From 5a47c46b39475fc3581b9819f488b977ea1beca3 Mon Sep 17 00:00:00 2001
From: Edmond Yoo <hj3yoo@uwaterloo.ca>
Date: Sun, 16 Sep 2018 03:11:04 +0000
Subject: [PATCH] Moving files from MTGCardDetector
---
src/gemm.c | 1168 ++++++++++++++++++++++++++++++++++++++++++++++++++++++---
1 files changed, 1,091 insertions(+), 77 deletions(-)
diff --git a/src/gemm.c b/src/gemm.c
index ff5edfa..6ff57cd 100644
--- a/src/gemm.c
+++ b/src/gemm.c
@@ -5,6 +5,8 @@
#include <stdlib.h>
#include <stdio.h>
#include <math.h>
+#include <float.h>
+#include <string.h>
#if defined(_OPENMP)
#include <omp.h>
@@ -304,13 +306,84 @@
//----------------------------
-#if (defined(__AVX__) && defined(__x86_64__)) || defined(_WIN64)
+void transpose_8x8_bits_my(unsigned char *A, unsigned char *B, int lda, int ldb)
+{
+ unsigned x, y, t;
+ for (y = 0; y < 8; ++y) {
+ for (x = 0; x < 8; ++x) {
+ if (A[y * lda] & (1 << x)) B[x * ldb] |= 1 << y;
+ }
+ }
+}
-#define OSXSAVEFlag (1UL<<27)
-#define AVXFlag ((1UL<<28)|OSXSAVEFlag)
-#define FMAFlag ((1UL<<12)|AVXFlag|OSXSAVEFlag)
-#define CLMULFlag ((1UL<< 1)|AVXFlag|OSXSAVEFlag)
-#define VAESFlag ((1UL<<25)|AVXFlag|OSXSAVEFlag)
+unsigned char reverse_byte_1(char a)
+{
+ return ((a & 0x1) << 7) | ((a & 0x2) << 5) |
+ ((a & 0x4) << 3) | ((a & 0x8) << 1) |
+ ((a & 0x10) >> 1) | ((a & 0x20) >> 3) |
+ ((a & 0x40) >> 5) | ((a & 0x80) >> 7);
+}
+
+unsigned char reverse_byte_2(unsigned char a)
+{
+ return ((a * 0x0802LU & 0x22110LU) | (a * 0x8020LU & 0x88440LU)) * 0x10101LU >> 16;
+}
+
+static unsigned char lookup[16] = {
+ 0x0, 0x8, 0x4, 0xc, 0x2, 0xa, 0x6, 0xe,
+ 0x1, 0x9, 0x5, 0xd, 0x3, 0xb, 0x7, 0xf, };
+
+unsigned char reverse_byte(unsigned char n) {
+ // Reverse the top and bottom nibble then swap them.
+ return (lookup[n & 0b1111] << 4) | lookup[n >> 4];
+}
+
+
+void transpose8rS32_reversed_diagonale(unsigned char* A, int m, int n, unsigned char* B)
+{
+ unsigned x, y, t;
+
+ // Load the array and pack it into x and y.
+ x = (A[0] << 24) | (A[m] << 16) | (A[2 * m] << 8) | A[3 * m];
+ y = (A[4 * m] << 24) | (A[5 * m] << 16) | (A[6 * m] << 8) | A[7 * m];
+
+ t = (x ^ (x >> 7)) & 0x00AA00AA; x = x ^ t ^ (t << 7);
+ t = (y ^ (y >> 7)) & 0x00AA00AA; y = y ^ t ^ (t << 7);
+
+ t = (x ^ (x >> 14)) & 0x0000CCCC; x = x ^ t ^ (t << 14);
+ t = (y ^ (y >> 14)) & 0x0000CCCC; y = y ^ t ^ (t << 14);
+
+ t = (x & 0xF0F0F0F0) | ((y >> 4) & 0x0F0F0F0F);
+ y = ((x << 4) & 0xF0F0F0F0) | (y & 0x0F0F0F0F);
+ x = t;
+
+ B[7 * n] = reverse_byte(x >> 24); B[6 * n] = reverse_byte(x >> 16); B[5 * n] = reverse_byte(x >> 8); B[4 * n] = reverse_byte(x);
+ B[3 * n] = reverse_byte(y >> 24); B[2 * n] = reverse_byte(y >> 16); B[1 * n] = reverse_byte(y >> 8); B[0 * n] = reverse_byte(y);
+}
+
+void transpose_bin(char *A, char *B, const int n, const int m,
+ const int lda, const int ldb, const int block_size)
+{
+ int i;
+#pragma omp parallel for
+ for (i = 0; i < n; i += 8) {
+ int j;
+ for (j = 0; j < m - 8; j += 8) {
+ int a_index = i*lda + j;
+ int b_index = j*ldb + i;
+ //transpose_8x8_bits_my(&A[a_index/8], &B[b_index/8], lda/8, ldb/8);
+ transpose8rS32_reversed_diagonale(&A[a_index / 8], lda / 8, ldb / 8, &B[b_index / 8]);
+ }
+ for (; j < m; ++j) {
+ if (get_bit(A, i*lda + j)) set_bit(B, j*ldb + i);
+ }
+ }
+}
+
+//----------------------------
+
+
+#if (defined(__AVX__) && defined(__x86_64__)) || defined(_WIN64)
#ifdef _WIN64
#include <intrin.h>
@@ -318,6 +391,24 @@
#include <immintrin.h>
#include <smmintrin.h>
+#if defined(_MSC_VER) && _MSC_VER <= 1900
+static inline __int32 _mm256_extract_epi64(__m256i a, const int index) {
+ return a.m256i_i64[index];
+}
+
+static inline __int32 _mm256_extract_epi32(__m256i a, const int index) {
+ return a.m256i_i32[index];
+}
+#endif
+
+static inline float _castu32_f32(uint32_t a) {
+ return *((float *)&a);
+}
+
+static inline float _mm256_extract_float32(__m256 a, const int index) {
+ return a.m256_f32[index];
+}
+
#else // Linux GCC/Clang
#include <x86intrin.h>
#include <ammintrin.h>
@@ -325,6 +416,14 @@
#include <smmintrin.h>
#include <cpuid.h>
+static inline float _castu32_f32(uint32_t a) {
+ return *((float *)&a);
+}
+
+static inline float _mm256_extract_float32(__m256 a, const int index) {
+ return _castu32_f32(_mm256_extract_epi32(_mm256_castps_si256(a), index));
+}
+
void asm_cpuid(uint32_t* abcd, uint32_t eax)
{
uint32_t ebx = 0, edx = 0, ecx = 0;
@@ -341,35 +440,121 @@
abcd[2] = ecx;
abcd[3] = edx;
}
-
#endif
-int simd_detect_x86(unsigned int idFeature)
-{
- uint32_t regs[4]; // EAX, EBX, ECX, EDX;
+
+
#ifdef _WIN32
- __cpuid(regs, 0);
- if (regs[0] > 1U) __cpuid(regs, 1);
+// Windows
+#define cpuid(info, x) __cpuidex(info, x, 0)
#else
- __get_cpuid(0, ®s[0], ®s[1], ®s[2], ®s[3]);
- if(regs[0] > 1U) __get_cpuid(1, ®s[0], ®s[1], ®s[2], ®s[3]);
+// GCC Intrinsics
+void cpuid(int info[4], int InfoType) {
+ __cpuid_count(InfoType, 0, info[0], info[1], info[2], info[3]);
+}
#endif
- if ((regs[2] & idFeature) != idFeature)
- return 0;
- return 1;
+
+// Misc.
