#include "config.h" #include #include #include #include #include #include #include "kautodiff.h" typedef struct { uint64_t s[2]; double n_gset; int n_iset; volatile int lock; } kad_rng_t; /********************** * Graph construction * **********************/ static inline kad_node_t *kad_new_core(int n_d, int op, int n_child) { kad_node_t *s; if (n_d >= KAD_MAX_DIM) return 0; s = (kad_node_t*)calloc(1, sizeof(kad_node_t)); s->n_d = n_d, s->op = op, s->n_child = n_child; if (s->n_child) s->child = (kad_node_t**)calloc(s->n_child, sizeof(kad_node_t*)); return s; } static inline kad_node_t *kad_vleaf(uint8_t flag, float *x, float *g, int n_d, va_list ap) { int i; kad_node_t *p; if (n_d > KAD_MAX_DIM) return 0; p = (kad_node_t*)calloc(1, sizeof(kad_node_t)); p->n_d = n_d; for (i = 0; i < n_d; ++i) p->d[i] = va_arg(ap, int32_t); p->x = x, p->g = g, p->flag = flag; return p; } kad_node_t *kad_const(float *x, int n_d, ...) { kad_node_t *p; va_list ap; va_start(ap, n_d); p = kad_vleaf(KAD_CONST, x, 0, n_d, ap); va_end(ap); return p; } kad_node_t *kad_feed(int n_d, ...) { kad_node_t *p; va_list ap; va_start(ap, n_d); p = kad_vleaf(0, 0, 0, n_d, ap); va_end(ap); return p; } kad_node_t *kad_var(float *x, float *g, int n_d, ...) { kad_node_t *p; va_list ap; va_start(ap, n_d); p = kad_vleaf(KAD_VAR, x, g, n_d, ap); va_end(ap); return p; } static inline kad_node_t *kad_finalize_node(kad_node_t *s) /* a helper function */ { int i; if (kad_op_list[s->op](s, KAD_SYNC_DIM) < 0) { /* check dimension */ if (s->ptr) free(s->ptr); free(s->child); free(s); return 0; } for (i = 0; i < s->n_child; ++i) if (kad_is_back(s->child[i])) break; if (i < s->n_child) s->flag |= KAD_VAR; return s; } /********** Simple arithmetic **********/ static inline kad_node_t *kad_op2_core(int op, kad_node_t *x, kad_node_t *y) { kad_node_t *s; s = kad_new_core(0, op, 2); s->child[0] = x, s->child[1] = y; return kad_finalize_node(s); } static inline kad_node_t *kad_op1_core(int op, kad_node_t *x) { kad_node_t *s; s = kad_new_core(0, op, 1); s->child[0] = x; return kad_finalize_node(s); } #define KAD_FUNC_OP2(fname, op) kad_node_t *fname(kad_node_t *x, kad_node_t *y) { return kad_op2_core((op), x, y); } KAD_FUNC_OP2(kad_add, 1) KAD_FUNC_OP2(kad_sub, 23) KAD_FUNC_OP2(kad_mul, 2) KAD_FUNC_OP2(kad_cmul, 3) KAD_FUNC_OP2(kad_matmul, 9) KAD_FUNC_OP2(kad_ce_multi, 13) KAD_FUNC_OP2(kad_ce_bin, 22) KAD_FUNC_OP2(kad_ce_bin_neg, 4) KAD_FUNC_OP2(kad_mse, 29) #define KAD_FUNC_OP1(fname, op) kad_node_t *fname(kad_node_t *x) { return kad_op1_core((op), x); } KAD_FUNC_OP1(kad_log, 27) KAD_FUNC_OP1(kad_exp, 33) KAD_FUNC_OP1(kad_sin, 34) KAD_FUNC_OP1(kad_square, 5) KAD_FUNC_OP1(kad_sigm, 6) KAD_FUNC_OP1(kad_tanh, 7) KAD_FUNC_OP1(kad_relu, 8) KAD_FUNC_OP1(kad_1minus, 11) KAD_FUNC_OP1(kad_softmax, 14) KAD_FUNC_OP1(kad_stdnorm, 32) kad_node_t *kad_ce_multi_weighted(kad_node_t *pred, kad_node_t *truth, kad_node_t *weight) { kad_node_t *s; s = kad_new_core(0, 13, 3); s->child[0] = pred, s->child[1] = truth, s->child[2] = weight; return kad_finalize_node(s); } /********** Convolution **********/ /* compute output dimension and padding sizes on both sides */ static inline int conv_find_par(int in_size, int kernel_size, int stride, int pad0, int *new_pad0, int *new_pad1) { int out_size, pad_both; /* key equation: out_size = (in_size - kernel_size + pad_both) / stride + 1 */ if (pad0 == KAD_PAD_SAME && stride == 1) out_size = in_size; else out_size = (in_size - kernel_size + (pad0 > 0? pad0 : 0) + stride - 1) / stride + 1; pad_both = (out_size - 1) * stride + kernel_size - in_size; *new_pad0 = pad_both / 2; *new_pad1 = pad_both - *new_pad0; return out_size; } typedef struct { int kernel_size, stride, pad[2]; } conv_conf_t; static inline conv_conf_t *conv2d_gen_aux(int in_row, int in_col, int kernel_r, int kernel_c, int stride_r, int stride_c, int top_pad, int left_pad) { conv_conf_t *cnn; cnn = (conv_conf_t*)calloc(2, sizeof(conv_conf_t)); cnn[0].kernel_size = kernel_r, cnn[0].stride = stride_r; cnn[1].kernel_size = kernel_c, cnn[1].stride = stride_c; conv_find_par(in_row, kernel_r, stride_r, top_pad, &cnn[0].pad[0], &cnn[0].pad[1]); conv_find_par(in_col, kernel_c, stride_c, left_pad, &cnn[1].pad[0], &cnn[1].pad[1]); return cnn; } kad_node_t *kad_conv2d(kad_node_t *x, kad_node_t *w, int stride_r, int stride_c, int top_pad, int left_pad) { kad_node_t *s; if (x->n_d != 4 || w->n_d != 4) return 0; s = kad_new_core(0, 16, 2); s->child[0] = x, s->child[1] = w; s->ptr = conv2d_gen_aux(x->d[2], x->d[3], w->d[2], w->d[3], stride_r, stride_c, top_pad, left_pad); s->ptr_size = sizeof(conv_conf_t) * 2; return kad_finalize_node(s); } kad_node_t *kad_max2d(kad_node_t *x, int kernel_r, int kernel_c, int stride_r, int stride_c, int top_pad, int left_pad) { kad_node_t *s; if (x->n_d != 4) return 0; s = kad_new_core(0, 17, 1); s->child[0] = x; s->ptr = conv2d_gen_aux(x->d[2], x->d[3], kernel_r, kernel_c, stride_r, stride_c, top_pad, left_pad); s->ptr_size = sizeof(conv_conf_t) * 2; return kad_finalize_node(s); } static inline conv_conf_t *conv1d_gen_aux(int in_col, int kernel_c, int stride_c, int left_pad) { conv_conf_t *cnn; cnn = (conv_conf_t*)calloc(1, sizeof(conv_conf_t)); cnn->kernel_size = kernel_c, cnn->stride = stride_c; conv_find_par(in_col, kernel_c, stride_c, left_pad, &cnn->pad[0], &cnn->pad[1]); return cnn; } kad_node_t *kad_conv1d(kad_node_t *x, kad_node_t *w, int stride, int left_pad) { kad_node_t *s; if (x->n_d != 3 || w->n_d != 3) return 0; s = kad_new_core(0, 18, 2); s->child[0] = x, s->child[1] = w; s->ptr = conv1d_gen_aux(x->d[2], w->d[2], stride, left_pad); s->ptr_size = sizeof(conv_conf_t); return kad_finalize_node(s); } kad_node_t *kad_max1d(kad_node_t *x, int kernel_size, int stride, int left_pad) { kad_node_t *s; if (x->n_d != 3) return 0; s = kad_new_core(0, 19, 1); s->child[0] = x; s->ptr = conv1d_gen_aux(x->d[2], kernel_size, stride, left_pad); s->ptr_size = sizeof(conv_conf_t); return kad_finalize_node(s); } kad_node_t *kad_avg1d(kad_node_t *x, int kernel_size, int stride, int left_pad) { kad_node_t *s; if (x->n_d != 3) return 0; s = kad_new_core(0, 28, 1); s->child[0] = x; s->ptr = conv1d_gen_aux(x->d[2], kernel_size, stride, left_pad); s->ptr_size = sizeof(conv_conf_t); return kad_finalize_node(s); } /********** Multi-node pooling **********/ static kad_node_t *kad_pooling_general(int op, int n, kad_node_t **x) { int i; kad_node_t *s; s = kad_new_core(0, op, n); s->flag |= KAD_POOL; for (i = 0; i < n; ++i) s->child[i] = x[i]; return kad_finalize_node(s); } kad_node_t *kad_avg(int n, kad_node_t **x) { return kad_pooling_general(10, n, x); } kad_node_t *kad_max(int n, kad_node_t **x) { return kad_pooling_general(21, n, x); } kad_node_t *kad_stack(int n, kad_node_t **x) { return kad_pooling_general(35, n, x); } kad_node_t *kad_select(int n, kad_node_t **x, int which) { kad_node_t *s; int32_t i, *aux; aux = (int32_t*)calloc(1, 4); *aux = which; s = kad_new_core(0, 12, n); for (i = 0; i < n; ++i) s->child[i] = x[i]; s->flag |= KAD_POOL, s->ptr = aux, s->ptr_size = 4; return kad_finalize_node(s); } /********** Dimension reduction **********/ static kad_node_t *kad_reduce_general(int op, kad_node_t *x, int axis) { kad_node_t *s; int32_t *aux; aux = (int32_t*)malloc(4); aux[0] = axis; s = kad_new_core(0, op, 1); s->child[0] = x; s->ptr = aux, s->ptr_size = 4; return kad_finalize_node(s); } kad_node_t *kad_reduce_sum(kad_node_t *x, int axis) { return kad_reduce_general(25, x, axis); } kad_node_t *kad_reduce_mean(kad_node_t *x, int axis) { return kad_reduce_general(26, x, axis); } /********** Sampling related **********/ kad_node_t *kad_dropout(kad_node_t *x, kad_node_t *y) { kad_node_t *z; z = kad_op2_core(15, x, y); z->ptr = kad_rng(), z->ptr_size = sizeof(kad_rng_t); return z; } kad_node_t *kad_sample_normal(kad_node_t *x) { kad_node_t *z; z = kad_op1_core(24, x); z->ptr = kad_rng(), z->ptr_size = sizeof(kad_rng_t); return z; } /********** Miscellaneous **********/ kad_node_t *kad_slice(kad_node_t *x, int axis, int start, int end) { kad_node_t *s; int32_t *aux; if (end < start || start < 0) return 0; aux = (int32_t*)malloc(3 * 4); aux[0] = axis, aux[1] = start, aux[2] = end; s = kad_new_core(0, 20, 1); s->child[0] = x; s->ptr = aux, s->ptr_size = 3 * 4; return kad_finalize_node(s); } kad_node_t *kad_concat_array(int axis, int n, kad_node_t **p) { kad_node_t *s; int32_t i, *aux; aux = (int32_t*)malloc(4); aux[0] = axis; s = kad_new_core(0, 31, n); for (i = 0; i < n; ++i) s->child[i] = p[i]; s->ptr = aux, s->ptr_size = 4; return kad_finalize_node(s); } kad_node_t *kad_concat(int axis, int n, ...) { int i; kad_node_t **p, *s; va_list ap; p = (kad_node_t**)malloc(n * sizeof(kad_node_t*)); va_start(ap, n); for (i = 0; i < n; ++i) p[i] = va_arg(ap, kad_node_p); va_end(ap); s = kad_concat_array(axis, n, p); free(p); return s; } kad_node_t *kad_reshape(kad_node_t *x, int n_d, int *d) { kad_node_t *s; int32_t i, *aux = 0; if (n_d > 0) { aux = (int32_t*)malloc(n_d * 4); for (i = 0; i < n_d; ++i) aux[i] = d? d[i] : -1; } s = kad_new_core(0, 30, 1); s->child[0] = x, s->ptr = aux, s->ptr_size = n_d * 4; return kad_finalize_node(s); } kad_node_t *kad_reverse(kad_node_t *x, int axis) { kad_node_t *s; int32_t *aux; aux = (int32_t*)malloc(4); *aux = axis; s = kad_new_core(0, 36, 1); s->child[0] = x, s->ptr = aux, s->ptr_size = 4; return kad_finalize_node(s); } kad_node_t *kad_switch(int n, kad_node_t **p) { kad_node_t *s; int32_t i, *aux; aux = (int32_t*)calloc(1, 4); s = kad_new_core(0, 12, n); for (i = 0; i < n; ++i) s->child[i] = p[i]; s->ptr = aux, s->ptr_size = 4; return kad_finalize_node(s); } /*********************** * Graph linearization * ***********************/ static void kad_mark_back(int n, kad_node_t **v) { int i, j; for (i = 0; i < n; ++i) { if (v[i]->n_child == 0) continue; for (j = 0; j < v[i]->n_child; ++j) if (kad_is_back(v[i]->child[j])) break; if (j < v[i]->n_child) v[i]->flag |= KAD_VAR; else v[i]->flag &= ~KAD_VAR; } } static void kad_allocate_internal(int n, kad_node_t **v) { int i; kad_mark_back(n, v); for (i = 0; i < n; ++i) { kad_node_t *p = v[i]; if (p->n_child == 0) continue; p->x = (float*)realloc(p->x, kad_len(p) * sizeof(float)); if (kad_is_back(p)) { p->g = (float*)realloc(p->g, kad_len(p) * sizeof(float)); kad_op_list[p->op](p, KAD_ALLOC); } } } int kad_sync_dim(int n, kad_node_t **v, int batch_size) { int i, req_alloc = 0, req_sync = 0, old_size = 0; for (i = 0; i < n; ++i) { if (kad_is_feed(v[i])) { old_size = v[i]->d[0]; /* TODO: check if all feeds have the same batch size */ if (batch_size > 0 && v[i]->d[0] != batch_size) v[i]->d[0] = batch_size, req_sync = 1; } else if (v[i]->n_child > 0 && req_sync) kad_op_list[v[i]->op](v[i], KAD_SYNC_DIM); } if (old_size < batch_size) req_alloc = 1; for (i = 0; i < n; ++i) if (v[i]->n_child > 0 && v[i]->x == 0) req_alloc = 1; if (req_alloc) kad_allocate_internal(n, v); return batch_size > 0? batch_size : old_size; } #define kvec_t(type) struct { size_t n, m; type *a; } #define kv_pop(v) ((v).a[--(v).n]) #define kv_push(type, v, x) do { \ if ((v).n == (v).m) { \ (v).m = (v).m? (v).m<<1 : 2; \ (v).a = (type*)realloc((v).a, sizeof(type) * (v).m); \ } \ (v).a[(v).n++] = (x); \ } while (0) /* IMPORTANT: kad_node_t::tmp MUST BE set to zero before calling this function */ kad_node_t **kad_compile_array(int *n_node, int n_roots, kad_node_t **roots) { int i; kvec_t(kad_node_p) stack = {0,0,0}, a = {0,0,0}; /* generate kad_node_t::tmp, the count of the parent nodes; shifted by 1; lowest bit to detect fake roots */ for (i = 0; i < n_roots; ++i) { roots[i]->tmp = 1; /* mark the root */ kv_push(kad_node_p, stack, roots[i]); } while (stack.n) { kad_node_t *p = kv_pop(stack); for (i = 0; i < p->n_child; ++i) { kad_node_t *q = p->child[i]; if (q->tmp == 0) kv_push(kad_node_p, stack, q); q->tmp += 1<<1; } } /* topological sorting (Kahn's algorithm) */ for (i = 0; i < n_roots; ++i) if (roots[i]->tmp>>1 == 0) /* if roots[i]->tmp>>1 != 0, it is not a real root */ kv_push(kad_node_p, stack, roots[i]); while (stack.n) { kad_node_t *p = kv_pop(stack); kv_push(kad_node_p, a, p); for (i = 0; i < p->n_child; ++i) { p->child[i]->tmp -= 1<<1; if (p->child[i]->tmp>>1 == 0) kv_push(kad_node_p, stack, p->child[i]); } } free(stack.a); for (i = 0; i < (int)a.n; ++i) { /* check cycles; no cycles if constructed with kad_add() etc */ assert(a.a[i]->tmp>>1 == 0); a.a[i]->tmp = 0; } /* reverse */ for (i = 0; i < (int)a.n>>1; ++i) { /* reverse a.a[] */ kad_node_p t; t = a.a[i], a.a[i] = a.a[a.n-1-i], a.a[a.n-1-i] = t; } kad_allocate_internal(a.n, a.a); *n_node = a.n; return a.a; } kad_node_t **kad_compile(int *n_node, int n_roots, ...) { int i; kad_node_t **roots, **ret; va_list ap; roots = (kad_node_t**)malloc(n_roots * sizeof(kad_node_t*)); va_start(ap, n_roots); for (i = 0; i < n_roots; ++i) roots[i] = va_arg(ap, kad_node_p); va_end(ap); ret = kad_compile_array(n_node, n_roots, roots); free(roots); return ret; } /************************************ * Miscellaneous on compiled graphs * ************************************/ void kad_delete(int n, kad_node_t **a) { int i; for (i = 0; i < n; ++i) { kad_node_t *p = a[i]; if (p->n_child) { free(p->x); free(p->g); } free(p->child); free(p->ptr); free(p->gtmp); free(p); } free(a); } int kad_size_var(int n, kad_node_t *const* v) { int c, i; for (i = c = 0; i < n; ++i) if (kad_is_var(v[i])) c += kad_len(v[i]); return c; } int kad_size_const(int n, kad_node_t *const* v) { int c, i; for (i = c = 0; i < n; ++i) if (kad_is_const(v[i])) c += kad_len(v[i]); return c; } /********************************** * Computate values and gradients * **********************************/ static void kad_propagate_marks(int n, kad_node_t **a) { int i, j; for (i = n - 1; i >= 0; --i) { kad_node_t *p = a[i]; if (p->tmp > 0) { if (kad_is_switch(p)) { int32_t *aux = (int32_t*)p->ptr; if (p->child[*aux]->tmp == 0) p->child[*aux]->tmp = 1; } else { for (j = 0; j < p->n_child; ++j) if (p->child[j]->tmp == 0) p->child[j]->tmp = 1; } } } } void kad_eval_marked(int n, kad_node_t **a) { int i; kad_propagate_marks(n, a); for (i = 0; i < n; ++i) if (a[i]->n_child && a[i]->tmp > 0) kad_op_list[a[i]->op](a[i], KAD_FORWARD); for (i = 0; i < n; ++i) a[i]->tmp = 0; } const float *kad_eval_at(int n, kad_node_t **a, int from) { int i; if (from < 0 || from >= n) from = n - 1; for (i = 0; i < n; ++i) a[i]->tmp = (i == from); kad_eval_marked(n, a); return a[from]->x; } void kad_grad(int n, kad_node_t **a, int from) { int i; if (from < 0 || from >= n) from = n - 1; assert(a[from]->n_d == 0); for (i = 0; i < n; ++i) a[i]->tmp = (i == from); kad_propagate_marks(n, a); for (i = 0; i <= from; ++i) /* set all grandients to zero */ if (a[i]->g && a[i]->tmp > 0) memset(a[i]->g, 0, kad_len(a[i]) * sizeof(float)); for (i = from, a[i]->g[0] = 1.0f; i >= 0; --i) /* backprop */ if (a[i]->n_child && a[i]->tmp > 0) kad_op_list[a[i]->op](a[i], KAD_BACKWARD); for (i = 0; i <= from; ++i) a[i]->tmp = 0; } /*********************** * Load and save graph * ***********************/ static void kad_save1(FILE *fp, const kad_node_t *p) { fwrite(&p->ext_label, 4, 1, fp); fwrite(&p->ext_flag, 4, 1, fp); fwrite(&p->flag, 1, 1, fp); fwrite(&p->n_child, 4, 1, fp); if (p->n_child) { int32_t j, pre = p->pre? p->pre->tmp : -1; fwrite(&p->op, 2, 1, fp); for (j = 0; j < p->n_child; ++j) fwrite(&p->child[j]->tmp, 4, 1, fp); fwrite(&pre, 4, 1, fp); fwrite(&p->ptr_size, 4, 1, fp); if (p->ptr_size > 0 && p->ptr) fwrite(p->ptr, p->ptr_size, 1, fp); } else { fwrite(&p->n_d, 1, 1, fp); if (p->n_d) fwrite(p->d, 4, p->n_d, fp); } } static kad_node_t *kad_load1(FILE *fp, kad_node_t **node) { kad_node_t *p; p = (kad_node_t*)calloc(1, sizeof(kad_node_t)); (void) !fread(&p->ext_label, 4, 1, fp); (void) !fread(&p->ext_flag, 4, 1, fp); (void) !fread(&p->flag, 1, 1, fp); (void) !fread(&p->n_child, 4, 1, fp); if (p->n_child) { int32_t j, k; p->child = (kad_node_t**)calloc(p->n_child, sizeof(kad_node_t*)); (void) !fread(&p->op, 2, 1, fp); for (j = 0; j < p->n_child; ++j) { (void) !fread(&k, 4, 1, fp); p->child[j] = node? node[k] : 0; } (void) !fread(&k, 4, 1, fp); if (k >= 0) p->pre = node[k]; (void) !fread(&p->ptr_size, 4, 1, fp); if (p->ptr_size > 0) { p->ptr = malloc(p->ptr_size); (void) !fread(p->ptr, p->ptr_size, 1, fp); } } else { (void) !fread(&p->n_d, 1, 1, fp); if (p->n_d) (void) !fread(p->d, 4, p->n_d, fp); } return p; } int kad_save(FILE *fp, int n_node, kad_node_t **node) { int32_t i, k = n_node; fwrite(&k, 4, 1, fp); for (i = 0; i < n_node; ++i) node[i]->tmp = i; for (i = 0; i < n_node; ++i) kad_save1(fp, node[i]); for (i = 0; i < n_node; ++i) node[i]->tmp = 0; return 0; } kad_node_t **kad_load(FILE *fp, int *_n_node) { int32_t i, n_node; kad_node_t **node; (void) !fread(&n_node, 4, 1, fp); node = (kad_node_t**)malloc(n_node * sizeof(kad_node_t*)); for (i = 0; i < n_node; ++i) { kad_node_t *p; p = node[i] = kad_load1(fp, node); if (p->n_child) { kad_op_list[p->op](p, KAD_ALLOC); kad_op_list[p->op](p, KAD_SYNC_DIM); } } *_n_node = n_node; kad_mark_back(n_node, node); return node; } /*************** * Graph clone * ***************/ static inline kad_node_t *kad_dup1(const kad_node_t *p) { kad_node_t *q; q = (kad_node_t*)malloc(sizeof(kad_node_t)); memcpy(q, p, sizeof(kad_node_t)); q->pre = 0, q->tmp = 0, q->gtmp = 0; if (p->ptr && p->ptr_size > 0) { if (kad_use_rng(p) && !(p->flag & KAD_SHARE_RNG) && p->ptr_size == sizeof(kad_rng_t)) { q->ptr = kad_rng(); /* each time step uses a different RNG */ } else { q->ptr = malloc(p->ptr_size); memcpy(q->ptr, p->ptr, p->ptr_size); } } if (q->n_child) { q->x = q->g = 0; q->child = (kad_node_t**)calloc(q->n_child, sizeof(kad_node_t*)); } return q; } kad_node_t **kad_clone(int n, kad_node_t **v, int batch_size) { int i, j; kad_node_t **u; u = (kad_node_t**)calloc(n, sizeof(kad_node_t*)); for (i = 0; i < n; ++i) v[i]->tmp = i; for (i = 0; i < n; ++i) { kad_node_t *p = v[i], *q; q = u[i] = kad_dup1(p); if (p->pre) q->pre = u[p->pre->tmp]; if (p->n_child) { for (j = 0; j < p->n_child; ++j) q->child[j] = u[p->child[j]->tmp]; } else if (!kad_is_feed(p)) { q->x = (float*)malloc(kad_len(p) * sizeof(float)); memcpy(q->x, p->x, kad_len(p) * sizeof(float)); q->g = 0; } } for (i = 0; i < n; ++i) v[i]->tmp = 0; kad_sync_dim(n, u, batch_size); /* this will allocate x[] and g[] at internal nodes */ return u; } /************** * Unroll RNN * **************/ typedef struct { int32_t n, m; kad_node_t **v; } nodes_t; static inline void push_nodes(nodes_t *w, kad_node_t *p) { if (w->n == w->m) { w->m = w->m? w->m<<1 : 16; w->v = (kad_node_t**)realloc(w->v, w->m * sizeof(kad_node_t*)); } w->v[w->n++] = p; } static void kad_unroll_helper(int n_v, kad_node_t **v, int i_pivot, kad_node_t **t, int len, nodes_t *w) { int i, j, l; uint8_t *flag; kad_node_t **aux; assert(kad_is_pivot(v[i_pivot]) && t[i_pivot] == 0); t[i_pivot] = kad_dup1(v[i_pivot]); t[i_pivot]->n_child = len; t[i_pivot]->child = (kad_node_t**)realloc(t[i_pivot]->child, len * sizeof(kad_node_t*)); flag = (uint8_t*)calloc(n_v, 1); for (i = i_pivot, flag[i] = 16; i >= 0; --i) { if (i < i_pivot && kad_is_pivot(v[i])) continue; /* don't trespass other pivots */ if (flag[i]&16) /* flag 16: nodes to unroll */ for (j = 0; j < v[i]->n_child; ++j) flag[v[i]->child[j]->tmp] = 16; } for (i = 0; i < i_pivot; ++i) { if (!(flag[i]&16)) continue; if (kad_is_var(v[i]) || kad_is_const(v[i]) || kad_is_pivot(v[i])) flag[i] |= 1; /* external nodes that should not be duplicated */ if (v[i]->pre) flag[v[i]->pre->tmp] |= 2; } flag[v[i_pivot]->child[0]->tmp] |= 4; aux = (kad_node_t**)calloc(n_v, sizeof(kad_node_t*)); for (l = 0; l < len; ++l) { for (i = 0; i < i_pivot; ++i) { if (!