| | |
| | | if (l->bf_algo == CUDNN_CONVOLUTION_BWD_FILTER_ALGO_WINOGRAD_NONFUSED) bf = 2; |
| | | //printf("Tensor Cores - Backward-filter enabled: l->bf_algo = CUDNN_CONVOLUTION_BWD_FILTER_ALGO_WINOGRAD_NONFUSED \n"); |
| | | |
| | | if (fw == 2 && bd == 2 && bf == 2) printf("TF "); |
| | | else if (fw == 1 && bd == 1 && bf == 1) printf("TH "); |
| | | //if (fw == 2 && bd == 2 && bf == 2) printf("TF "); |
| | | //else if (fw == 1 && bd == 1 && bf == 1) printf("TH "); |
| | | } |
| | | } |
| | | #endif |
| | |
| | | } |
| | | } |
| | | |
| | | void gemm_nn_custom(int M, int N, int K, float ALPHA, |
| | | float *A, int lda, |
| | | float *B, int ldb, |
| | | float *C, int ldc) |
| | | { |
| | | int i, j, k; |
| | | for (i = 0; i < M; ++i) { |
| | | for (k = 0; k < K; ++k) { |
| | | register float A_PART = ALPHA*A[i*lda + k]; |
| | | //printf("\n weight = %f \n", A_PART); |
| | | for (j = 0; j < N; ++j) { |
| | | C[i*ldc + j] += A_PART*B[k*ldb + j]; |
| | | } |
| | | } |
| | | } |
| | | } |
| | | |
| | | |
| | | void get_mean_array(float *src, size_t size, size_t filters, float *mean_arr) { |
| | | size_t i, counter; |
| | | counter = 0; |
| | | for (i = 0; i < size; i += size / filters) { |
| | | mean_arr[counter++] = fabs(src[i]); |
| | | } |
| | | } |
| | | |
| | | /* |
| | | void float_to_bit(float *src, unsigned char *dst, size_t size) { |
| | | |
| | | size_t dst_size = size / 8 + 1; |
| | | memset(dst, 0, dst_size); |
| | | size_t i, dst_i, dst_shift; |
| | | for (i = 0; i < size; ++i) { |
| | | if (src[i] > 0) set_bit(dst, i); |
| | | } |
| | | } |
| | | */ |
| | | |
| | | void bit_to_float(unsigned char *src, float *dst, size_t size, size_t filters, float *mean_arr) { |
| | | memset(dst, 0, size *sizeof(float)); |
| | | size_t i, src_i, src_shift; |
| | | |
| | | for (i = 0; i < size; ++i) { |
| | | float mean_val = 1; |
| | | if(mean_arr != NULL) mean_val = fabs(mean_arr[i / (size / filters)]); |
| | | if(get_bit(src, i)) dst[i] = mean_val; |
| | | else dst[i] = -mean_val; |
| | | } |
| | | } |
| | | |
| | | void binary_transpose_align_weights(convolutional_layer *l, size_t ldb_align) |
| | | { |
| | | int m = l->n; |
| | | int k = l->size*l->size*l->c; |
| | | size_t new_ldb = k + (ldb_align - k%ldb_align); // (k / 8 + 1) * 8; |
| | | |
| | | binarize_weights(l->weights, m, k, l->binary_weights); |
| | | |
| | | size_t align_weights_size = new_ldb * m; |
| | | size_t align_bit_weights_size = align_weights_size / 8;// +1; |
| | | float *align_weights = calloc(align_weights_size, sizeof(float)); |
| | | l->align_bit_weights = calloc(align_bit_weights_size, sizeof(char)); |
| | | |
| | | size_t i, j; |
| | | // align A without transpose |
| | | for (i = 0; i < m; ++i) { |
| | | for (j = 0; j < k; ++j) { |
| | | align_weights[i*new_ldb + j] = l->binary_weights[i*k + j]; |
| | | } |
| | | } |
| | | float_to_bit(align_weights, l->align_bit_weights, align_weights_size); |
| | | |
| | | l->mean_arr = calloc(l->n, sizeof(float)); |
| | | get_mean_array(align_weights, align_weights_size, l->n, l->mean_arr); |
| | | |
| | | free(align_weights); |
| | | } |
| | | |
| | | |
| | | void forward_convolutional_layer(convolutional_layer l, network_state state) |
