {} / %" PRId64 " vectors ({} -1s)\n",
- nadd,
- n,
- nminus1);
+ printf(" added %zd / %" PRId64 " vectors (%zd -1s)\n",
+ nadd,
+ n,
+ nminus1);
  }
 
  ntotal += n;
@@ -1133,13 +1128,13 @@ void IndexIVF::update_vectors(int n, const idx_t* new_ids, const float* x) {
 
 void IndexIVF::train(idx_t n, const float* x) {
  if (verbose) {
- fmt::print("Training level-1 quantizer\n");
+ printf("Training level-1 quantizer\n");
  }
 
  train_q1(n, x, verbose, metric_type);
 
  if (verbose) {
- fmt::print("Training IVF residual\n");
+ printf("Training IVF residual\n");
  }
 
  // optional subsampling
@@ -1176,7 +1171,7 @@ void IndexIVF::train_encoder(
  const idx_t* assign) {
  // does nothing by default
  if (verbose) {
- fmt::print("IndexIVF: no residual training\n");
+ printf("IndexIVF: no residual training\n");
  }
 }