in src/QuantUtilsAvx2.cc [1142:1416]
void requantizeOutputProcessingGConvAvx2(
uint8_t* out,
const int32_t* inp,
const block_type_t& block,
int ld_out,
int ld_in,
const requantizationParams_t<BIAS_TYPE>& r) {
// Adoption of implementation at QNNPACK/src/requantization/fp32-sse2.c
// using AVX2 instructions
int quant_param_idx = 0;
if (Q_GRAN == QuantizationGranularity::GROUP) {
int ncol_per_group = r.ncols / r.groups;
int g = block.col_start / ncol_per_group;
quant_param_idx = g;
}
__m256 multiplier_v = _mm256_set1_ps(r.C_multiplier[quant_param_idx]);
// Broadcasted reciprocal of act_times_w_scale
__m256 act_times_w_rcp_v;
if (!(Q_GRAN == QuantizationGranularity::OUT_CHANNEL)) {
if (is_same<BIAS_TYPE, float>::value) {
act_times_w_rcp_v =
_mm256_set1_ps(1.0 / r.act_times_w_scale[quant_param_idx]);
}
}
__m256i min_v = _mm256_set1_epi8(static_cast<uint8_t>(0));
__m256i max_v = _mm256_set1_epi8(static_cast<uint8_t>(255));
assert(
(A_SYMMETRIC == (r.A_zero_point == 0)) &&
"A_SYMMETRIC == true if and only if A_zero_point == 0");
assert(
(B_SYMMETRIC ==
((Q_GRAN == QuantizationGranularity::TENSOR && r.B_zero_point[0] == 0) ||
r.row_offsets == nullptr)) &&
"B_SYMMETRIC == true if and only if B_zero_point == 0 "
"or r.row_offsets == nullptr");
assert(
(HAS_BIAS == (r.bias != nullptr)) &&
"HAS_BIAS == true if and only if bias != nullptr");
__m256i A_zero_point_v = _mm256_set1_epi32(r.A_zero_point);
__m256i C_zero_point_epi16_v = _mm256_set1_epi16(r.C_zero_point);
__m256i C_zero_point_epi8_v = _mm256_set1_epi8(r.C_zero_point);
__m256i permute_mask_v =
_mm256_set_epi32(0x07, 0x03, 0x06, 0x02, 0x05, 0x01, 0x04, 0x00);
constexpr int VLEN = 8;
for (int i = block.row_start; i < block.row_start + block.row_size; ++i) {
int j = block.col_start;
for (; j < block.col_start + (block.col_size / VLEN * VLEN); j += VLEN) {
__m256i x_v = _mm256_loadu_si256(reinterpret_cast<const __m256i*>(
inp + (i - block.row_start) * ld_in + (j - block.col_start)));
if (!A_SYMMETRIC) {
__m256i col_off_v = _mm256_mullo_epi32(
A_zero_point_v,
_mm256_loadu_si256(
reinterpret_cast<const __m256i*>(r.col_offsets + j)));
x_v = _mm256_sub_epi32(x_v, col_off_v);
}
if (!B_SYMMETRIC) {
__m256i row_offset_v;
if (C_PER_G == 2) {
// When C_PER_G == 2, we need to handle 4 groups at a time to fully
// utilize 32B AVX2 vector register (C_PER_G * 4 * sizeof(int32_t) ==
// 32B)
// Load row_offsets for 4 groups and broadcast by 2 times.
row_offset_v =
_mm256_castps_si256(_mm256_moveldup_ps(_mm256_permutevar8x32_ps(
_mm256_castps128_ps256(
_mm_loadu_ps(reinterpret_cast<const float*>(
r.row_offsets + (i - block.row_start) * 4))),
permute_mask_v)));
}
// When C_PER_G == 4, we need to handle 2 groups at a time to fully
// utilize 32B AVX2 vector register (C_PER_G * 2 * sizeof(int32_t) ==
// 32B)
// When C_PER_G == 8, we just need 1 group at a time on the other hand.
// Groups 0 and 1 when C_PER_G == 4
// Group 0 when C_PER_G == 8
else if (C_PER_G == 4) {
// Load row_offsets for 2 groups and broadcast by 4 times each because
// we have 4 channels per group.
