biases_[i] = read_little_endian<BiasType>(stream);
for (std::size_t i = 0; i < kOutputDimensions * kPaddedInputDimensions; ++i)
weights_[i] = read_little_endian<WeightType>(stream);
+
+#if defined (USE_SSSE3)
+ // Determine if quadruplets of weight and input products can be summed using 16bits
+ // without saturation. We assume worst case combinations of 0 and 127 for all inputs.
+ if (!stream.fail())
+ {
+ auto can_saturate = [](const WeightType* w, int idx[4]) {
+ int pSum = 0, nSum = 0;
+ for (int p = 0; p < 4; ++p)
+ if (w[idx[p]] > 0)
+ pSum += w[idx[p]];
+ else
+ nSum += w[idx[p]];
+
+ return pSum > 258 || nSum < -258;
+ };
+
+ for (IndexType i = 0; i < kOutputDimensions; ++i)
+ {
+ canSaturate16[i] = false;
+ const WeightType* w = &weights_[i * kPaddedInputDimensions];
+#if defined (USE_AVX512)
+ for (IndexType j = 0; j < (kPaddedInputDimensions & ~127) && !canSaturate16[i]; j += 128)
+ for (int k = 0; k < 64 && !canSaturate16[i]; k += 2)
+ {
+ int spacing[4] = { 0, 1, 64, 65 };
+ canSaturate16[i] = can_saturate(&w[j + k], spacing);
+ }
+#elif defined (USE_AVX2)
+ for (IndexType j = 0; j < (kPaddedInputDimensions & ~63) && !canSaturate16[i]; j += 64)
+ for (int k = 0; k < 32 && !canSaturate16[i]; k += 2)
+ {
+ int spacing[4] = { 0, 1, 32, 33 };
+ canSaturate16[i] = can_saturate(&w[j + k], spacing);
+ }
+#elif defined (USE_SSSE3)
+ for (IndexType j = 0; j < (kPaddedInputDimensions & ~31) && !canSaturate16[i]; j += 32)
+ for (int k = 0; k < 16 && !canSaturate16[i]; k += 2)
+ {
+ int spacing[4] = { 0, 1, 16, 17 };
+ canSaturate16[i] = can_saturate(&w[j + k], spacing);
+ }
+#endif
+ }
+ }
+#endif
+
return !stream.fail();
}
return _mm512_add_epi32(_mm512_permutexvar_epi32(indices, x), bias);
};
-#if defined (USE_VNNI)
[[maybe_unused]] auto m512_add_dpbusd_epi32 = [=](__m512i& acc, __m512i a, __m512i b) {
+#if defined (USE_VNNI)
acc = _mm512_dpbusd_epi32(acc, a, b);
#else
- [[maybe_unused]] auto m512_dpbusd_epi32 = [=](__m512i a, __m512i b) -> __m512i {
__m512i product0 = _mm512_maddubs_epi16(a, b);
- return _mm512_madd_epi16(product0, kOnes512);
+ product0 = _mm512_madd_epi16(product0, kOnes512);
+ acc = _mm512_add_epi32(acc, product0);
+#endif
+ };
+
+ [[maybe_unused]] auto m512_add_dpbusd_epi32x2 = [=](__m512i& acc, __m512i a0, __m512i b0, __m512i a1, __m512i b1) {
+#if defined (USE_VNNI)
+ acc = _mm512_dpbusd_epi32(acc, a0, b0);
+ acc = _mm512_dpbusd_epi32(acc, a1, b1);
+#else
+ __m512i product0 = _mm512_maddubs_epi16(a0, b0);
+ __m512i product1 = _mm512_maddubs_epi16(a1, b1);
+ product0 = _mm512_adds_epi16(product0, product1);
+ product0 = _mm512_madd_epi16(product0, kOnes512);
+ acc = _mm512_add_epi32(acc, product0);
#endif
};
return _mm_add_epi32(_mm_add_epi32(sum128lo, sum128hi), bias);
};
-#if defined (USE_VNNI)
+
[[maybe_unused]] auto m256_add_dpbusd_epi32 = [=](__m256i& acc, __m256i a, __m256i b) {
+#if defined (USE_VNNI)
acc = _mm256_dpbusd_epi32(acc, a, b);
#else
- [[maybe_unused]] auto m256_dpbusd_epi32 = [=](__m256i a, __m256i b) -> __m256i {