+static int HW_MMX, HW_x64, HW_RDRAND, HW_BMI1, HW_BMI2, HW_ADX, HW_PREFETCHWT1;
+static int HW_ABM; // Advanced Bit Manipulation
+
+// SIMD: 128-bit
+static int HW_SSE, HW_SSE2, HW_SSE3, HW_SSSE3, HW_SSE41, HW_SSE42, HW_SSE4a, HW_AES, HW_SHA;
+
+// SIMD: 256-bit
+static int HW_AVX, HW_XOP, HW_FMA3, HW_FMA4, HW_AVX2;
+
+// SIMD: 512-bit
+static int HW_AVX512F; // AVX512 Foundation
+static int HW_AVX512CD; // AVX512 Conflict Detection
+static int HW_AVX512PF; // AVX512 Prefetch
+static int HW_AVX512ER; // AVX512 Exponential + Reciprocal
+static int HW_AVX512VL; // AVX512 Vector Length Extensions
+static int HW_AVX512BW; // AVX512 Byte + Word
+static int HW_AVX512DQ; // AVX512 Doubleword + Quadword
+static int HW_AVX512IFMA; // AVX512 Integer 52-bit Fused Multiply-Add
+static int HW_AVX512VBMI; // AVX512 Vector Byte Manipulation Instructions
+
+// https://stackoverflow.com/questions/6121792/how-to-check-if-a-cpu-supports-the-sse3-instruction-set
+void check_cpu_features(void) {
+ int info[4];
+ cpuid(info, 0);
+ int nIds = info[0];
+
+ cpuid(info, 0x80000000);
+ unsigned nExIds = info[0];
+
+ // Detect Features
+ if (nIds >= 0x00000001) {
+ cpuid(info, 0x00000001);
+ HW_MMX = (info[3] & ((int)1 << 23)) != 0;
+ HW_SSE = (info[3] & ((int)1 << 25)) != 0;
+ HW_SSE2 = (info[3] & ((int)1 << 26)) != 0;
+ HW_SSE3 = (info[2] & ((int)1 << 0)) != 0;
+
+ HW_SSSE3 = (info[2] & ((int)1 << 9)) != 0;
+ HW_SSE41 = (info[2] & ((int)1 << 19)) != 0;
+ HW_SSE42 = (info[2] & ((int)1 << 20)) != 0;
+ HW_AES = (info[2] & ((int)1 << 25)) != 0;
+
+ HW_AVX = (info[2] & ((int)1 << 28)) != 0;
+ HW_FMA3 = (info[2] & ((int)1 << 12)) != 0;
+
+ HW_RDRAND = (info[2] & ((int)1 << 30)) != 0;
+ }
+ if (nIds >= 0x00000007) {
+ cpuid(info, 0x00000007);
+ HW_AVX2 = (info[1] & ((int)1 << 5)) != 0;
+
+ HW_BMI1 = (info[1] & ((int)1 << 3)) != 0;
+ HW_BMI2 = (info[1] & ((int)1 << 8)) != 0;
+ HW_ADX = (info[1] & ((int)1 << 19)) != 0;
+ HW_SHA = (info[1] & ((int)1 << 29)) != 0;
+ HW_PREFETCHWT1 = (info[2] & ((int)1 << 0)) != 0;
+
+ HW_AVX512F = (info[1] & ((int)1 << 16)) != 0;
+ HW_AVX512CD = (info[1] & ((int)1 << 28)) != 0;
+ HW_AVX512PF = (info[1] & ((int)1 << 26)) != 0;
+ HW_AVX512ER = (info[1] & ((int)1 << 27)) != 0;
+ HW_AVX512VL = (info[1] & ((int)1 << 31)) != 0;
+ HW_AVX512BW = (info[1] & ((int)1 << 30)) != 0;
+ HW_AVX512DQ = (info[1] & ((int)1 << 17)) != 0;
+ HW_AVX512IFMA = (info[1] & ((int)1 << 21)) != 0;
+ HW_AVX512VBMI = (info[2] & ((int)1 << 1)) != 0;
+ }
+ if (nExIds >= 0x80000001) {
+ cpuid(info, 0x80000001);
+ HW_x64 = (info[3] & ((int)1 << 29)) != 0;
+ HW_ABM = (info[2] & ((int)1 << 5)) != 0;
+ HW_SSE4a = (info[2] & ((int)1 << 6)) != 0;
+ HW_FMA4 = (info[2] & ((int)1 << 16)) != 0;
+ HW_XOP = (info[2] & ((int)1 << 11)) != 0;
+ }
}
-int is_fma_avx() {
+int is_avx() {
static int result = -1;
if (result == -1) {
- result = simd_detect_x86(AVXFlag);
+ check_cpu_features();
+ result = HW_AVX;
if (result == 1) printf(" Used AVX \n");
else printf(" Not used AVX \n");
}
return result;
}
+int is_fma_avx2() {
+ static int result = -1;
+ if (result == -1) {
+ check_cpu_features();
+ result = HW_FMA3 && HW_AVX2;
+ if (result == 1) printf(" Used FMA & AVX2 \n");
+ else printf(" Not used FMA & AVX2 \n");
+ }
+ return result;
+}
+
// https://software.intel.com/sites/landingpage/IntrinsicsGuide
void gemm_nn(int M, int N, int K, float ALPHA,
float *A, int lda,
@@ -377,7 +562,7 @@
float *C, int ldc)
{
int i, j, k;
- if (is_fma_avx() == 1) { // AVX
+ if (is_avx() == 1) { // AVX
for (i = 0; i < M; ++i) {
for (k = 0; k < K; ++k) {
float A_PART = ALPHA*A[i*lda + k];
@@ -429,6 +614,180 @@
}
+void convolution_2d_old(int w, int h, int ksize, int n, int c, int pad, int stride,
+ float *weights, float *input, float *output)
+{
+ int out_h = (h + 2 * pad - ksize) / stride + 1; // output_height=input_height for stride=1 and pad=1
+ int out_w = (w + 2 * pad - ksize) / stride + 1; // output_width=input_width for stride=1 and pad=1
+ int i, f, j;
+
+ int fil;
+ // filter index
+#pragma omp parallel for // "omp parallel for" - automatic parallelization of loop by using OpenMP
+ for (fil = 0; fil < n; ++fil) {
+ int chan, y, x, f_y, f_x;
+ // channel index
+ for (chan = 0; chan < c; ++chan)
+ // input - y
+ for (y = 0; y < h; ++y)
+ // input - x
+ for (x = 0; x < w; ++x)
+ {
+ int const output_index = fil*w*h + y*w + x;
+ int const weights_pre_index = fil*c*ksize*ksize + chan*ksize*ksize;
+ int const input_pre_index = chan*w*h;
+ float sum = 0;
+
+ // filter - y
+ for (f_y = 0; f_y < ksize; ++f_y)
+ {
+ int input_y = y + f_y - pad;
+ // filter - x
+ for (f_x = 0; f_x < ksize; ++f_x)
+ {
+ int input_x = x + f_x - pad;
+ if (input_y < 0 || input_x < 0 || input_y >= h || input_x >= w) continue;
+
+ int input_index = input_pre_index + input_y*w + input_x;
+ int weights_index = weights_pre_index + f_y*ksize + f_x;
+
+ sum += input[input_index] * weights[weights_index];
+ }
+ }
+ // l.output[filters][width][height] +=
+ // state.input[channels][width][height] *
+ // l.weights[filters][channels][filter_width][filter_height];
+ output[output_index] += sum;
+ }
+ }