| | | { |
| | | int out_h = convolutional_out_height(l); |
| | |
| | | fill_cpu(l.outputs*l.batch, 0, l.output, 1); |
| | | |
| | | if(l.xnor){ |
| | | if (!l.align_bit_weights) { |
| | | binarize_weights(l.weights, l.n, l.c*l.size*l.size, l.binary_weights); |
| | | //printf("\n binarize_weights l.align_bit_weights = %p \n", l.align_bit_weights); |
| | | } |
| | | swap_binary(&l); |
| | | binarize_cpu(state.input, l.c*l.h*l.w*l.batch, l.binary_input); |
| | | state.input = l.binary_input; |
| | |
| | | int k = l.size*l.size*l.c; |
| | | int n = out_h*out_w; |
| | | |
| | | |
| | | float *a = l.weights; |
| | | float *b = state.workspace; |
| | | float *c = l.output; |
| | | |
| | | static int u = 0; |
| | | u++; |
| | | |
| | | for(i = 0; i < l.batch; ++i){ |
| | | im2col_cpu(state.input, l.c, l.h, l.w, |
| | | l.size, l.stride, l.pad, b); |
| | | //gemm(0,0,m,n,k,1,a,k,b,n,1,c,n); |
| | | //gemm_nn_custom(m, n, k, 1, a, k, b, n, c, n); |
| | | if (l.xnor) { |
| | | size_t output_size = l.outputs; |
| | | //float *count_output = calloc(output_size, sizeof(float)); |
| | | //size_t bit_output_size = output_size / 8 + 1; |
| | | //char *bit_output = calloc(bit_output_size, sizeof(char)); |
| | | |
| | | size_t intput_size = n * k; // (out_h*out_w) X (l.size*l.size*l.c) : after im2col() |
| | | size_t bit_input_size = intput_size / 8 + 1; |
| | | //char *bit_input = calloc(bit_input_size, sizeof(char)); |
| | | |
| | | size_t weights_size = k * m; //l.size*l.size*l.c*l.n; |
| | | size_t bit_weights_size = weights_size / 8 + 1; |
| | | //char *bit_weights = calloc(bit_weights_size, sizeof(char)); |
| | | //float *mean_arr = calloc(l.n, sizeof(float)); |
| | | |
| | | // test: float->bit->float |
| | | //get_mean_array(l.weights, weights_size, l.n, mean_arr); |
| | | //float_to_bit(l.weights, bit_weights, weights_size); |
| | | //memset(l.weights, 0, weights_size * sizeof(float)); |
| | | //bit_to_float(bit_weights, l.weights, weights_size, l.n, mean_arr); // just for test float->bit->float |
| | | |
| | | //float_to_bit(b, bit_input, intput_size); |
| | | //memset(b, 0, intput_size * sizeof(float)); |
| | | //bit_to_float(bit_input, b, intput_size, 1, NULL); // just for test float->bit->float |
| | | |
| | | // transpose B from NxK to KxN (x-axis (ldb = l.size*l.size*l.c) - should be multiple of 8 bits) |
| | | { |
| | | size_t ldb_align = 256;// 8; |
| | | size_t new_ldb = k + (ldb_align - k%ldb_align); // (k / 8 + 1) * 8; |
| | | size_t t_intput_size = new_ldb * n; |
| | | size_t t_bit_input_size = t_intput_size / 8;// +1; |
| | | float *t_input = calloc(t_intput_size, sizeof(float)); |
| | | char *t_bit_input = calloc(t_bit_input_size, sizeof(char)); |
| | | |
| | | //printf("\n bit_input_size = %d, n = %d, k = %d, ldb = %d \n", bit_input_size, n, k, n); |
| | | //printf("\n t_bit_input_size = %d, k = %d, n = %d, new_ldb = %d \n", t_bit_input_size, k, n, new_ldb); |
| | | |
| | | |
| | | //printf("\n align_weights_size = %d, k = %d, m = %d, lda = %d \n", align_weights_size, k, m, k); |
| | | //printf("\n align_bit_weights_size = %d, k = %d, m = %d, new_lda = %d \n", align_bit_weights_size, k, m, new_ldb); |
| | | |
| | | |