__m256i product0 = _mm256_maddubs_epi16(a, b);
- return _mm256_madd_epi16(product0, kOnes256);
+ product0 = _mm256_madd_epi16(product0, kOnes256);
+ acc = _mm256_add_epi32(acc, product0);
+#endif
+ };
+
+ [[maybe_unused]] auto m256_add_dpbusd_epi32x2 = [=](__m256i& acc, __m256i a0, __m256i b0, __m256i a1, __m256i b1) {
+#if defined (USE_VNNI)
+ acc = _mm256_dpbusd_epi32(acc, a0, b0);
+ acc = _mm256_dpbusd_epi32(acc, a1, b1);
+#else
+ __m256i product0 = _mm256_maddubs_epi16(a0, b0);
+ __m256i product1 = _mm256_maddubs_epi16(a1, b1);
+ product0 = _mm256_adds_epi16(product0, product1);
+ product0 = _mm256_madd_epi16(product0, kOnes256);
+ acc = _mm256_add_epi32(acc, product0);
#endif
};
return _mm_add_epi32(sum0, bias);
};
- [[maybe_unused]] auto m128_dpbusd_epi32 = [=](__m128i a, __m128i b) -> __m128i {
+ [[maybe_unused]] auto m128_add_dpbusd_epi32 = [=](__m128i& acc, __m128i a, __m128i b) {
__m128i product0 = _mm_maddubs_epi16(a, b);
- return _mm_madd_epi16(product0, kOnes128);
+ product0 = _mm_madd_epi16(product0, kOnes128);
+ acc = _mm_add_epi32(acc, product0);
+ };
+
+ [[maybe_unused]] auto m128_add_dpbusd_epi32x2 = [=](__m128i& acc, __m128i a0, __m128i b0, __m128i a1, __m128i b1) {
+ __m128i product0 = _mm_maddubs_epi16(a0, b0);
+ __m128i product1 = _mm_maddubs_epi16(a1, b1);
+ product0 = _mm_adds_epi16(product0, product1);
+ product0 = _mm_madd_epi16(product0, kOnes128);
+ acc = _mm_add_epi32(acc, product0);
};
#endif
const __m512i bias = *reinterpret_cast<const __m512i*>(&biases_[i]);
__m512i* outptr = reinterpret_cast<__m512i*>(&output[i]);
+ __m512i sum01a = _mm512_setzero_si512();
+ __m512i sum23a = _mm512_setzero_si512();
+ __m512i sum45a = _mm512_setzero_si512();
+ __m512i sum67a = _mm512_setzero_si512();
+ __m512i sum01b = _mm512_setzero_si512();
+ __m512i sum23b = _mm512_setzero_si512();
+ __m512i sum45b = _mm512_setzero_si512();
+ __m512i sum67b = _mm512_setzero_si512();
+
const auto row01a = *reinterpret_cast<const __m512i*>(&weights_[offset01a]);
const auto row23a = *reinterpret_cast<const __m512i*>(&weights_[offset23a]);
const auto row45a = *reinterpret_cast<const __m512i*>(&weights_[offset45a]);
const __m256i in256 = input_vector256[0];
const __m512i in = _mm512_inserti64x4(_mm512_castsi256_si512(in256), in256, 1);
-#if defined (USE_VNNI)
- __m512i sum01a = _mm512_setzero_si512();
- __m512i sum23a = _mm512_setzero_si512();
- __m512i sum45a = _mm512_setzero_si512();
- __m512i sum67a = _mm512_setzero_si512();
- __m512i sum01b = _mm512_setzero_si512();
- __m512i sum23b = _mm512_setzero_si512();
- __m512i sum45b = _mm512_setzero_si512();
- __m512i sum67b = _mm512_setzero_si512();
-
m512_add_dpbusd_epi32(sum01a, in, row01a);
m512_add_dpbusd_epi32(sum23a, in, row23a);
m512_add_dpbusd_epi32(sum45a, in, row45a);
m512_add_dpbusd_epi32(sum23b, in, row23b);
m512_add_dpbusd_epi32(sum45b, in, row45b);
m512_add_dpbusd_epi32(sum67b, in, row67b);
-#else
- __m512i sum01a = m512_dpbusd_epi32(in, row01a);
- __m512i sum23a = m512_dpbusd_epi32(in, row23a);