+}
+
+void convolution_2d(int w, int h, int ksize, int n, int c, int pad, int stride,
+ float *weights, float *input, float *output, float *mean)
+{
+ int out_h = (h + 2 * pad - ksize) / stride + 1; // output_height=input_height for stride=1 and pad=1
+ int out_w = (w + 2 * pad - ksize) / stride + 1; // output_width=input_width for stride=1 and pad=1
+ int i, f, j;
+
+#if defined(_OPENMP)
+ static int max_num_threads = 0;
+ if (max_num_threads == 0) {
+ max_num_threads = omp_get_max_threads();
+ //omp_set_num_threads( max_num_threads / 2);
+ }
+#endif
+
+ //convolution_2d_old(w, h, ksize, n, c, pad, stride, weights, input, output);
+
+ __m256i all256_sing1 = _mm256_set_epi32(0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000);
+ for (i = 0; i < ksize*ksize*n*c; i+=8) {
+ *((__m256*)&weights[i]) = _mm256_and_ps(*((__m256*)&weights[i]), _mm256_castsi256_ps(all256_sing1));
+ }
+
+ for (i = 0; i < w*h*c; i += 8) {
+ //*((__m256*)&input[i]) = _mm256_and_ps(*((__m256*)&input[i]), _mm256_castsi256_ps(all256_sing1));
+ }
+
+
+ //__m256i all256_last_zero = _mm256_set1_epi32(0xFFFFFFFF);
+ //all256_last_zero.m256i_i32[7] = 0;
+ __m256i all256_last_zero =
+ _mm256_set_epi32(0xFFFFFFFF, 0xFFFFFFFF, 0xFFFFFFFF, 0xFFFFFFFF, 0xFFFFFFFF, 0xFFFFFFFF, 0xFFFFFFFF, 0x0);
+
+ __m256i idx256 = _mm256_set_epi32(0, 7, 6, 5, 4, 3, 2, 1);
+ //__m256 all256_sing1 = _mm256_set1_ps(0x80000000);
+ __m256 all256_one = _mm256_set1_ps(1);
+ __m256i all256i_one = _mm256_set1_epi32(1);
+
+ ///__m256i src256 = _mm256_loadu_si256((__m256i *)(&src[i]));
+ ///__m256i result256 = _mm256_and_si256(src256, all256_sing1); // check sign in 8 x 32-bit floats
+
+ int fil;
+ // filter index
+#pragma omp parallel for // "omp parallel for" - automatic parallelization of loop by using OpenMP
+ for (fil = 0; fil < n; ++fil) {
+ int chan, y, x, f_y, f_x;
+ float cur_mean = fabs(mean[fil]);
+ __m256 mean256 = _mm256_set1_ps(cur_mean);
+ // channel index
+ //for (chan = 0; chan < c; ++chan)
+ // input - y
+ for (y = 0; y < h; ++y)
+ // input - x
+ for (x = 0; x < w-8; x+=8)
+ {
+ int const output_index = fil*w*h + y*w + x;
+ float sum = 0;
+ __m256 sum256 = _mm256_set1_ps(0);
+
+ for (chan = 0; chan < c; ++chan) {
+ int const weights_pre_index = fil*c*ksize*ksize + chan*ksize*ksize;
+ int const input_pre_index = chan*w*h;
+
+
+ // filter - y
+ for (f_y = 0; f_y < ksize; ++f_y)
+ {
+ int input_y = y + f_y - pad;
+ //__m256 in = *((__m256*)&input[input_pre_index + input_y*w]);
+ if (input_y < 0 || input_y >= h) continue;
+ //__m256 in = _mm256_loadu_ps(&input[input_pre_index + input_y*w + x - pad]);
+
+ // filter - x
+ for (f_x = 0; f_x < ksize; ++f_x)
+ {
+ int input_x = x + f_x - pad;
+ //if (input_y < 0 || input_x < 0 || input_y >= h || input_x >= w) continue;
+
+ int input_index = input_pre_index + input_y*w + input_x;
+ int weights_index = weights_pre_index + f_y*ksize + f_x;
+ //if (input_y < 0 || input_y >= h) continue;
+
+ //sum += input[input_index] * weights[weights_index];
+
+ __m256 in = *((__m256*)&input[input_index]);
+ __m256 w = _mm256_set1_ps(weights[weights_index]);
+ //__m256 w_sign = _mm256_and_ps(w, _mm256_castsi256_ps(all256_sing1)); // check sign in 8 x 32-bit floats
+ __m256 xor256 = _mm256_xor_ps(w, in);
+ //printf("\n xor256_1 = %f, xor256_2 = %f \n", xor256.m256_f32[0], xor256.m256_f32[1]);
+ //printf("\n in = %f, w = %f, xor256 = %f \n", in.m256_f32[0], w_sign.m256_f32[0], xor256.m256_f32[0]);
+
+ //__m256 pn1 = _mm256_and_ps(_mm256_castsi256_ps(all256i_one), xor256);
+
+
+ //sum256 = xor256;
+ sum256 = _mm256_add_ps(xor256, sum256);
+ //printf("\n --- \n");
+ //printf("\n 0 = %f, 1 = %f, 2 = %f, 3 = %f, 4 = %f, 5 = %f, 6 = %f, 7 = %f \n", in.m256_f32[0], in.m256_f32[1], in.m256_f32[2], in.m256_f32[3], in.m256_f32[4], in.m256_f32[5], in.m256_f32[6], in.m256_f32[7]);
+
+ if (f_x < ksize-1) {
+ //in = _mm256_permutevar8x32_ps(in, idx256);
+ //in = _mm256_and_ps(in, _mm256_castsi256_ps(all256_last_zero));
+ }
+ }
+ }
+ }
+ // l.output[filters][width][height] +=
+ // state.input[channels][width][height] *
+ // l.weights[filters][channels][filter_width][filter_height];
+ //output[output_index] += sum;
+
+ sum256 = _mm256_mul_ps(sum256, mean256);
+ //printf("\n cur_mean = %f, sum256 = %f, sum256 = %f, in = %f \n",
+ // cur_mean, sum256.m256_f32[0], sum256.m256_f32[1], input[input_pre_index]);
+
+ //__m256 out = *((__m256*)&output[output_index]);
+ //out = _mm256_add_ps(out, sum256);
+ //*((__m256*)&output[output_index]) = out;
+ *((__m256*)&output[output_index]) = sum256;
+
+ //_mm256_storeu_ps(&C[i*ldc + j], result256);
+ }
+ }
+}
+
+
+
// http://graphics.stanford.edu/~seander/bithacks.html
// https://stackoverflow.com/questions/17354971/fast-counting-the-number-of-set-bits-in-m128i-register
// https://arxiv.org/pdf/1611.07612.pdf
@@ -466,12 +825,18 @@
static inline int popcnt256_custom(__m256i n) {
__m256i val = count256(n);
- return val.m256i_i64[0] +
- val.m256i_i64[1] +
- val.m256i_i64[2] +
- val.m256i_i64[3];
+ //return val.m256i_i64[0] +
+ //val.m256i_i64[1] +
+ //val.m256i_i64[2] +
+ //val.m256i_i64[3];