// groups 0 and 1
row_offset_v = _mm256_insertf128_si256(
_mm256_castsi128_si256(
_mm_set1_epi32(r.row_offsets[(i - block.row_start) * 2 + 0])),
_mm_set1_epi32(r.row_offsets[(i - block.row_start) * 2 + 1]),
1);
} else if (C_PER_G == 8) {
row_offset_v =
_mm256_set1_epi32(r.row_offsets[(i - block.row_start)]);
} else {
assert(C_PER_G == 16);
row_offset_v =
_mm256_set1_epi32(r.row_offsets[(i - block.row_start)]);
}
__m256i B_zero_point_v = _mm256_set1_epi32(r.B_zero_point[0]);
if (Q_GRAN == QuantizationGranularity::OUT_CHANNEL) {
B_zero_point_v = _mm256_loadu_si256(
reinterpret_cast<const __m256i*>(r.B_zero_point + j));
} else if (Q_GRAN == QuantizationGranularity::GROUP) {
if (C_PER_G == 2) {
B_zero_point_v =
_mm256_castps_si256(_mm256_moveldup_ps(_mm256_permutevar8x32_ps(
_mm256_castps128_ps256(
_mm_loadu_ps(reinterpret_cast<const float*>(
r.B_zero_point + quant_param_idx))),
permute_mask_v)));
} else if (C_PER_G == 4) {
B_zero_point_v = _mm256_insertf128_si256(
_mm256_castsi128_si256(
_mm_set1_epi32(r.B_zero_point[quant_param_idx])),
_mm_set1_epi32(r.B_zero_point[quant_param_idx + 1]),
1);
} else if (C_PER_G == 8) {
B_zero_point_v = _mm256_set1_epi32(r.B_zero_point[quant_param_idx]);
} else {
B_zero_point_v = _mm256_set1_epi32(r.B_zero_point[quant_param_idx]);
}
}
row_offset_v = _mm256_mullo_epi32(row_offset_v, B_zero_point_v);
x_v = _mm256_sub_epi32(x_v, row_offset_v);
}
__m256 xf_v;
if (HAS_BIAS) {
if (is_same<BIAS_TYPE, float>::value) {
__m256 x_bias_v =
_mm256_loadu_ps(reinterpret_cast<const float*>(r.bias + j));
if (Q_GRAN == QuantizationGranularity::OUT_CHANNEL) {
x_bias_v = _mm256_div_ps(
x_bias_v, _mm256_loadu_ps(r.act_times_w_scale + j));
} else if (Q_GRAN == QuantizationGranularity::GROUP) {
__m256 diviser_v;
if (C_PER_G == 2) {
diviser_v = _mm256_moveldup_ps(_mm256_permutevar8x32_ps(
_mm256_castps128_ps256(
_mm_loadu_ps(r.act_times_w_scale + quant_param_idx)),
permute_mask_v));
} else if (C_PER_G == 4) {
diviser_v = _mm256_insertf128_ps(
_mm256_castps128_ps256(
_mm_set1_ps(r.act_times_w_scale[quant_param_idx + 0])),
_mm_set1_ps(r.act_times_w_scale[quant_param_idx + 1]),
1);
} else if (C_PER_G == 8) {
diviser_v = _mm256_set1_ps(r.act_times_w_scale[quant_param_idx]);
} else {
assert(C_PER_G == 16);
diviser_v = _mm256_set1_ps(r.act_times_w_scale[quant_param_idx]);
}
x_bias_v = _mm256_div_ps(x_bias_v, diviser_v);
} else {
x_bias_v = _mm256_mul_ps(x_bias_v, act_times_w_rcp_v);
}
xf_v = _mm256_add_ps(_mm256_cvtepi32_ps(x_v), x_bias_v);
} else {
x_v = _mm256_add_epi32(
x_v,
_mm256_loadu_si256(reinterpret_cast<const __m256i*>(r.bias + j)));
xf_v = _mm256_cvtepi32_ps(x_v);
}
} else {
xf_v = _mm256_cvtepi32_ps(x_v);
}
/*
* Convert int32_t input to FP32 and multiply by FP32 scale.
* Both operations involve statistically unbiased roundings (with
* default MXCSR rounding mode):
* - Large int32_t values can't be exactly represented as FP32.