- __m512i sum45a = m512_dpbusd_epi32(in, row45a);
- __m512i sum67a = m512_dpbusd_epi32(in, row67a);
- __m512i sum01b = m512_dpbusd_epi32(in, row01b);
- __m512i sum23b = m512_dpbusd_epi32(in, row23b);
- __m512i sum45b = m512_dpbusd_epi32(in, row45b);
- __m512i sum67b = m512_dpbusd_epi32(in, row67b);
-#endif
*outptr = m512_hadd256x16(
sum01a, sum23a, sum45a, sum67a,
if constexpr (kPaddedInputDimensions % (kSimdWidth * 2) == 0)
{
- const auto row0 = reinterpret_cast<const __m512i*>(&weights_[offset0]);
- const auto row1 = reinterpret_cast<const __m512i*>(&weights_[offset1]);
- const auto row2 = reinterpret_cast<const __m512i*>(&weights_[offset2]);
- const auto row3 = reinterpret_cast<const __m512i*>(&weights_[offset3]);
-
-#if defined (USE_VNNI)
__m512i sum0 = _mm512_setzero_si512();
__m512i sum1 = _mm512_setzero_si512();
__m512i sum2 = _mm512_setzero_si512();
__m512i sum3 = _mm512_setzero_si512();
- const IndexType kStart = 0;
-#else
- __m512i sum0 = m512_dpbusd_epi32(input_vector512[0], row0[0]);
- __m512i sum1 = m512_dpbusd_epi32(input_vector512[0], row1[0]);
- __m512i sum2 = m512_dpbusd_epi32(input_vector512[0], row2[0]);
- __m512i sum3 = m512_dpbusd_epi32(input_vector512[0], row3[0]);
- const IndexType kStart = 1;
-#endif
- for (IndexType j = kStart; j < kNumChunks512; ++j)
+ const auto row0 = reinterpret_cast<const __m512i*>(&weights_[offset0]);
+ const auto row1 = reinterpret_cast<const __m512i*>(&weights_[offset1]);
+ const auto row2 = reinterpret_cast<const __m512i*>(&weights_[offset2]);
+ const auto row3 = reinterpret_cast<const __m512i*>(&weights_[offset3]);
+
+ int j = 0;
+ if (!canSaturate16x4[i / 4])
+ {
+ for (; j < (int)kNumChunks512 - 1; j += 2)
+ {
+ const __m512i in0 = input_vector512[j];
+ const __m512i in1 = input_vector512[j + 1];
+
+ m512_add_dpbusd_epi32x2(sum0, in0, row0[j], in1, row0[j + 1]);
+ m512_add_dpbusd_epi32x2(sum1, in0, row1[j], in1, row1[j + 1]);
+ m512_add_dpbusd_epi32x2(sum2, in0, row2[j], in1, row2[j + 1]);
+ m512_add_dpbusd_epi32x2(sum3, in0, row3[j], in1, row3[j + 1]);
+ }
+ }
+ for (; j < (int)kNumChunks512; ++j)
{
const __m512i in = input_vector512[j];
-#if defined (USE_VNNI)
m512_add_dpbusd_epi32(sum0, in, row0[j]);
m512_add_dpbusd_epi32(sum1, in, row1[j]);
m512_add_dpbusd_epi32(sum2, in, row2[j]);
m512_add_dpbusd_epi32(sum3, in, row3[j]);
-#else
- sum0 = _mm512_add_epi32(sum0, m512_dpbusd_epi32(in, row0[j]));
- sum1 = _mm512_add_epi32(sum1, m512_dpbusd_epi32(in, row1[j]));
- sum2 = _mm512_add_epi32(sum2, m512_dpbusd_epi32(in, row2[j]));
- sum3 = _mm512_add_epi32(sum3, m512_dpbusd_epi32(in, row3[j]));
-#endif
}
*outptr = m512_haddx4(sum0, sum1, sum2, sum3, bias);
}
else
{
- const auto row0 = reinterpret_cast<const __m256i*>(&weights_[offset0]);
- const auto row1 = reinterpret_cast<const __m256i*>(&weights_[offset1]);
- const auto row2 = reinterpret_cast<const __m256i*>(&weights_[offset2]);
- const auto row3 = reinterpret_cast<const __m256i*>(&weights_[offset3]);
-
-#if defined (USE_VNNI)