| | | // transpose and align B |
| | | int i, j; |
| | | for (i = 0; i < n; ++i) { |
| | | for (j = 0; j < k; ++j) { |
| | | t_input[i*new_ldb + j] = b[j*n + i]; |
| | | } |
| | | } |
| | | float_to_bit(t_input, t_bit_input, t_intput_size); |
| | | |
| | | if (!l.align_bit_weights) |
| | | { |
| | | size_t align_weights_size = new_ldb * m; |
| | | size_t align_bit_weights_size = align_weights_size / 8;// +1; |
| | | float *align_weights = calloc(align_weights_size, sizeof(float)); |
| | | l.align_bit_weights = calloc(align_bit_weights_size, sizeof(char)); |
| | | |
| | | // align A without transpose |
| | | for (i = 0; i < m; ++i) { |
| | | for (j = 0; j < k; ++j) { |
| | | align_weights[i*new_ldb + j] = a[i*k + j]; |
| | | } |
| | | } |
| | | float_to_bit(align_weights, l.align_bit_weights, align_weights_size); |
| | | |
| | | l.mean_arr = calloc(l.n, sizeof(float)); |
| | | get_mean_array(align_weights, align_weights_size, l.n, l.mean_arr); |
| | | |
| | | free(align_weights); |
| | | } |
| | | |
| | | gemm_nn_custom_bin_mean_transposed(m, n, k, 1, l.align_bit_weights, new_ldb, t_bit_input, new_ldb, c, n, l.mean_arr); |
| | | |
| | | //gemm_nn_custom_bin_mean_transposed(m, n, k, 1, bit_weights, k, t_bit_input, new_ldb, c, n, mean_arr); |
| | | |
| | | free(t_input); |
| | | free(t_bit_input); |
| | | |
| | | //free(align_bit_weights); |
| | | } |
| | | |
| | | // for bit_input: (k * n) |
| | | //if (u == 8) gemm_nn_custom_bin_mean(m, n, k, 1, bit_weights, k, bit_input, n, c, n, mean_arr); // last xnor layer |
| | | //else gemm_nn_custom_bin_mean(m, n, k, 1, bit_weights, k, bit_input, n, c, n, NULL); |
| | | |
| | | //gemm_nn_custom_bin_mean(m, n, k, 1, bit_weights, k, bit_input, n, c, n, mean_arr); |
| | | |
| | | //printf("\n u = %d \n", u); |
| | | |
| | | //gemm_nn_custom(m, n, k, 1, a, k, b, n, c, n); |
| | | |
| | | //int j; |
| | | //if (u != 8) for (j = 0; j < l.n; ++j) l.biases[j] = l.biases[j] / (mean_arr[j]*2); |
| | | |
| | | //free(count_output); |
| | | //free(bit_input); |
| | | //free(bit_weights); |
| | | //free(mean_arr); |
| | | } |
| | | else { |
| | | gemm(0,0,m,n,k,1,a,k,b,n,1,c,n); |
| | | // bit-count to float |
| | | } |
| | | c += n*m; |
| | | state.input += l.c*l.h*l.w; |
| | | } |
| | |
| | | void swap_binary(convolutional_layer *l); |
| | | void binarize_weights2(float *weights, int n, int size, char *binary, float *scales); |
| | | |
| | | void binary_transpose_align_weights(convolutional_layer *l, size_t ldb_align); |
| | | |
| | | void backward_convolutional_layer(convolutional_layer layer, network_state state); |
| | | |
| | | void add_bias(float *output, float *biases, int batch, int n, int size); |
| | |
| | | } |
| | | //set_batch_network(&net, 1); |
| | | fuse_conv_batchnorm(net); |
| | | calculate_binary_weights(net); |
| | | srand(2222222); |
| | | |
| | | if(filename){ |
| | |
| | | } |
| | | //set_batch_network(&net, 1); |
| | | fuse_conv_batchnorm(net); |
| | | calculate_binary_weights(net); |
| | | srand(time(0)); |
| | | |
| | | list *plist = get_paths(valid_images); |
| | |
| | | } |
| | | //set_batch_network(&net, 1); |
| | | fuse_conv_batchnorm(net); |
| | | calculate_binary_weights(net); |