+ return _mm256_extract_epi64(val, 0)
+ + _mm256_extract_epi64(val, 1)
+ + _mm256_extract_epi64(val, 2)
+ + _mm256_extract_epi64(val, 3);
}
+// 5x times faster than gemm()-float32
+// further optimizations: do mean-mult only for the last layer
void gemm_nn_custom_bin_mean_transposed(int M, int N, int K, float ALPHA_UNUSED,
unsigned char *A, int lda,
unsigned char *B, int ldb,
@@ -483,7 +848,7 @@
static int max_num_threads = 0;
if (max_num_threads == 0) {
max_num_threads = omp_get_max_threads();
- omp_set_num_threads(max_num_threads / 2);
+ //omp_set_num_threads(max_num_threads / 2);
}
#endif
@@ -514,10 +879,14 @@
}
// count of 1 bits
- count = count_sum.m256i_i64[0] +
- count_sum.m256i_i64[1] +
- count_sum.m256i_i64[2] +
- count_sum.m256i_i64[3];
+ //count = count_sum.m256i_i64[0] +
+ // count_sum.m256i_i64[1] +
+ // count_sum.m256i_i64[2] +
+ // count_sum.m256i_i64[3];
+ count = _mm256_extract_epi64(count_sum, 0)
+ + _mm256_extract_epi64(count_sum, 1)
+ + _mm256_extract_epi64(count_sum, 2)
+ + _mm256_extract_epi64(count_sum, 3);
int f1 = (K % bit_step == 0) ? 0 : (bit_step - (K % bit_step));
count = count - f1; // remove extra bits (from empty space for align only)
@@ -541,6 +910,121 @@
//From Berkeley Vision's Caffe!
//https://github.com/BVLC/caffe/blob/master/LICENSE
+void im2col_cpu_custom_transpose(float* data_im,
+ int channels, int height, int width,
+ int ksize, int stride, int pad, float* data_col, int ldb_align)
+{
+ int c, h, w;
+ int height_col = (height + 2 * pad - ksize) / stride + 1;
+ int width_col = (width + 2 * pad - ksize) / stride + 1;
+ int channels_col = channels * ksize * ksize;
+
+ // optimized version
+ if (height_col == height && width_col == width && stride == 1 && pad == 1)
+ {
+#pragma omp parallel for
+ for (c = 0; c < channels_col; ++c) {
+ int w_offset = c % ksize;
+ int h_offset = (c / ksize) % ksize;
+ int c_im = c / ksize / ksize;
+ for (h = pad; h < height_col - pad; ++h) {
+ for (w = pad; w < width_col - pad - 4; w+=8) {
+ int im_row = h_offset + h - pad;
+ int im_col = w_offset + w - pad;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = (h * width_col + w)*ldb_align + c; // transposed & aligned
+
+ //data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)];
+ __m256 src256 = _mm256_loadu_ps((float *)(&data_im[im_col + width*(im_row + height*c_im)]));
+ data_col[col_index + ldb_align * 0] = _mm256_extract_float32(src256, 0);// src256.m256_f32[0];
+ data_col[col_index + ldb_align * 1] = _mm256_extract_float32(src256, 1);// src256.m256_f32[1];
+ data_col[col_index + ldb_align * 2] = _mm256_extract_float32(src256, 2);// src256.m256_f32[2];
+ data_col[col_index + ldb_align * 3] = _mm256_extract_float32(src256, 3);// src256.m256_f32[3];
+ data_col[col_index + ldb_align * 4] = _mm256_extract_float32(src256, 4);// src256.m256_f32[4];
+ data_col[col_index + ldb_align * 5] = _mm256_extract_float32(src256, 5);// src256.m256_f32[5];
+ data_col[col_index + ldb_align * 6] = _mm256_extract_float32(src256, 6);// src256.m256_f32[6];
+ data_col[col_index + ldb_align * 7] = _mm256_extract_float32(src256, 7);// src256.m256_f32[7];
+
+ //_mm256_storeu_ps(&data_col[col_index], src256);
+ }
+
+ for (; w < width_col - pad; ++w) {
+ int im_row = h_offset + h - pad;
+ int im_col = w_offset + w - pad;
+ int col_index = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)];
+ }
+ }
+
+ {
+ w = 0;
+ for (h = 0; h < height_col; ++h) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ int col_index = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ data_col[col_index] = im2col_get_pixel(data_im, height, width, channels,
+ im_row, im_col, c_im, pad);
+ }
+ }
+
+ {
+ w = width_col - 1;
+ for (h = 0; h < height_col; ++h) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ int col_index = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ data_col[col_index] = im2col_get_pixel(data_im, height, width, channels,
+ im_row, im_col, c_im, pad);
+ }
+ }
+
+ {
+ h = 0;
+ for (w = 0; w < width_col; ++w) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ int col_index = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ data_col[col_index] = im2col_get_pixel(data_im, height, width, channels,
+ im_row, im_col, c_im, pad);
+ }
+ }
+
+ {
+ h = height_col - 1;
+ for (w = 0; w < width_col; ++w) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ int col_index = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ data_col[col_index] = im2col_get_pixel(data_im, height, width, channels,
+ im_row, im_col, c_im, pad);
+ }
+ }
+ }
+
+ }
+ else {
+ #pragma omp parallel for
+ for (c = 0; c < channels_col; ++c) {
+ int w_offset = c % ksize;
+ int h_offset = (c / ksize) % ksize;
+ int c_im = c / ksize / ksize;
+ for (h = 0; h < height_col; ++h) {
+ for (w = 0; w < width_col; ++w) {
+ int im_row = h_offset + h * stride;
+ int im_col = w_offset + w * stride;
+
+ int col_index = (h * width_col + w)*ldb_align + c; // transposed & aligned
+ data_col[col_index] = im2col_get_pixel(data_im, height, width, channels,
+ im_row, im_col, c_im, pad);
+ }
+ }
+ }
+ }
+}
+
+
+//From Berkeley Vision's Caffe!