__m256i sum0 = _mm256_setzero_si256();
__m256i sum1 = _mm256_setzero_si256();
__m256i sum2 = _mm256_setzero_si256();
__m256i sum3 = _mm256_setzero_si256();
- const IndexType kStart = 0;
-#else
- __m256i sum0 = m256_dpbusd_epi32(input_vector256[0], row0[0]);
- __m256i sum1 = m256_dpbusd_epi32(input_vector256[0], row1[0]);
- __m256i sum2 = m256_dpbusd_epi32(input_vector256[0], row2[0]);
- __m256i sum3 = m256_dpbusd_epi32(input_vector256[0], row3[0]);
- const IndexType kStart = 1;
-#endif
- for (IndexType j = kStart; j < kNumChunks256; ++j)
+ const auto row0 = reinterpret_cast<const __m256i*>(&weights_[offset0]);
+ const auto row1 = reinterpret_cast<const __m256i*>(&weights_[offset1]);
+ const auto row2 = reinterpret_cast<const __m256i*>(&weights_[offset2]);
+ const auto row3 = reinterpret_cast<const __m256i*>(&weights_[offset3]);
+
+ for (IndexType j = 0; j < kNumChunks256; ++j)
{
const __m256i in = input_vector256[j];
-#if defined (USE_VNNI)
m256_add_dpbusd_epi32(sum0, in, row0[j]);
m256_add_dpbusd_epi32(sum1, in, row1[j]);
m256_add_dpbusd_epi32(sum2, in, row2[j]);
m256_add_dpbusd_epi32(sum3, in, row3[j]);
-#else
- sum0 = _mm256_add_epi32(sum0, m256_dpbusd_epi32(in, row0[j]));
- sum1 = _mm256_add_epi32(sum1, m256_dpbusd_epi32(in, row1[j]));
- sum2 = _mm256_add_epi32(sum2, m256_dpbusd_epi32(in, row2[j]));
- sum3 = _mm256_add_epi32(sum3, m256_dpbusd_epi32(in, row3[j]));
-#endif
}
*outptr = m256_haddx4(sum0, sum1, sum2, sum3, bias);
{
if constexpr (kPaddedInputDimensions % (kSimdWidth * 2) == 0)
{
- const auto row0 = reinterpret_cast<const __m512i*>(&weights_[0]);
-
-#if defined (USE_VNNI)
__m512i sum0 = _mm512_setzero_si512();
- const IndexType kStart = 0;
-#else
- __m512i sum0 = m512_dpbusd_epi32(input_vector512[0], row0[0]);
- const IndexType kStart = 1;
-#endif
- for (IndexType j = kStart; j < kNumChunks512; ++j)
+ const auto row0 = reinterpret_cast<const __m512i*>(&weights_[0]);
+
+ for (IndexType j = 0; j < kNumChunks512; ++j)
{
const __m512i in = input_vector512[j];
-#if defined (USE_VNNI)
m512_add_dpbusd_epi32(sum0, in, row0[j]);
-#else
- sum0 = _mm512_add_epi32(sum0, m512_dpbusd_epi32(in, row0[j]));
-#endif
}
output[0] = m512_hadd(sum0, biases_[0]);
}
else
{
- const auto row0 = reinterpret_cast<const __m256i*>(&weights_[0]);
-
-#if defined (USE_VNNI)
__m256i sum0 = _mm256_setzero_si256();
- const IndexType kStart = 0;
-#else
- __m256i sum0 = m256_dpbusd_epi32(input_vector256[0], row0[0]);
- const IndexType kStart = 1;
-#endif
- for (IndexType j = kStart; j < kNumChunks256; ++j)
+ const auto row0 = reinterpret_cast<const __m256i*>(&weights_[0]);
+
+ for (IndexType j = 0; j < kNumChunks256; ++j)
{
const __m256i in = input_vector256[j];
-#if defined (USE_VNNI)
m256_add_dpbusd_epi32(sum0, in, row0[j]);
-#else
- sum0 = _mm256_add_epi32(sum0, m256_dpbusd_epi32(in, row0[j]));
-#endif
}
output[0] = m256_hadd(sum0, biases_[0]);
const __m128i bias = *reinterpret_cast<const __m128i*>(&biases_[i]);
__m128i* outptr = reinterpret_cast<__m128i*>(&output[i]);
- const auto row0 = reinterpret_cast<const __m256i*>(&weights_[offset0]);