| | | if (net.layers[net.n - 1].classes != names_size) { |
| | | printf(" Error: in the file %s number of names %d that isn't equal to classes=%d in the file %s \n", |
| | | name_list, names_size, net.layers[net.n - 1].classes, cfgfile); |
| | |
| | | gemm_cpu( TA, TB, M, N, K, ALPHA,A,lda, B, ldb,BETA,C,ldc); |
| | | } |
| | | |
| | | |
| | | //-------------------------------------------- |
| | | // XNOR bitwise GEMM for binary neural network |
| | | //-------------------------------------------- |
| | | |
| | | #include <stdint.h> |
| | | |
| | | static inline unsigned char xnor(unsigned char a, unsigned char b) { |
| | | //return a == b; |
| | | return !(a^b); |
| | | } |
| | | |
| | | // INT-32 |
| | | static inline uint32_t get_bit_int32(uint32_t const*const src, size_t index) { |
| | | size_t src_i = index / 32; |
| | | int src_shift = index % 32; |
| | | unsigned char val = (src[src_i] & (1 << src_shift)) > 0; |
| | | return val; |
| | | } |
| | | |
| | | static inline uint32_t xnor_int32(uint32_t a, uint32_t b) { |
| | | return ~(a^b); |
| | | } |
| | | |
| | | static inline uint64_t xnor_int64(uint64_t a, uint64_t b) { |
| | | return ~(a^b); |
| | | } |
| | | |
| | | |
| | | static inline uint32_t fill_bit_int32(char src) { |
| | | if (src == 0) return 0x00000000; |
| | | else return 0xFFFFFFFF; |
| | | } |
| | | |
| | | static inline uint64_t fill_bit_int64(char src) { |
| | | if (src == 0) return 0x0000000000000000; |
| | | else return 0xFFFFFFFFFFFFFFFF; |
| | | } |
| | | |
| | | void binary_int32_printf(uint32_t src) { |
| | | int i; |
| | | for (i = 0; i < 32; ++i) { |
| | | if (src & 1) printf("1"); |
| | | else printf("0"); |
| | | src = src >> 1; |
| | | } |
| | | printf("\n"); |
| | | } |
| | | |
| | | void binary_int64_printf(uint64_t src) { |
| | | int i; |
| | | for (i = 0; i < 64; ++i) { |
| | | if (src & 1) printf("1"); |
| | | else printf("0"); |
| | | src = src >> 1; |
| | | } |
| | | printf("\n"); |
| | | } |
| | | |
| | | /* |
| | | void gemm_nn_custom_bin_mean(int M, int N, int K, float ALPHA_UNUSED, |
| | | unsigned char *A, int lda, |
| | | unsigned char *B, int ldb, |
| | | float *C, int ldc, float *mean_arr) |
| | | { |
| | | int *count_arr = calloc(M*N, sizeof(int)); |
| | | |
| | | int i, j, k; |
| | | for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] |
| | | for (k = 0; k < K; ++k) { // l.size*l.size*l.c - one filter size [27 - 9216] |
| | | char a_bit = get_bit(A, i*lda + k); |
| | | |
| | | for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] |
| | | char b_bit = get_bit(B, k*ldb + j); |
| | | count_arr[i*ldc + j] += xnor(a_bit, b_bit); |
| | | } |
| | | } |
| | | } |
| | | |
| | | for (i = 0; i < M; ++i) { |
| | | float mean_val = mean_arr[i]; |
| | | for (j = 0; j < N; ++j) { |
| | | C[i*ldc + j] = (2 * count_arr[i*ldc + j] - K) * mean_val; |
| | | } |
| | | } |
| | | free(count_arr); |
| | | } |
| | | */ |
| | | |
| | | /* |
| | | 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, |
| | | float *C, int ldc, float *mean_arr) |
| | | { |
| | | int *count_arr = calloc(M*N, sizeof(int)); |
| | | |
| | | int i, j, k; |
| | | for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] |