+//https://github.com/BVLC/caffe/blob/master/LICENSE
void im2col_cpu_custom(float* data_im,
int channels, int height, int width,
int ksize, int stride, int pad, float* data_col)
@@ -552,7 +1036,7 @@
int channels_col = channels * ksize * ksize;
// optimized version
- if (height_col == height && width_col == width && stride == 1 && pad == 1)
+ if (height_col == height && width_col == width && stride == 1 && pad == 1 && is_fma_avx2())
{
#pragma omp parallel for
for (c = 0; c < channels_col; ++c) {
@@ -566,7 +1050,7 @@
int col_index = (c * height_col + h) * width_col + w;
//data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)];
- __m256 src256 = _mm256_loadu_ps((__m256i *)(&data_im[im_col + width*(im_row + height*c_im)]));
+ __m256 src256 = _mm256_loadu_ps((float *)(&data_im[im_col + width*(im_row + height*c_im)]));
_mm256_storeu_ps(&data_col[col_index], src256);
}
@@ -631,26 +1115,248 @@
}
}
+//From Berkeley Vision's Caffe!
+//https://github.com/BVLC/caffe/blob/master/LICENSE
+void im2col_cpu_custom_align(float* data_im,
+ int channels, int height, int width,
+ int ksize, int stride, int pad, float* data_col, int bit_align)
+{
+ int c, h, w;
+ int height_col = (height + 2 * pad - ksize) / stride + 1;
+ int width_col = (width + 2 * pad - ksize) / stride + 1;
+ int channels_col = channels * ksize * ksize;
+
+ // optimized version
+ if (height_col == height && width_col == width && stride == 1 && pad == 1 && is_fma_avx2())
+ {
+ int new_ldb = bit_align;
+
+ #pragma omp parallel for
+ for (c = 0; c < channels_col; ++c) {
+ int w_offset = c % ksize;
+ int h_offset = (c / ksize) % ksize;
+ int c_im = c / ksize / ksize;
+ for (h = pad; h < height_col - pad; ++h) {
+ for (w = pad; w < width_col - pad - 8; w += 8) {
+ int im_row = h_offset + h - pad;
+ int im_col = w_offset + w - pad;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)];
+ __m256 src256 = _mm256_loadu_ps((float *)(&data_im[im_col + width*(im_row + height*c_im)]));
+ _mm256_storeu_ps(&data_col[col_index], src256);
+ }
+
+ for (; w < width_col - pad; ++w) {
+ int im_row = h_offset + h - pad;
+ int im_col = w_offset + w - pad;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+ data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)];
+ }
+ }
+
+ {
+ w = 0;
+ for (h = 0; h < height_col; ++h) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+ data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ }
+ }
+
+ {
+ w = width_col - 1;
+ for (h = 0; h < height_col; ++h) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+ data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ }
+ }
+
+ {
+ h = 0;
+ for (w = 0; w < width_col; ++w) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+ data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ }
+ }
+
+ {
+ h = height_col - 1;
+ for (w = 0; w < width_col; ++w) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+ data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ }
+ }
+ }
+
+ }
+ else {
+ printf("\n Error: is no non-optimized version \n");
+ //im2col_cpu(data_im, channels, height, width, ksize, stride, pad, data_col); // must be aligned for transpose after float_to_bin
+ // float_to_bit(b, t_input, src_size);
+ // transpose_bin(t_input, *t_bit_input, k, n, bit_align, new_ldb, 8);
+ }
+}
+
+
+//From Berkeley Vision's Caffe!
+//https://github.com/BVLC/caffe/blob/master/LICENSE
+void im2col_cpu_custom_bin(float* data_im,
+ int channels, int height, int width,
+ int ksize, int stride, int pad, float* data_col, int bit_align)
+{
+ int c, h, w;
+ int height_col = (height + 2 * pad - ksize) / stride + 1;
+ int width_col = (width + 2 * pad - ksize) / stride + 1;
+ int channels_col = channels * ksize * ksize;
+
+ // optimized version
+ if (height_col == height && width_col == width && stride == 1 && pad == 1 && is_fma_avx2())
+ {
+ __m256i all256_sing1 = _mm256_set_epi32(0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000);
+ __m256 float_zero256 = _mm256_set1_ps(0.00);
+
+ int new_ldb = bit_align;
+
+ #pragma omp parallel for
+ for (c = 0; c < channels_col; ++c) {
+ int w_offset = c % ksize;
+ int h_offset = (c / ksize) % ksize;
+ int c_im = c / ksize / ksize;
+ for (h = pad; h < height_col - pad; ++h) {
+ for (w = pad; w < width_col - pad - 8; w += 8) {
+ int im_row = h_offset + h - pad;
+ int im_col = w_offset + w - pad;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //__m256i src256 = _mm256_loadu_si256((__m256i *)(&data_im[im_col + width*(im_row + height*c_im)]));
+ //__m256i result256 = _mm256_and_si256(src256, all256_sing1); // check sign in 8 x 32-bit floats
+ //uint16_t mask = _mm256_movemask_ps(_mm256_castsi256_ps(result256)); // (val >= 0) ? 0 : 1
+ //mask = ~mask; // inverse mask, (val >= 0) ? 1 : 0
+
+ __m256 src256 = _mm256_loadu_ps((float *)(&data_im[im_col + width*(im_row + height*c_im)]));
+ __m256 result256 = _mm256_cmp_ps(src256, float_zero256, _CMP_GT_OS);
+ uint16_t mask = _mm256_movemask_ps(result256); // (val > 0) ? 0 : 1
+
+ uint16_t *dst_ptr = &((unsigned char*)data_col)[col_index / 8];
+ *dst_ptr |= (mask << (col_index % 8));
+ }
+
+ for (; w < width_col - pad; ++w) {
+ int im_row = h_offset + h - pad;
+ int im_col = w_offset + w - pad;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)];
+ float val = data_im[im_col + width*(im_row + height*c_im)];
+ if(val > 0) set_bit(data_col, col_index);
+ }
+ }
+