* CVTDQ2PS instruction on x86 would round it according to nearest
* FP32 value with ties to even (assuming default MXCSR rounding
* mode).
* - Product of two FP32 values is generally not exactly
* representation as an FP32 value, and will be rounded to nearest
* FP32 value with ties to even with default MXCSR rounding mode.
*/
__m256 x_scaled_v;
if (Q_GRAN == QuantizationGranularity::OUT_CHANNEL) {
x_scaled_v = _mm256_mul_ps(xf_v, _mm256_loadu_ps(r.C_multiplier + j));
} else if (Q_GRAN == QuantizationGranularity::GROUP) {
if (C_PER_G == 2) {
multiplier_v = _mm256_moveldup_ps(_mm256_permutevar8x32_ps(
_mm256_castps128_ps256(
_mm_loadu_ps(r.C_multiplier + quant_param_idx)),
permute_mask_v));
} else if (C_PER_G == 4) {
multiplier_v = _mm256_insertf128_ps(
_mm256_castps128_ps256(
_mm_set1_ps(r.C_multiplier[quant_param_idx])),
_mm_set1_ps(r.C_multiplier[quant_param_idx + 1]),
1);
} else if (C_PER_G == 8) {
multiplier_v = _mm256_set1_ps(r.C_multiplier[quant_param_idx]);
} else {
multiplier_v = _mm256_set1_ps(r.C_multiplier[quant_param_idx]);
}
x_scaled_v = _mm256_mul_ps(xf_v, multiplier_v);
} else {
x_scaled_v = _mm256_mul_ps(xf_v, multiplier_v);
}
/*
* Convert scaled FP32 result to int32_t using CVTPS2DQ instruction.
* CVTPS2DQ instruction rounds result according to nearest FP32 value
* with ties to even (assuming default MXCSR rounding mode). However,
* when conversion overflows, it produces INT32_MIN as a result. For
* large positive inputs the result of conversion can become negative,
* which affects the final requantization result. Note that on x86
* SSE2 we have e.g. int32_t(float(INT32_MAX)) == INT32_MIN! This
* happens because float(INT32_MAX) rounds to 2**31, which overflows
* int32_t when it is converted back to integer.
*
* Thankfully, we can prove that overflow never happens in this
* requantization scheme. The largest positive input is INT32_MAX
* (2**31 - 1), which turns into 2**31 when converted to float. The
* largest scale value is 0x1.FFFFFEp-1. When multiplied together, the
* result is 2147483520 (compare to INT32_MAX = 2147483647), which
* fits into int32_t without overflow.
*/
__m256i x_rounded_v = _mm256_cvtps_epi32(x_scaled_v);
/*
* Standard final sequence on x86 AVX2:
* - Pack to int16_t and saturate
* - Add zero point
* - Pack to uint8_t and saturate
* - Clamp between qmin and qmax
*/
__m256i x_packed_v = _mm256_adds_epi16(
_mm256_packs_epi32(x_rounded_v, _mm256_setzero_si256()),
C_zero_point_epi16_v);
x_packed_v = _mm256_packus_epi16(x_packed_v, _mm256_setzero_si256());
__m256i x_clamped_v = _mm256_max_epu8(
FUSE_RELU ? C_zero_point_epi8_v : min_v,
_mm256_min_epu8(x_packed_v, max_v));
/*
* x_clamped_v has results in the following layout so we need to
* permute: x0-3 garbage0-11 x4-7 garbage12-23
*/
x_clamped_v = _mm256_permutevar8x32_epi32(x_clamped_v, permute_mask_v);
/*
* 1x CVTDQ2PS
* 1x MULPS
* 1x CVTPS2DQ
* 1x PACKSSDW
* 1x PACKUSWB
* 1x PADDW
* 1x PMAXUB
* 1x PMINUB
* 1x PERMD
* ---------------------
* 9 instructions total
*/
_mm_storel_epi64(
reinterpret_cast<__m128i*>(out + i * ld_out + j),
_mm256_castsi256_si128(x_clamped_v));
} // j loop vectorized
const int remainder = block.col_start + block.col_size - j;
(void)remainder; // Suppress unused variable warning
assert(remainder == 0);
} // i loop
}