| | | for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] |
| | | for (k = 0; k < K; ++k) { // l.size*l.size*l.c - one filter size [27 - 9216] |
| | | char a_bit = get_bit(A, i*lda + k); |
| | | char b_bit = get_bit(B, j*ldb + k); |
| | | count_arr[i*ldc + j] += xnor(a_bit, b_bit); |
| | | } |
| | | } |
| | | } |
| | | |
| | | for (i = 0; i < M; ++i) { |
| | | float mean_val = mean_arr[i]; |
| | | for (j = 0; j < N; ++j) { |
| | | C[i*ldc + j] = (2 * count_arr[i*ldc + j] - K) * mean_val; |
| | | } |
| | | } |
| | | free(count_arr); |
| | | } |
| | | */ |
| | | |
| | | /* |
| | | void gemm_nn_custom_bin_mean(int M, int N, int K, float ALPHA_UNUSED, |
| | | unsigned char *A, int lda, |
| | | unsigned char *B, int ldb, |
| | | float *C, int ldc, float *mean_arr) |
| | | { |
| | | int *count_arr = calloc(M*N, sizeof(int)); |
| | | |
| | | int i, j, k, h; |
| | | |
| | | #pragma omp parallel for |
| | | for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] |
| | | for (k = 0; k < K; ++k) { // l.size*l.size*l.c - one filter size [27 - 9216] |
| | | const char a_bit = get_bit(A, i*lda + k); |
| | | uint64_t a_bit64 = fill_bit_int64(a_bit); |
| | | int k_ldb = k*ldb; |
| | | |
| | | for (j = 0; j < N; j += 64) { // out_h*out_w - one channel output size [169 - 173056] |
| | | if ((N - j > 64) && (k_ldb % 8 == 0)) { |
| | | uint64_t b_bit64 = *((uint64_t *)(B + (k_ldb + j) / 8)); |
| | | uint64_t c_bit64 = xnor_int64(a_bit64, b_bit64); |
| | | //printf("\n %d \n",__builtin_popcountll(c_bit64)); // gcc |
| | | printf("\n %d \n", __popcnt64(c_bit64)); // msvs |
| | | |
| | | int h; |
| | | for (h = 0; h < 64; ++h) |
| | | if ((c_bit64 >> h) & 1) count_arr[i*ldc + j + h] += 1; |
| | | |
| | | //binary_int64_printf(a_bit64); |
| | | //binary_int64_printf(b_bit64); |
| | | //binary_int64_printf(c_bit64); |
| | | } |
| | | else { |
| | | for (; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] |
| | | char b_bit = get_bit(B, k_ldb + j); |
| | | if (xnor(a_bit, b_bit)) count_arr[i*ldc + j] += 1; |
| | | } |
| | | } |
| | | |
| | | } |
| | | } |
| | | } |
| | | |
| | | if (mean_arr) { |
| | | //int K_2 = K / 2; |
| | | for (i = 0; i < M; ++i) { |
| | | float mean_val = mean_arr[i]; |
| | | //float mean_val2 = 2 * mean_val; |
| | | for (j = 0; j < N; ++j) { |
| | | C[i*ldc + j] = (2 * count_arr[i*ldc + j] - K) * mean_val; |
| | | //C[i*ldc + j] = (count_arr[i*ldc + j] - K_2) *mean_val2; |
| | | } |
| | | } |
| | | } |
| | | else { |
| | | for (i = 0; i < M; ++i) { |
| | | for (j = 0; j < N; ++j) { |
| | | C[i*ldc + j] = count_arr[i*ldc + j] - K / 2; |
| | | } |
| | | } |
| | | } |
| | | |
| | | free(count_arr); |
| | | |
| | | //getchar(); |
| | | } |
| | | */ |
| | | |
| | | |
| | | /* |
| | | 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, |
| | | float *C, int ldc, float *mean_arr) |
| | | { |
| | | int i, j, k, h; |
| | | |
| | | #pragma omp parallel for |
| | | for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] |
| | | float mean_val = mean_arr[i]; |
| | | |
| | | for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] |
| | | int count = 0; |
| | | |
| | | for (k = 0; k < K; k += 64) { // l.size*l.size*l.c - one filter size [27 - 9216] |