+ {
+ w = 0;
+ for (h = 0; h < height_col; ++h) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ float val = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ if (val > 0) set_bit(data_col, col_index);
+ }
+ }
+
+ {
+ w = width_col - 1;
+ for (h = 0; h < height_col; ++h) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ float val = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ if (val > 0) set_bit(data_col, col_index);
+ }
+ }
+
+ {
+ h = 0;
+ for (w = 0; w < width_col; ++w) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ float val = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ if (val > 0) set_bit(data_col, col_index);
+ }
+ }
+
+ {
+ h = height_col - 1;
+ for (w = 0; w < width_col; ++w) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ float val = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ if (val > 0) set_bit(data_col, col_index);
+ }
+ }
+ }
+
+ }
+ else {
+ printf("\n Error: is no non-optimized version \n");
+ //im2col_cpu(data_im, channels, height, width, ksize, stride, pad, data_col); // must be aligned for transpose after float_to_bin
+ // float_to_bit(b, t_input, src_size);
+ // transpose_bin(t_input, *t_bit_input, k, n, bit_align, new_ldb, 8);
+ }
+}
+
+
void activate_array_cpu_custom(float *x, const int n, const ACTIVATION a)
{
- int i;
+ int i = 0;
if (a == LINEAR)
{}
else if (a == LEAKY)
{
- __m256i all256_sing1 = _mm256_set_epi32(0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000);
- __m256 all256_01 = _mm256_set1_ps(0.1F);
+ if (is_fma_avx2()) {
+ __m256i all256_sing1 = _mm256_set_epi32(0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000);
+ __m256 all256_01 = _mm256_set1_ps(0.1F);
- for (i = 0; i < n; i += 8) {
- //x[i] = (x[i]>0) ? x[i] : .1*x[i];
+ for (i = 0; i < n - 8; i += 8) {
+ //x[i] = (x[i]>0) ? x[i] : .1*x[i];
- __m256 src256 = _mm256_loadu_ps((__m256 *)(&x[i]));
- __m256 mult256 = _mm256_mul_ps((src256), all256_01); // mult * 0.1
+ __m256 src256 = _mm256_loadu_ps(&x[i]);
+ __m256 mult256 = _mm256_mul_ps((src256), all256_01); // mult * 0.1
- __m256i sign256 = _mm256_and_si256(_mm256_castps_si256(src256), all256_sing1); // check sign in 8 x 32-bit floats
+ __m256i sign256 = _mm256_and_si256(_mm256_castps_si256(src256), all256_sing1); // check sign in 8 x 32-bit floats
- __m256 result256 = _mm256_blendv_ps(src256, mult256, _mm256_castsi256_ps(sign256)); // (sign>0) ? src : mult;
- _mm256_storeu_ps((__m256 *)(&x[i]), result256);
+ __m256 result256 = _mm256_blendv_ps(src256, mult256, _mm256_castsi256_ps(sign256)); // (sign>0) ? src : mult;
+ _mm256_storeu_ps(&x[i], result256);
+ }
}
for (; i < n; ++i) {
@@ -671,14 +1377,18 @@
size_t i;
__m256i all256_sing1 = _mm256_set_epi32(0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000, 0x80000000);
+ __m256 float_zero256 = _mm256_set1_ps(0.0);
for (i = 0; i < size; i+=8)
{
- __m256i src256 = _mm256_loadu_si256((__m256i *)(&src[i]));
- __m256i result256 = _mm256_and_si256(src256, all256_sing1); // check sign in 8 x 32-bit floats
+ //__m256i src256 = _mm256_loadu_si256((__m256i *)(&src[i]));
+ //__m256i result256 = _mm256_and_si256(src256, all256_sing1); // check sign in 8 x 32-bit floats
+ //uint32_t mask = _mm256_movemask_ps(_mm256_castsi256_ps(result256)); // (val >= 0) ? 0 : 1
+ ////mask = ~mask; // inverse mask, (val >= 0) ? 1 : 0
- uint32_t mask = _mm256_movemask_ps(_mm256_castsi256_ps(result256)); // (val >= 0) ? 0 : 1
- mask = ~mask; // inverse mask, (val >= 0) ? 1 : 0
+ __m256 src256 = _mm256_loadu_ps((float *)(&src[i]));
+ __m256 result256 = _mm256_cmp_ps(src256, float_zero256, _CMP_GT_OS);
+ uint32_t mask = _mm256_movemask_ps(result256); // (val > 0) ? 0 : 1
dst[i / 8] = mask;
}
@@ -686,47 +1396,50 @@
static inline void transpose4x4_SSE(float *A, float *B, const int lda, const int ldb)
{
- __m128 row1 = _mm_load_ps(&A[0 * lda]);
- __m128 row2 = _mm_load_ps(&A[1 * lda]);
- __m128 row3 = _mm_load_ps(&A[2 * lda]);
- __m128 row4 = _mm_load_ps(&A[3 * lda]);
+ __m128 row1 = _mm_loadu_ps(&A[0 * lda]);
+ __m128 row2 = _mm_loadu_ps(&A[1 * lda]);
+ __m128 row3 = _mm_loadu_ps(&A[2 * lda]);
+ __m128 row4 = _mm_loadu_ps(&A[3 * lda]);
_MM_TRANSPOSE4_PS(row1, row2, row3, row4);
- _mm_store_ps(&B[0 * ldb], row1);
- _mm_store_ps(&B[1 * ldb], row2);
- _mm_store_ps(&B[2 * ldb], row3);
- _mm_store_ps(&B[3 * ldb], row4);
+ _mm_storeu_ps(&B[0 * ldb], row1);
+ _mm_storeu_ps(&B[1 * ldb], row2);
+ _mm_storeu_ps(&B[2 * ldb], row3);
+ _mm_storeu_ps(&B[3 * ldb], row4);
}
void transpose_block_SSE4x4(float *A, float *B, const int n, const int m,
const int lda, const int ldb, const int block_size)
{
int i;
- if (block_size % 4 == 0) {
- #pragma omp parallel for
- for (i = 0; i < n; i += block_size) {
- int j, i2, j2;
+ #pragma omp parallel for
+ for (i = 0; i < n; i += block_size) {
+ int j, i2, j2;
+ //int max_i2 = (i + block_size < n) ? (i + block_size) : n;
+ if (i + block_size < n) {
+ int max_i2 = i + block_size;
for (j = 0; j < m; j += block_size) {
- int max_i2 = i + block_size < n ? i + block_size : n;
- int max_j2 = j + block_size < m ? j + block_size : m;
- for (i2 = i; i2 < max_i2; i2 += 4) {
- for (j2 = j; j2 < max_j2; j2 += 4) {
- transpose4x4_SSE(&A[i2*lda + j2], &B[j2*ldb + i2], lda, ldb);
+ //int max_j2 = (j + block_size < m) ? (j + block_size) : m;
+ if (j + block_size < m) {
+ int max_j2 = j + block_size;
+ for (i2 = i; i2 < max_i2; i2 += 4) {
