New NNUE architecture and net

[stockfish] / src / nnue / layers / clipped_relu.h

diff --git a/src/nnue/layers/clipped_relu.h b/src/nnue/layers/clipped_relu.h
index f1ac2dfe64455a807d4ee1083f157a2dc9b33b6c..65455df4944324a12870ca29d68c9ff5e0b379b1 100644 (file)
--- a/src/nnue/layers/clipped_relu.h
+++ b/src/nnue/layers/clipped_relu.h
@@ -72,22 +72,42 @@ namespace Stockfish::Eval::NNUE::Layers {
       const auto output = reinterpret_cast<OutputType*>(buffer);
 
   #if defined(USE_AVX2)
-      constexpr IndexType NumChunks = InputDimensions / SimdWidth;
-      const __m256i Zero = _mm256_setzero_si256();
-      const __m256i Offsets = _mm256_set_epi32(7, 3, 6, 2, 5, 1, 4, 0);
-      const auto in = reinterpret_cast<const __m256i*>(input);
-      const auto out = reinterpret_cast<__m256i*>(output);
-      for (IndexType i = 0; i < NumChunks; ++i) {
-        const __m256i words0 = _mm256_srai_epi16(_mm256_packs_epi32(
-            _mm256_load_si256(&in[i * 4 + 0]),
-            _mm256_load_si256(&in[i * 4 + 1])), WeightScaleBits);
-        const __m256i words1 = _mm256_srai_epi16(_mm256_packs_epi32(
-            _mm256_load_si256(&in[i * 4 + 2]),
-            _mm256_load_si256(&in[i * 4 + 3])), WeightScaleBits);
-        _mm256_store_si256(&out[i], _mm256_permutevar8x32_epi32(_mm256_max_epi8(
-            _mm256_packs_epi16(words0, words1), Zero), Offsets));
+      if constexpr (InputDimensions % SimdWidth == 0) {
+        constexpr IndexType NumChunks = InputDimensions / SimdWidth;
+        const __m256i Zero = _mm256_setzero_si256();
+        const __m256i Offsets = _mm256_set_epi32(7, 3, 6, 2, 5, 1, 4, 0);
+        const auto in = reinterpret_cast<const __m256i*>(input);
+        const auto out = reinterpret_cast<__m256i*>(output);
+        for (IndexType i = 0; i < NumChunks; ++i) {
+          const __m256i words0 = _mm256_srai_epi16(_mm256_packs_epi32(
+              _mm256_load_si256(&in[i * 4 + 0]),
+              _mm256_load_si256(&in[i * 4 + 1])), WeightScaleBits);
+          const __m256i words1 = _mm256_srai_epi16(_mm256_packs_epi32(
+              _mm256_load_si256(&in[i * 4 + 2]),
+              _mm256_load_si256(&in[i * 4 + 3])), WeightScaleBits);
+          _mm256_store_si256(&out[i], _mm256_permutevar8x32_epi32(_mm256_max_epi8(
+              _mm256_packs_epi16(words0, words1), Zero), Offsets));
+        }
+      } else {
+        constexpr IndexType NumChunks = InputDimensions / (SimdWidth / 2);
+        const __m128i Zero = _mm_setzero_si128();
+        const auto in = reinterpret_cast<const __m128i*>(input);
+        const auto out = reinterpret_cast<__m128i*>(output);
+        for (IndexType i = 0; i < NumChunks; ++i) {
+          const __m128i words0 = _mm_srai_epi16(_mm_packs_epi32(
+              _mm_load_si128(&in[i * 4 + 0]),
+              _mm_load_si128(&in[i * 4 + 1])), WeightScaleBits);
+          const __m128i words1 = _mm_srai_epi16(_mm_packs_epi32(
+              _mm_load_si128(&in[i * 4 + 2]),
+              _mm_load_si128(&in[i * 4 + 3])), WeightScaleBits);
+          const __m128i packedbytes = _mm_packs_epi16(words0, words1);
+          _mm_store_si128(&out[i], _mm_max_epi8(packedbytes, Zero));
+        }
       }
-      constexpr IndexType Start = NumChunks * SimdWidth;
+      constexpr IndexType Start =
+        InputDimensions % SimdWidth == 0
+        ? InputDimensions / SimdWidth * SimdWidth
+        : InputDimensions / (SimdWidth / 2) * (SimdWidth / 2);
 
   #elif defined(USE_SSE2)
       constexpr IndexType NumChunks = InputDimensions / SimdWidth;