| | | uint64_t a_bit64 = *((uint64_t *)(A + (i*lda + k) / 8)); |
| | | uint64_t b_bit64 = *((uint64_t *)(B + (j*ldb + k) / 8)); |
| | | uint64_t c_bit64 = xnor_int64(a_bit64, b_bit64); |
| | | |
| | | #ifdef WIN32 |
| | | int tmp_count = __popcnt64(c_bit64); |
| | | #else |
| | | int tmp_count = __builtin_popcountll(c_bit64); |
| | | #endif |
| | | |
| | | if (K - k < 64) tmp_count = tmp_count - (64 - (K - k)); // remove extra bits |
| | | count += tmp_count; |
| | | //binary_int64_printf(c_bit64); |
| | | //printf(", count = %d \n\n", tmp_count); |
| | | } |
| | | |
| | | C[i*ldc + j] = (2 * count - K) * mean_val; |
| | | } |
| | | } |
| | | } |
| | | */ |
| | | |
| | | //---------------------------- |
| | | |
| | | |
| | | #if (defined(__AVX__) && defined(__x86_64__)) || defined(_WIN64) |
| | | |
| | | #define OSXSAVEFlag (1UL<<27) |
| | |
| | | #define CLMULFlag ((1UL<< 1)|AVXFlag|OSXSAVEFlag) |
| | | #define VAESFlag ((1UL<<25)|AVXFlag|OSXSAVEFlag) |
| | | |
| | | #include <stdint.h> |
| | | |
| | | #ifdef _WIN64 |
| | | #include <intrin.h> |
| | | #include <ammintrin.h> |
| | |
| | | } |
| | | } |
| | | } |
| | | |
| | | |
| | | // http://graphics.stanford.edu/~seander/bithacks.html |
| | | // https://stackoverflow.com/questions/17354971/fast-counting-the-number-of-set-bits-in-m128i-register |
| | | |
| | | // 2 x faster than popcnt: https://arxiv.org/pdf/1611.07612.pdf |
| | | |
| | | static inline int popcnt128(__m128i n) { |
| | | const __m128i n_hi = _mm_unpackhi_epi64(n, n); |
| | | #ifdef _MSC_VER |
| | | return __popcnt64(_mm_cvtsi128_si64(n)) + __popcnt64(_mm_cvtsi128_si64(n_hi)); |
| | | #else |
| | | return __popcntq(_mm_cvtsi128_si64(n)) + __popcntq(_mm_cvtsi128_si64(n_hi)); |
| | | #endif |
| | | } |
| | | |
| | | static inline int popcnt256(__m256i n) { |
| | | return popcnt128(_mm256_extractf128_si256(n, 0)) + popcnt128(_mm256_extractf128_si256(n, 1)); |
| | | } |
| | | |
| | | 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, |
| | | float *C, int ldc, float *mean_arr) |
| | | { |
| | | __m256i all_1 = _mm256_set1_epi8(255); |
| | | int i, j, k, h; |
| | | |
| | | #pragma omp parallel for |
| | | for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] |
| | | float mean_val = mean_arr[i]; |
| | | |
| | | for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] |
| | | int count = 0; |
| | | const int bit_step = 256; |
| | | |
| | | for (k = 0; k < K; k += bit_step) { // l.size*l.size*l.c - one filter size [27 - 9216] |
| | | |
| | | //__m128i a_bit128 = _mm_loadu_si128((__m128i *)(A + (i*lda + k) / 8)); |
| | | //__m128i b_bit128 = _mm_loadu_si128((__m128i *)(B + (j*ldb + k) / 8)); |
| | | //__m128i xor128 = _mm_xor_si128(a_bit128, b_bit128); |
| | | //__m128i c_bit128 = _mm_andnot_si128(xor128, all_1); |
| | | //int tmp_count = popcnt128(c_bit128); |
| | | |
| | | __m256i a_bit256 = _mm256_loadu_si256((__m256i *)(A + (i*lda + k) / 8)); |
| | | __m256i b_bit256 = _mm256_loadu_si256((__m256i *)(B + (j*ldb + k) / 8)); |
| | | __m256i xor256 = _mm256_xor_si256(a_bit256, b_bit256); |
| | | __m256i c_bit256 = _mm256_andnot_si256(xor256, all_1); //we can do NOT for wegihts once and do not do this NOT |