+ for (j2 = j; j2 < max_j2; j2 += 4) {
+ transpose4x4_SSE(&A[i2*lda + j2], &B[j2*ldb + i2], lda, ldb);
+ }
+ }
+ }
+ else {
+ for (i2 = i; i2 < max_i2; ++i2) {
+ for (j2 = j; j2 < m; ++j2) {
+ B[j2*ldb + i2] = A[i2*lda + j2];
+ }
}
}
}
}
- }
- else {
- #pragma omp parallel for
- for (i = 0; i < n; i += block_size) {
- int j, i2, j2;
- for (j = 0; j < m; j += block_size) {
- int max_i2 = i + block_size < n ? i + block_size : n;
- int max_j2 = j + block_size < m ? j + block_size : m;
- for (i2 = i; i2 < max_i2; ++i2) {
- for (j2 = j; j2 < max_j2; ++j2) {
- B[j2*ldb + i2] = A[i2*lda + j2];
- }
+ else {
+ for (i2 = i; i2 < n; ++i2) {
+ for (j2 = 0; j2 < m; ++j2) {
+ B[j2*ldb + i2] = A[i2*lda + j2];
}
}
}
@@ -734,6 +1447,100 @@
}
+void forward_maxpool_layer_avx(float *src, float *dst, int *indexes, int size, int w, int h, int out_w, int out_h, int c,
+ int pad, int stride, int batch)
+{
+
+ int w_offset = -pad / 2;
+ int h_offset = -pad / 2;
+ int b, k;
+
+ for (b = 0; b < batch; ++b) {
+ #pragma omp parallel for
+ for (k = 0; k < c; ++k) {
+ int i, j, m, n;
+ for (i = 0; i < out_h; ++i) {
+ //for (j = 0; j < out_w; ++j) {
+ j = 0;
+
+ if(stride == 1 && is_avx() == 1) {
+ for (j = 0; j < out_w - 8 - (size - 1); j += 8) {
+ int out_index = j + out_w*(i + out_h*(k + c*b));
+ __m256 max256 = _mm256_set1_ps(-FLT_MAX);
+ for (n = 0; n < size; ++n) {
+ for (m = 0; m < size; ++m) {
+ int cur_h = h_offset + i*stride + n;
+ int cur_w = w_offset + j*stride + m;
+ int index = cur_w + w*(cur_h + h*(k + b*c));
+ int valid = (cur_h >= 0 && cur_h < h &&
+ cur_w >= 0 && cur_w < w);
+ if (!valid) continue;
+
+ __m256 src256 = _mm256_loadu_ps(&src[index]);
+ max256 = _mm256_max_ps(src256, max256);
+ }
+ }
+ _mm256_storeu_ps(&dst[out_index], max256);
+
+ }
+ }
+ else if (size == 2 && stride == 2 && is_avx() == 1) {
+ for (j = 0; j < out_w - 4; j += 4) {
+ int out_index = j + out_w*(i + out_h*(k + c*b));
+ float max = -FLT_MAX;
+ int max_i = -1;
+ __m128 max128 = _mm_set1_ps(-FLT_MAX);
+
+ for (n = 0; n < size; ++n) {
+ //for (m = 0; m < size; ++m)
+ m = 0;
+ {
+ int cur_h = h_offset + i*stride + n;
+ int cur_w = w_offset + j*stride + m;
+ int index = cur_w + w*(cur_h + h*(k + b*c));
+ int valid = (cur_h >= 0 && cur_h < h &&
+ cur_w >= 0 && cur_w < w);
+ if (!valid) continue;
+
+ __m256 src256 = _mm256_loadu_ps(&src[index]);
+ __m256 src256_2 = _mm256_permute_ps(src256, (1 << 0) | (3 << 4));
+ __m256 max256 = _mm256_max_ps(src256, src256_2);
+
+ __m128 src128_0 = _mm256_extractf128_ps(max256, 0);
+ __m128 src128_1 = _mm256_extractf128_ps(max256, 1);
+ __m128 src128 = _mm_shuffle_ps(src128_0, src128_1, (2 << 2) | (2 << 6));
+
+ max128 = _mm_max_ps(src128, max128);
+ }
+ }
+ _mm_storeu_ps(&dst[out_index], max128);
+ }
+ }
+
+ for (; j < out_w; ++j) {
+ int out_index = j + out_w*(i + out_h*(k + c*b));
+ float max = -FLT_MAX;
+ int max_i = -1;
+ for (n = 0; n < size; ++n) {
+ for (m = 0; m < size; ++m) {
+ int cur_h = h_offset + i*stride + n;
+ int cur_w = w_offset + j*stride + m;
+ int index = cur_w + w*(cur_h + h*(k + b*c));
+ int valid = (cur_h >= 0 && cur_h < h &&
+ cur_w >= 0 && cur_w < w);
+ float val = (valid != 0) ? src[index] : -FLT_MAX;
+ max_i = (val > max) ? index : max_i;
+ max = (val > max) ? val : max;
+ }
+ }
+ dst[out_index] = max;
+ indexes[out_index] = max_i;
+ }
+ }
+ }
+ }
+}
+
#else
void gemm_nn(int M, int N, int K, float ALPHA,
@@ -752,6 +1559,55 @@
}
}
+
+void convolution_2d(int w, int h, int ksize, int n, int c, int pad, int stride,
+ float *weights, float *input, float *output, float *mean)
+{
+ int out_h = (h + 2 * pad - ksize) / stride + 1; // output_height=input_height for stride=1 and pad=1
+ int out_w = (w + 2 * pad - ksize) / stride + 1; // output_width=input_width for stride=1 and pad=1
+ int i, f, j;
+
+ int fil;
+ // filter index
+#pragma omp parallel for // "omp parallel for" - automatic parallelization of loop by using OpenMP
+ for (fil = 0; fil < n; ++fil) {
+ int chan, y, x, f_y, f_x;
+ // channel index
+ for (chan = 0; chan < c; ++chan)
+ // input - y
+ for (y = 0; y < h; ++y)
+ // input - x
+ for (x = 0; x < w; ++x)
+ {
+ int const output_index = fil*w*h + y*w + x;
+ int const weights_pre_index = fil*c*ksize*ksize + chan*ksize*ksize;
+ int const input_pre_index = chan*w*h;
+ float sum = 0;
+
+ // filter - y
+ for (f_y = 0; f_y < ksize; ++f_y)
+ {
+ int input_y = y + f_y - pad;
+ // filter - x
+ for (f_x = 0; f_x < ksize; ++f_x)
+ {
+ int input_x = x + f_x - pad;
+ if (input_y < 0 || input_x < 0 || input_y >= h || input_x >= w) continue;
+
+ int input_index = input_pre_index + input_y*w + input_x;
+ int weights_index = weights_pre_index + f_y*ksize + f_x;
+
+ sum += input[input_index] * weights[weights_index];
+ }
+ }
+ // l.output[filters][width][height] +=
+ // state.input[channels][width][height] *
+ // l.weights[filters][channels][filter_width][filter_height];
+ output[output_index] += sum;
+ }
+ }
+}
+
void gemm_nn_custom_bin_mean_transposed(int M, int N, int K, float ALPHA_UNUSED,
unsigned char *A, int lda,
unsigned char *B, int ldb,
@@ -788,12 +1644,21 @@
}
}
+void im2col_cpu_custom_transpose(float* data_im,
+ int channels, int height, int width,
+ int ksize, int stride, int pad, float* data_col, int ldb_align)
+{
+ printf("\n im2col_cpu_custom_transpose() isn't implemented without AVX \n");
+}
+
//From Berkeley Vision's Caffe!