- const auto row1 = reinterpret_cast<const __m256i*>(&weights_[offset1]);
- const auto row2 = reinterpret_cast<const __m256i*>(&weights_[offset2]);
- const auto row3 = reinterpret_cast<const __m256i*>(&weights_[offset3]);
-
-#if defined (USE_VNNI)
__m256i sum0 = _mm256_setzero_si256();
__m256i sum1 = _mm256_setzero_si256();
__m256i sum2 = _mm256_setzero_si256();
__m256i sum3 = _mm256_setzero_si256();
- const IndexType kStart = 0;
-#else
- __m256i sum0 = m256_dpbusd_epi32(input_vector[0], row0[0]);
- __m256i sum1 = m256_dpbusd_epi32(input_vector[0], row1[0]);
- __m256i sum2 = m256_dpbusd_epi32(input_vector[0], row2[0]);
- __m256i sum3 = m256_dpbusd_epi32(input_vector[0], row3[0]);
- const IndexType kStart = 1;
-#endif
- for (IndexType j = kStart; j < kNumChunks; ++j)
+ const auto row0 = reinterpret_cast<const __m256i*>(&weights_[offset0]);
+ const auto row1 = reinterpret_cast<const __m256i*>(&weights_[offset1]);
+ const auto row2 = reinterpret_cast<const __m256i*>(&weights_[offset2]);
+ const auto row3 = reinterpret_cast<const __m256i*>(&weights_[offset3]);
+
+ int j = 0;
+ if (!canSaturate16x4[i / 4])
{
- const __m256i in = input_vector[j];
+ for (; j < (int)kNumChunks - 1; j += 2)
+ {
+ const __m256i in0 = input_vector[j];
+ const __m256i in1 = input_vector[j + 1];
+
+ m256_add_dpbusd_epi32x2(sum0, in0, row0[j], in1, row0[j + 1]);
+ m256_add_dpbusd_epi32x2(sum1, in0, row1[j], in1, row1[j + 1]);
+ m256_add_dpbusd_epi32x2(sum2, in0, row2[j], in1, row2[j + 1]);
+ m256_add_dpbusd_epi32x2(sum3, in0, row3[j], in1, row3[j + 1]);
+ }
+ }
+ for (; j < (int)kNumChunks; ++j)
+ {
+ const __m256i in = input_vector[j];
-#if defined (USE_VNNI)
- m256_add_dpbusd_epi32(sum0, in, row0[j]);
- m256_add_dpbusd_epi32(sum1, in, row1[j]);
- m256_add_dpbusd_epi32(sum2, in, row2[j]);
- m256_add_dpbusd_epi32(sum3, in, row3[j]);
-#else
- sum0 = _mm256_add_epi32(sum0, m256_dpbusd_epi32(in, row0[j]));
- sum1 = _mm256_add_epi32(sum1, m256_dpbusd_epi32(in, row1[j]));
- sum2 = _mm256_add_epi32(sum2, m256_dpbusd_epi32(in, row2[j]));
- sum3 = _mm256_add_epi32(sum3, m256_dpbusd_epi32(in, row3[j]));
-#endif
+ m256_add_dpbusd_epi32(sum0, in, row0[j]);
+ m256_add_dpbusd_epi32(sum1, in, row1[j]);
+ m256_add_dpbusd_epi32(sum2, in, row2[j]);
+ m256_add_dpbusd_epi32(sum3, in, row3[j]);
}
*outptr = m256_haddx4(sum0, sum1, sum2, sum3, bias);
}
else if constexpr (kOutputDimensions == 1)
{
- const auto row0 = reinterpret_cast<const __m256i*>(&weights_[0]);
-
-#if defined (USE_VNNI)
__m256i sum0 = _mm256_setzero_si256();
- const IndexType kStart = 0;
-#else
- __m256i sum0 = m256_dpbusd_epi32(input_vector[0], row0[0]);
- const IndexType kStart = 1;
-#endif
- for (IndexType j = kStart; j < kNumChunks; ++j)
+ const auto row0 = reinterpret_cast<const __m256i*>(&weights_[0]);
+
+ for (IndexType j = 0; j < kNumChunks; ++j)
{
- const __m256i in = input_vector[j];
+ const __m256i in = input_vector[j];
-#if defined (USE_VNNI)
- m256_add_dpbusd_epi32(sum0, in, row0[j]);
-#else