| | | int tmp_count = popcnt256(c_bit256); |
| | | |
| | | if (K - k < bit_step) tmp_count = tmp_count - (bit_step - (K - k)); // remove extra bits |
| | | count += tmp_count; |
| | | //binary_int64_printf(c_bit64); |
| | | //printf(", count = %d \n\n", tmp_count); |
| | | } |
| | | |
| | | C[i*ldc + j] = (2 * count - K) * mean_val; |
| | | } |
| | | } |
| | | } |
| | | |
| | | |
| | | void float_to_bit(float *src, unsigned char *dst, size_t size) |
| | | { |
| | | size_t dst_size = size / 8 + 1; |
| | | memset(dst, 0, dst_size); |
| | | |
| | | size_t i; |
| | | __m128i all128_0 = _mm_set_epi32(0, 0, 0, 0); |
| | | __m256 all256_0 = _mm256_set1_ps(0); |
| | | __m256i bits_asc = _mm256_set_epi32(1, 2, 4, 8, 16, 32, 64, 128); |
| | | //for(i = 0; i < 8; ++i) bits_asc.m256i_i32[i] = 1 << i; |
| | | |
| | | for (i = 0; i < size; i+=8) |
| | | { |
| | | __m256 src256 = _mm256_loadu_ps((__m256i *)(&src[i])); // load 256 bits |
| | | __m256 result256 = _mm256_cmp_ps(src256, all256_0, _CMP_GT_OS); // compare dst[i] = (float[i] > 0) |
| | | |
| | | __m256i bits256 = _mm256_castps_si256(result256); // floats to ints32 |
| | | __m256i and256 = _mm256_and_si256(bits256, bits_asc); // bitwise and |
| | | |
| | | // sum all elements from single and256 |
| | | __m128i tmp128 = _mm_hadd_epi32(_mm256_extractf128_si256(and256, 0), _mm256_extractf128_si256(and256, 1)); |
| | | tmp128 = _mm_hadd_epi32(tmp128, all128_0); |
| | | tmp128 = _mm_hadd_epi32(tmp128, all128_0); |
| | | |
| | | dst[i / 8] = tmp128.m128i_i32[0]; |
| | | } |
| | | // int _mm256_movemask_epi8 (__m256i a) |
| | | } |
| | | |
| | | #else |
| | | |
| | | void gemm_nn(int M, int N, int K, float ALPHA, |
| | |
| | | } |
| | | } |
| | | } |
| | | |
| | | 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, |
| | | float *C, int ldc, float *mean_arr) |
| | | { |
| | | int i, j, k, h; |
| | | |
| | | #pragma omp parallel for |
| | | for (i = 0; i < M; ++i) { // l.n - filters [16 - 55 - 1024] |
| | | float mean_val = mean_arr[i]; |
| | | |
| | | for (j = 0; j < N; ++j) { // out_h*out_w - one channel output size [169 - 173056] |
| | | int count = 0; |
| | | |
| | | for (k = 0; k < K; k += 64) { // l.size*l.size*l.c - one filter size [27 - 9216] |
| | | uint64_t a_bit64 = *((uint64_t *)(A + (i*lda + k) / 8)); |
| | | uint64_t b_bit64 = *((uint64_t *)(B + (j*ldb + k) / 8)); |
| | | uint64_t c_bit64 = xnor_int64(a_bit64, b_bit64); |
| | | |
| | | #ifdef WIN32 |
| | | int tmp_count = __popcnt64(c_bit64); |
| | | #else |
| | | int tmp_count = __builtin_popcountll(c_bit64); |
| | | #endif |
| | | |
| | | if (K - k < 64) tmp_count = tmp_count - (64 - (K - k)); // remove extra bits |
| | | count += tmp_count; |
| | | //binary_int64_printf(c_bit64); |
| | | //printf(", count = %d \n\n", tmp_count); |
| | | } |
| | | |
| | | C[i*ldc + j] = (2 * count - K) * mean_val; |
| | | } |
| | | } |
| | | } |
| | | |
| | | void float_to_bit(float *src, unsigned char *dst, size_t size) |
| | | { |
| | | size_t dst_size = size / 8 + 1; |
| | | memset(dst, 0, dst_size); |
| | | |
| | | size_t i; |
| | | char *byte_arr = calloc(size, sizeof(char)); |
| | | for (i = 0; i < size; ++i) { |
| | | if (src[i] > 0) byte_arr[i] = 1; |
