1 files changed, 84 insertions, 0 deletions
diff --git a/klm/lm/quantize.cc b/klm/lm/quantize.cc
new file mode 100644
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+++ b/klm/lm/quantize.cc
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+#include "lm/quantize.hh"
+
+#include "lm/lm_exception.hh"
+
+#include <algorithm>
+#include <numeric>
+
+#include <unistd.h>
+
+namespace lm {
+namespace ngram {
+
+/* Quantize into bins of equal size as described in
+ * M. Federico and N. Bertoldi. 2006. How many bits are needed
+ * to store probabilities for phrase-based translation? In Proc.
+ * of the Workshop on Statistical Machine Translation, pages
+ * 94–101, New York City, June. Association for Computa-
+ * tional Linguistics.
+ */
+
+namespace {
+
+void MakeBins(float *values, float *values_end, float *centers, uint32_t bins) {
+  std::sort(values, values_end);
+  const float *start = values, *finish;
+  for (uint32_t i = 0; i < bins; ++i, ++centers, start = finish) {
+    finish = values + (((values_end - values) * static_cast<uint64_t>(i + 1)) / bins);
+    if (finish == start) {
+      // zero length bucket.
+      *centers = i ? *(centers - 1) : -std::numeric_limits<float>::infinity();
+    } else {
+      *centers = std::accumulate(start, finish, 0.0) / static_cast<float>(finish - start);
+    }
+  }
+}
+
+const char kSeparatelyQuantizeVersion = 2;
+
+} // namespace
+
+void SeparatelyQuantize::UpdateConfigFromBinary(int fd, const std::vector<uint64_t> &/*counts*/, Config &config) {
+  char version;
+  if (read(fd, &version, 1) != 1 || read(fd, &config.prob_bits, 1) != 1 || read(fd, &config.backoff_bits, 1) != 1) 
+    UTIL_THROW(util::ErrnoException, "Failed to read header for quantization.");
+  if (version != kSeparatelyQuantizeVersion) UTIL_THROW(FormatLoadException, "This file has quantization version " << (unsigned)version << " but the code expects version " << (unsigned)kSeparatelyQuantizeVersion);
+}
+
+void SeparatelyQuantize::SetupMemory(void *start, const Config &config) {
+  // Reserve 8 byte header for bit counts.  
+  start_ = reinterpret_cast<float*>(static_cast<uint8_t*>(start) + 8);
+  prob_bits_ = config.prob_bits;
+  backoff_bits_ = config.backoff_bits;
+  // We need the reserved values.  
+  if (config.prob_bits == 0) UTIL_THROW(ConfigException, "You can't quantize probability to zero");
+  if (config.backoff_bits == 0) UTIL_THROW(ConfigException, "You can't quantize backoff to zero");
+  if (config.prob_bits > 25) UTIL_THROW(ConfigException, "For efficiency reasons, quantizing probability supports at most 25 bits.  Currently you have requested " << static_cast<unsigned>(config.prob_bits) << " bits.");
+  if (config.backoff_bits > 25) UTIL_THROW(ConfigException, "For efficiency reasons, quantizing backoff supports at most 25 bits.  Currently you have requested " << static_cast<unsigned>(config.backoff_bits) << " bits.");
+}
+
+void SeparatelyQuantize::Train(uint8_t order, std::vector<float> &prob, std::vector<float> &backoff) {
+  TrainProb(order, prob);
+
+  // Backoff
+  float *centers = start_ + TableStart(order) + ProbTableLength();
+  *(centers++) = kNoExtensionBackoff;
+  *(centers++) = kExtensionBackoff;
+  MakeBins(&*backoff.begin(), &*backoff.end(), centers, (1ULL << backoff_bits_) - 2);
+}
+
+void SeparatelyQuantize::TrainProb(uint8_t order, std::vector<float> &prob) {
+  float *centers = start_ + TableStart(order);
+  *(centers++) = kBlankProb;
+  MakeBins(&*prob.begin(), &*prob.end(), centers, (1ULL << prob_bits_) - 1);
+}
+
+void SeparatelyQuantize::FinishedLoading(const Config &config) {
+  uint8_t *actual_base = reinterpret_cast<uint8_t*>(start_) - 8;
+  *(actual_base++) = kSeparatelyQuantizeVersion; // version
+  *(actual_base++) = config.prob_bits;
+  *(actual_base++) = config.backoff_bits;
+}
+
+} // namespace ngram
+} // namespace lm