- sum0 = _mm256_add_epi32(sum0, m256_dpbusd_epi32(in, row0[j]));
-#endif
+ m256_add_dpbusd_epi32(sum0, in, row0[j]);
}
output[0] = m256_hadd(sum0, biases_[0]);
const __m128i bias = *reinterpret_cast<const __m128i*>(&biases_[i]);
__m128i* outptr = reinterpret_cast<__m128i*>(&output[i]);
+ __m128i sum0 = _mm_setzero_si128();
+ __m128i sum1 = _mm_setzero_si128();
+ __m128i sum2 = _mm_setzero_si128();
+ __m128i sum3 = _mm_setzero_si128();
+
const auto row0 = reinterpret_cast<const __m128i*>(&weights_[offset0]);
const auto row1 = reinterpret_cast<const __m128i*>(&weights_[offset1]);
const auto row2 = reinterpret_cast<const __m128i*>(&weights_[offset2]);
const auto row3 = reinterpret_cast<const __m128i*>(&weights_[offset3]);
- __m128i sum0 = m128_dpbusd_epi32(input_vector[0], row0[0]);
- __m128i sum1 = m128_dpbusd_epi32(input_vector[0], row1[0]);
- __m128i sum2 = m128_dpbusd_epi32(input_vector[0], row2[0]);
- __m128i sum3 = m128_dpbusd_epi32(input_vector[0], row3[0]);
-
- for (int j = 1; j < (int)kNumChunks; ++j)
+ int j = 0;
+ if (!canSaturate16x4[i / 4])
+ {
+ for (; j < (int)kNumChunks - 1; j += 2)
+ {
+ const __m128i in0 = input_vector[j];
+ const __m128i in1 = input_vector[j + 1];
+
+ m128_add_dpbusd_epi32x2(sum0, in0, row0[j], in1, row0[j + 1]);
+ m128_add_dpbusd_epi32x2(sum1, in0, row1[j], in1, row1[j + 1]);
+ m128_add_dpbusd_epi32x2(sum2, in0, row2[j], in1, row2[j + 1]);
+ m128_add_dpbusd_epi32x2(sum3, in0, row3[j], in1, row3[j + 1]);
+ }
+ }
+ for (; j < (int)kNumChunks; ++j)
{
- const __m128i in = input_vector[j];
+ const __m128i in = input_vector[j];
- sum0 = _mm_add_epi32(sum0, m128_dpbusd_epi32(in, row0[j]));
- sum1 = _mm_add_epi32(sum1, m128_dpbusd_epi32(in, row1[j]));
- sum2 = _mm_add_epi32(sum2, m128_dpbusd_epi32(in, row2[j]));
- sum3 = _mm_add_epi32(sum3, m128_dpbusd_epi32(in, row3[j]));
+ m128_add_dpbusd_epi32(sum0, in, row0[j]);
+ m128_add_dpbusd_epi32(sum1, in, row1[j]);
+ m128_add_dpbusd_epi32(sum2, in, row2[j]);
+ m128_add_dpbusd_epi32(sum3, in, row3[j]);
}
*outptr = m128_haddx4(sum0, sum1, sum2, sum3, bias);
}
else if constexpr (kOutputDimensions == 1)
{
+ __m128i sum0 = _mm_setzero_si128();
+
const auto row0 = reinterpret_cast<const __m128i*>(&weights_[0]);
- __m128i sum0 = m128_dpbusd_epi32(input_vector[0], row0[0]);
+ for (int j = 0; j < (int)kNumChunks; ++j)
+ {
+ const __m128i in = input_vector[j];
- for (int j = 1; j < (int)kNumChunks; ++j)
- sum0 = _mm_add_epi32(sum0, m128_dpbusd_epi32(input_vector[j], row0[j]));
+ m128_add_dpbusd_epi32(sum0, in, row0[j]);
+ }
output[0] = m128_hadd(sum0, biases_[0]);
}
PreviousLayer previous_layer_;
alignas(kCacheLineSize) BiasType biases_[kOutputDimensions];
- alignas(kCacheLineSize)
- WeightType weights_[kOutputDimensions * kPaddedInputDimensions];
+ alignas(kCacheLineSize) WeightType weights_[kOutputDimensions * kPaddedInputDimensions];
+ union {
+ uint32_t canSaturate16x4[(kOutputDimensions + 3) / 4];
+ bool canSaturate16[kOutputDimensions];
+ };
};
} // namespace Eval::NNUE::Layers
projects / stockfish / blobdiff