//https://github.com/BVLC/caffe/blob/master/LICENSE
void im2col_cpu_custom(float* data_im,
int channels, int height, int width,
int ksize, int stride, int pad, float* data_col)
{
+ im2col_cpu(data_im, channels, height, width, ksize, stride, pad, data_col);
+ return;
int c, h, w;
int height_col = (height + 2 * pad - ksize) / stride + 1;
@@ -815,7 +1680,7 @@
int col_index = (c * height_col + h) * width_col + w;
data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)];
- }
+ }
for (; w < width_col - pad; ++w) {
int im_row = h_offset + h - pad;
@@ -824,7 +1689,7 @@
data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)];
}
-}
+ }
{
w = 0;
@@ -878,6 +1743,118 @@
}
}
+
+//From Berkeley Vision's Caffe!
+//https://github.com/BVLC/caffe/blob/master/LICENSE
+void im2col_cpu_custom_bin(float* data_im,
+ int channels, int height, int width,
+ int ksize, int stride, int pad, float* data_col, int bit_align)
+{
+ int c, h, w;
+ int height_col = (height + 2 * pad - ksize) / stride + 1;
+ int width_col = (width + 2 * pad - ksize) / stride + 1;
+ int channels_col = channels * ksize * ksize;
+
+ // optimized version
+ if (height_col == height && width_col == width && stride == 1 && pad == 1)
+ {
+ int new_ldb = bit_align;
+
+ #pragma omp parallel for
+ for (c = 0; c < channels_col; ++c) {
+ int w_offset = c % ksize;
+ int h_offset = (c / ksize) % ksize;
+ int c_im = c / ksize / ksize;
+ for (h = pad; h < height_col - pad; ++h) {
+ for (w = pad; w < width_col - pad - 8; w += 1) {
+ int im_row = h_offset + h - pad;
+ int im_col = w_offset + w - pad;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ float val = data_im[im_col + width*(im_row + height*c_im)];
+ if (val > 0) set_bit(data_col, col_index);
+ }
+
+ for (; w < width_col - pad; ++w) {
+ int im_row = h_offset + h - pad;
+ int im_col = w_offset + w - pad;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //data_col[col_index] = data_im[im_col + width*(im_row + height*c_im)];
+ float val = data_im[im_col + width*(im_row + height*c_im)];
+ if (val > 0) set_bit(data_col, col_index);
+ }
+ }
+
+ {
+ w = 0;
+ for (h = 0; h < height_col; ++h) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ float val = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ if (val > 0) set_bit(data_col, col_index);
+ }
+ }
+
+ {
+ w = width_col - 1;
+ for (h = 0; h < height_col; ++h) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ float val = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ if (val > 0) set_bit(data_col, col_index);
+ }
+ }
+
+ {
+ h = 0;
+ for (w = 0; w < width_col; ++w) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ float val = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ if (val > 0) set_bit(data_col, col_index);
+ }
+ }
+
+ {
+ h = height_col - 1;
+ for (w = 0; w < width_col; ++w) {
+ int im_row = h_offset + h;
+ int im_col = w_offset + w;
+ //int col_index = (c * height_col + h) * width_col + w;
+ int col_index = c * new_ldb + h * width_col + w;
+
+ //data_col[col_index] = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ float val = im2col_get_pixel(data_im, height, width, channels, im_row, im_col, c_im, pad);
+ if (val > 0) set_bit(data_col, col_index);
+ }
+ }
+ }
+
+ }
+ else {
+ printf("\n Error: is no non-optimized version \n");
+ //im2col_cpu(data_im, channels, height, width, ksize, stride, pad, data_col); // must be aligned for transpose after float_to_bin
+ // float_to_bit(b, t_input, src_size);
+ // transpose_bin(t_input, *t_bit_input, k, n, bit_align, new_ldb, 8);
+ }
+}
+
+
void activate_array_cpu_custom(float *x, const int n, const ACTIVATION a)
{
int i;
@@ -956,7 +1933,44 @@
}
}
}
-#endif // __x86_64
+
+void forward_maxpool_layer_avx(float *src, float *dst, int *indexes, int size, int w, int h, int out_w, int out_h, int c,
+ int pad, int stride, int batch)
+{
+ int b, k;
+ int w_offset = -pad / 2;
+ int h_offset = -pad / 2;
+
+ for (b = 0; b < batch; ++b) {
+ #pragma omp parallel for
+ for (k = 0; k < c; ++k) {
+ int i, j, m, n;
+ for (i = 0; i < out_h; ++i) {
+ for (j = 0; j < out_w; ++j) {
+ int out_index = j + out_w*(i + out_h*(k + c*b));
+ float max = -FLT_MAX;
+ int max_i = -1;
+ for (n = 0; n < size; ++n) {
+ for (m = 0; m < size; ++m) {
+ int cur_h = h_offset + i*stride + n;
+ int cur_w = w_offset + j*stride + m;
+ int index = cur_w + w*(cur_h + h*(k + b*c));
+ int valid = (cur_h >= 0 && cur_h < h &&
+ cur_w >= 0 && cur_w < w);
+ float val = (valid != 0) ? src[index] : -FLT_MAX;
+ max_i = (val > max) ? index : max_i;
+ max = (val > max) ? val : max;
+ }
+ }
+ dst[out_index] = max;
+ indexes[out_index] = max_i;
+ }
+ }
+ }
+ }
+}
+
+#endif // AVX
void gemm_nt(int M, int N, int K, float ALPHA,
float *A, int lda,
--
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