| | | } |
| | | |
| | | //for (i = 0; i < size; ++i) { |
| | | // dst[i / 8] |= byte_arr[i] << (i % 8); |
| | | //} |
| | | |
| | | for (i = 0; i < size; i += 8) { |
| | | char dst_tmp = 0; |
| | | dst_tmp |= byte_arr[i + 0] << 0; |
| | | dst_tmp |= byte_arr[i + 1] << 1; |
| | | dst_tmp |= byte_arr[i + 2] << 2; |
| | | dst_tmp |= byte_arr[i + 3] << 3; |
| | | dst_tmp |= byte_arr[i + 4] << 4; |
| | | dst_tmp |= byte_arr[i + 5] << 5; |
| | | dst_tmp |= byte_arr[i + 6] << 6; |
| | | dst_tmp |= byte_arr[i + 7] << 7; |
| | | dst[i / 8] = dst_tmp; |
| | | } |
| | | free(byte_arr); |
| | | } |
| | | #endif // __x86_64 |
| | | |
| | | void gemm_nt(int M, int N, int K, float ALPHA, |
| | |
| | | #ifndef GEMM_H |
| | | #define GEMM_H |
| | | |
| | | static inline void set_bit(unsigned char *const dst, size_t index) { |
| | | size_t dst_i = index / 8; |
| | | int dst_shift = index % 8; |
| | | dst[dst_i] |= 1 << dst_shift; |
| | | } |
| | | |
| | | static inline unsigned char get_bit(unsigned char const*const src, size_t index) { |
| | | size_t src_i = index / 8; |
| | | int src_shift = index % 8; |
| | | unsigned char val = (src[src_i] & (1 << src_shift)) > 0; |
| | | return val; |
| | | } |
| | | |
| | | void float_to_bit(float *src, unsigned char *dst, size_t size); |
| | | |
| | | 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, |
| | | float *C, int ldc, float *mean_arr); |
| | | |
| | | |
| | | //void gemm_nn_custom_bin_mean(int M, int N, int K, float ALPHA_UNUSED, |
| | | //unsigned char *A, int lda, |
| | | //unsigned char *B, int ldb, |
| | | //float *C, int ldc, float *mean_arr) |
| | | |
| | | |
| | | |
| | | void gemm_bin(int M, int N, int K, float ALPHA, |
| | | char *A, int lda, |
| | | float *B, int ldb, |
| | |
| | | if (l.scale_updates) free(l.scale_updates); |
| | | if (l.weights) free(l.weights); |
| | | if (l.weight_updates) free(l.weight_updates); |
| | | if (l.weights) free(l.align_bit_weights); |
| | | if (l.weights) free(l.mean_arr); |
| | | if (l.delta) free(l.delta); |
| | | if (l.output) free(l.output); |
| | | if (l.squared) free(l.squared); |
| | |
| | | float *weights; |
| | | float *weight_updates; |
| | | |
| | | char *align_bit_weights; |
| | | float *mean_arr; |
| | | |
| | | float *col_image; |
| | | int * input_layers; |
| | | int * input_sizes; |
| | |
| | | } |
| | | } |
| | | } |
| | | |
| | | |
| | | |
| | | void calculate_binary_weights(network net) |
| | | { |
| | | int j; |
| | | for (j = 0; j < net.n; ++j) { |
| | | layer *l = &net.layers[j]; |
| | | |
| | | if (l->type == CONVOLUTIONAL) { |
| | | //printf(" Merges Convolutional-%d and batch_norm \n", j); |
| | | |
| | | if (l->xnor) { |
| | | //printf("\n %d \n", j); |
| | | size_t ldb_align = 256; // 256bit for AVX2 |
| | | binary_transpose_align_weights(l, ldb_align); |
| | | } |
| | | } |
| | | } |
| | | //printf("\n calculate_binary_weights Done! \n"); |
| | | |
| | | } |
| | |
| | | int get_network_nuisance(network net); |
| | | int get_network_background(network net); |
| | | YOLODLL_API void fuse_conv_batchnorm(network net); |
| | | YOLODLL_API void calculate_binary_weights(network net); |
| | | |
| | | #ifdef __cplusplus |
| | | } |