(flag[i]&16) || ((flag[i]&3) && t[i])) continue; t[i] = kad_dup1(v[i]); if (v[i]->n_child) for (j = 0; j < v[i]->n_child; ++j) t[i]->child[j] = t[v[i]->child[j]->tmp]; if (flag[i]&4) t[i_pivot]->child[l] = t[i]; if (l == 0 && (flag[i]&2)) aux[i] = t[i]; if (v[i]->pre) { t[v[i]->pre->tmp] = t[i]; if (l == len - 1) t[i]->pre = aux[v[i]->pre->tmp]; /* this forms a cycle! */ } push_nodes(w, t[i]); } } push_nodes(w, t[i_pivot]); free(aux); free(flag); } int kad_n_pivots(int n_v, kad_node_t **v) { int i, n_pivots = 0; for (i = 0; i < n_v; ++i) if (kad_is_pivot(v[i])) ++n_pivots; return n_pivots; } kad_node_t **kad_unroll(int n_v, kad_node_t **v, int *new_n, int *len) { int i, j, n_pivots = 0; kad_node_t **t; nodes_t w = {0,0,0}; t = (kad_node_t**)calloc(n_v, sizeof(kad_node_t*)); n_pivots = kad_n_pivots(n_v, v); for (i = 0; i < n_v; ++i) v[i]->tmp = i; if (n_pivots) { int k, *i_pivots; i_pivots = (int*)calloc(n_pivots, sizeof(int)); for (i = k = 0; i < n_v; ++i) /* collect pivots */ if (kad_is_pivot(v[i])) i_pivots[k++] = i; for (i = 0; i < n_pivots; ++i) /* unroll each pivot, from the lowest to the highest */ kad_unroll_helper(n_v, v, i_pivots[i], t, len[i], &w); free(i_pivots); } for (i = 0; i < n_v; ++i) { /* copy over the rest of nodes */ if (t[i]) continue; t[i] = kad_dup1(v[i]); if (v[i]->n_child) for (j = 0; j < v[i]->n_child; ++j) t[i]->child[j] = t[v[i]->child[j]->tmp]; push_nodes(&w, t[i]); } free(t); for (i = 0; i < n_v; ++i) v[i]->tmp = 0; for (i = 0; i < w.n; ++i) /* stack may change the output dimension */ if (w.v[i]->n_child > 0) kad_op_list[w.v[i]->op](w.v[i], KAD_SYNC_DIM); kad_allocate_internal(w.n, w.v); *new_n = w.n; return w.v; } /******************************** * Vector and matrix operations * ********************************/ #ifdef __SSE__ #include static inline float kad_sdot(int n, const float *x, const float *y) /* BLAS sdot using SSE */ { int i, n8 = n>>3<<3; __m128 vs1, vs2; float s, t[4]; vs1 = _mm_setzero_ps(); vs2 = _mm_setzero_ps(); for (i = 0; i < n8; i += 8) { __m128 vx1, vx2, vy1, vy2; vx1 = _mm_loadu_ps(&x[i]); vx2 = _mm_loadu_ps(&x[i+4]); vy1 = _mm_loadu_ps(&y[i]); vy2 = _mm_loadu_ps(&y[i+4]); vs1 = _mm_add_ps(vs1, _mm_mul_ps(vx1, vy1)); vs2 = _mm_add_ps(vs2, _mm_mul_ps(vx2, vy2)); } for (s = 0.; i < n; ++i) s += x[i] * y[i]; _mm_storeu_ps(t, vs1); s += t[0] + t[1] + t[2] + t[3]; _mm_storeu_ps(t, vs2); s += t[0] + t[1] + t[2] + t[3]; return s; } static inline void kad_saxpy_inlined(int n, float a, const float *x, float *y) /* BLAS saxpy using SSE */ { int i, n8 = n>>3<<3; __m128 va; va = _mm_set1_ps(a); for (i = 0; i < n8; i += 8) { __m128 vx1, vx2, vy1, vy2, vt1, vt2; vx1 = _mm_loadu_ps(&x[i]); vx2 = _mm_loadu_ps(&x[i+4]); vy1 = _mm_loadu_ps(&y[i]); vy2 = _mm_loadu_ps(&y[i+4]); vt1 = _mm_add_ps(_mm_mul_ps(va, vx1), vy1); vt2 = _mm_add_ps(_mm_mul_ps(va, vx2), vy2); _mm_storeu_ps(&y[i], vt1); _mm_storeu_ps(&y[i+4], vt2); } for (; i < n; ++i) y[i] += a * x[i]; } #else static inline float kad_sdot(int n, const float *x, const float *y) /* BLAS sdot */ { int i; float s = 0.; for (i = 0; i < n; ++i) s += x[i] * y[i]; return s; } static inline void kad_saxpy_inlined(int n, float a, const float *x, float *y) // BLAS saxpy { int i; for (i = 0; i < n; ++i) y[i] += a * x[i]; } #endif void kad_vec_mul_sum(int n, float *a, const float *b, const float *c) { int i; for (i = 0; i < n; ++i) a[i] += b[i] * c[i]; } void kad_saxpy(int n, float a, const float *x, float *y) { kad_saxpy_inlined(n, a, x, y); } #ifdef HAVE_CBLAS #ifndef __APPLE__ /* As gfortran mangles names */ #define ssyev ssyev_ #endif extern void ssyev(const char* jobz, const char* uplo, int* n, float* a, int* lda, float* w, float* work, int* lwork, int* info); #ifdef HAVE_CBLAS_H #include "cblas.h" #else /* Poor man approach */ enum CBLAS_ORDER {CblasRowMajor=101, CblasColMajor=102 }; enum CBLAS_TRANSPOSE {CblasNoTrans=111, CblasTrans=112 }; extern void cblas_sgemm(const enum CBLAS_ORDER Order, const enum CBLAS_TRANSPOSE TA, const enum CBLAS_TRANSPOSE TB, const int M, const int N, const int K, const float alpha, const float *A, const int lda, const float *B, const int ldb, const float beta, float *C, const int ldc); #endif void kad_sgemm_simple(int trans_A, int trans_B, int M, int N, int K, const float *A, const float *B, float *C) { cblas_sgemm(CblasRowMajor, trans_A? CblasTrans : CblasNoTrans, trans_B? CblasTrans : CblasNoTrans, M, N, K, 1.0f, A, trans_A? M : K, B, trans_B? K : N, 1.0f, C, N); } #else void kad_sgemm_simple(int trans_A, int trans_B, int M, int N, int K, const float *A, const float *B, float *C) /* simplified BLAS sgemm */ { static const int x = 16; int i, j, k; if (!trans_A && trans_B) { for (i = 0; i < M; i += x) for (j = 0; j < N; j += x) { int ii, ie = M < i + x? M : i + x; int jj, je = N < j + x? N : j + x; for (ii = i; ii < ie; ++ii) { /* loop tiling */ const float *aii = A + ii * K, *bjj; float *cii = C + ii * N; for (jj = j, bjj = B + j * K; jj < je; ++jj, bjj += K) cii[jj] += kad_sdot(K, aii, bjj); } } } else if (!trans_A && !trans_B) { for (i = 0; i < M; ++i) for (k = 0; k < K; ++k) kad_saxpy_inlined(N, A[i*K+k], &B[k*N], &C[i*N]); } else if (trans_A && !trans_B) { for (k = 0; k < K; ++k) for (i = 0; i < M; ++i) kad_saxpy_inlined(N, A[k*M+i], &B[k*N], &C[i*N]); } else abort(); /* not implemented for (trans_A && trans_B) */ } #endif bool kad_ssyev_simple(int N, float *A, float *eigenvals) { #ifndef HAVE_CBLAS return false; #else int n = N, lda = N, info, lwork; float wkopt; float *work; /* Query and allocate the optimal workspace */ lwork = -1; ssyev ("Vectors", "Upper", &n, A, &lda, eigenvals, &wkopt, &lwork, &info); lwork = wkopt; work = (float*) g_malloc(lwork * sizeof(double)); ssyev ("Vectors", "Upper", &n, A, &lda, eigenvals, work, &lwork, &info); /* Check for convergence */ if (info > 0) { g_free (work); return false; } g_free (work); return true; #endif } /*************************** * Random number generator * ***************************/ static kad_rng_t kad_rng_dat = { {0x50f5647d2380309dULL, 0x91ffa96fc4c62cceULL}, 0.0, 0, 0 }; static inline uint64_t kad_splitmix64(uint64_t x) { uint64_t z = (x += 0x9E3779B97F4A7C15ULL); z = (z ^ (z >> 30)) * 0xBF58476D1CE4E5B9ULL; z = (z ^ (z >> 27)) * 0x94D049BB133111EBULL; return z ^ (z >> 31); } static inline uint64_t kad_xoroshiro128plus_next(kad_rng_t *r) { const uint64_t s0 = r->s[0]; uint64_t s1 = r->s[1]; const uint64_t result = s0 + s1; s1 ^= s0; r->s[0] = (s0 << 55 | s0 >> 9) ^ s1 ^ (s1 << 14); r->s[1] = s0 << 36 | s0 >> 28; return result; } static inline void kad_xoroshiro128plus_jump(kad_rng_t *r) { static const uint64_t JUMP[] = { 0xbeac0467eba5facbULL, 0xd86b048b86aa9922ULL }; uint64_t s0 = 0, s1 = 0; int i, b; for (i = 0; i < 2; ++i) for (b = 0; b < 64; b++) { if (JUMP[i] & 1ULL << b) s0 ^= r->s[0], s1 ^= r->s[1]; kad_xoroshiro128plus_next(r); } r->s[0] = s0, r->s[1] = s1; } void kad_srand(void *d, uint64_t seed) { kad_rng_t *r = d? (kad_rng_t*)d : &kad_rng_dat; r->n_gset = 0.0, r->n_iset = 0; r->s[0] = kad_splitmix64(seed); r->s[1] = kad_splitmix64(r->s[0]); } void *kad_rng(void) { kad_rng_t *r; r = (kad_rng_t*)calloc(1, sizeof(kad_rng_t)); kad_xoroshiro128plus_jump(&kad_rng_dat); r->s[0] = kad_rng_dat.s[0], r->s[1] = kad_rng_dat.s[1]; return r; } uint64_t kad_rand(void *d) { return kad_xoroshiro128plus_next(d? (kad_rng_t*)d : &kad_rng_dat); } double kad_drand(void *d) { union { uint64_t i; double d; } u; u.i = 0x3FFULL << 52 | kad_xoroshiro128plus_next(d? (kad_rng_t*)d : &kad_rng_dat) >> 12; return u.d - 1.0; } double kad_drand_normal(void *d) { kad_rng_t *r = d? (kad_rng_t*)d : &kad_rng_dat; if (r->n_iset == 0) { double fac, rsq, v1, v2; do { v1 = 2.0 * kad_drand(d) - 1.0; v2 = 2.0 * kad_drand(d) - 1.0; rsq = v1 * v1 + v2 * v2; } while (rsq >= 1.0 || rsq == 0.0); fac = sqrt(-2.0 * log(rsq) / rsq); r->n_gset = v1 * fac; r->n_iset = 1; return v2 * fac; } else { r->n_iset = 0; return r->n_gset; } } /************* * Operators * *************/ static inline void kad_copy_dim1(kad_node_t *dst, const kad_node_t *src) /* set the dimension/shape of dst to src */ { dst->n_d = src->n_d; if (src->n_d) memcpy(dst->d, src->d, src->n_d * sizeof(int)); } /********** Arithmetic operations **********/ int kad_op_add(kad_node_t *p, int action) { int i, n0, n1; kad_node_t *q[2]; q[0] = p->child[0], n0 = kad_len(q[0]); q[1] = p->child[1], n1 = kad_len(q[1]); if (action == KAD_SYNC_DIM) { if (n0 % n1 != 0) return -1; kad_copy_dim1(p, q[0]); } else if (action == KAD_FORWARD) { assert(n0 >= n1); memcpy(p->x, q[0]->x, n0 * sizeof(float)); for (i = 0; i < n0; i += n1) kad_saxpy(n1, 1.0f, q[1]->x, p->x + i); } else if (action == KAD_BACKWARD) { if (kad_is_back(q[0])) kad_saxpy(n0, 1.0f, p->g, q[0]->g); if (kad_is_back(q[1])) for (i = 0; i < n0; i += n1) kad_saxpy(n1, 1.0f, p->g + i, q[1]->g); } return 0; } int kad_op_sub(kad_node_t *p, int action) { int i, n0, n1; kad_node_t *q[2]; q[0] = p->child[0], n0 = kad_len(q[0]); q[1] = p->child[1], n1 = kad_len(q[1]); if (action == KAD_SYNC_DIM) { if (n0 % n1 != 0) return -1; kad_copy_dim1(p, q[0]); } else if (action == KAD_FORWARD) { assert(n0 >= n1); memcpy(p->x, q[0]->x, n0 * sizeof(float)); for (i = 0; i < n0; i += n1) kad_saxpy(n1, -1.0f, q[1]->x, p->x + i); } else if (action == KAD_BACKWARD) { if (kad_is_back(q[0])) kad_saxpy(n0, 1.0f, p->g, q[0]->g); if (kad_is_back(q[1])) for (i = 0; i < n0; i += n1) kad_saxpy(n1, -1.0f, p->g + i, q[1]->g); } return 0; } int kad_op_mul(kad_node_t *p, int action) { int i, n0, n1; kad_node_t *q[2]; q[0] = p->child[0], n0 = kad_len(q[0]); q[1] = p->child[1], n1 = kad_len(q[1]); if (action == KAD_SYNC_DIM) { if (n0 % n1 != 0) return -1; kad_copy_dim1(p, q[0]); } else if (action == KAD_FORWARD) { assert(n0 >= n1); memset(p->x, 0, n0 * sizeof(float)); if (q[0]->x != 0 && q[1]->x != 0) for (i = 0; i < n0; i += n1) /* TODO: optimize when n1==1 */ kad_vec_mul_sum(n1, p->x + i, q[0]->x + i, q[1]->x); } else if (action == KAD_BACKWARD) { if (kad_is_back(q[0]) && q[1]->x) for (i = 0; i < n0; i += n1) kad_vec_mul_sum(n1, q[0]->g + i, p->g + i, q[1]->x); if (kad_is_back(q[1]) && q[0]->x) for (i = 0; i < n0; i += n1) kad_vec_mul_sum(n1, q[1]->g, p->g + i, q[0]->x + i); } return 0; } int kad_op_cmul(kad_node_t *p, int action) { int i, n_a_row, n_b_row, n_col, n_a_col = 1, n_b_col = 1; kad_node_t *q[2]; q[0] = p->child[0], q[1] = p->child[1]; n_col = q[0]->d[q[0]->n_d - 1] > q[1]->d[q[1]->n_d - 1]? q[0]->d[q[0]->n_d - 1] : q[1]->d[q[1]->n_d - 1]; for (i = q[0]->n_d - 1; i >= 0; --i) if (n_a_col < n_col) n_a_col *= q[0]->d[i]; for (i = q[1]->n_d - 1; i >= 0; --i) if (n_b_col < n_col) n_b_col *= q[1]->d[i]; n_a_row = kad_len(q[0]) / n_a_col, n_b_row = kad_len(q[1]) / n_b_col; if (action == KAD_SYNC_DIM) { if (n_a_col != n_b_col) return -1; p->n_d = 2, p->d[0] = n_a_row, p->d[1] = n_b_row; } else if (action == KAD_FORWARD) { memset(p->x, 0, n_a_row * n_b_row * sizeof(float)); if (q[0]->x && q[1]->x) kad_sgemm_simple(0, 1, n_a_row, n_b_row, n_col, q[0]->x, q[1]->x, p->x); /* Y = X * trans(W) */ } else if (action == KAD_BACKWARD) { if (kad_is_back(q[0]) && q[1]->x) kad_sgemm_simple(0, 0, n_a_row, n_col, n_b_row, p->g, q[1]->x, q[0]->g); /* G_x <- G_y * W */ if (kad_is_back(q[1]) && q[0]->x) kad_sgemm_simple(1, 0, n_b_row, n_col, n_a_row, p->g, q[0]->x, q[1]->g); /* G_w <- trans(G_y) * X */ } return 0; } int kad_op_matmul(kad_node_t *p, int action) /* TODO: matmul and cmul have different broadcasting rules */ { int n_a_row, n_b_row, n_a_col, n_b_col; kad_node_t *q[2]; q[0] = p->child[0]; q[1] = p->child[1]; n_a_row = q[0]->n_d == 1? 1 : q[0]->d[0]; n_b_row = q[1]->n_d == 1? 1 : q[1]->d[0]; n_a_col = kad_len(q[0]) / n_a_row; n_b_col = kad_len(q[1]) / n_b_row; if (action == KAD_SYNC_DIM) { if (n_a_col != n_b_row) return -1; p->n_d = 2, p->d[0] = n_a_row, p->d[1] = n_b_col; } else if (action == KAD_FORWARD) { memset(p->x, 0, n_a_row * n_b_col * sizeof(float)); if (q[0]->x && q[1]->x) kad_sgemm_simple(0, 0, n_a_row, n_b_col, n_a_col, q[0]->x, q[1]->x, p->x); /* Y = X * W */ } else if (action == KAD_BACKWARD) { if (kad_is_back(q[0]) && q[1]->x) kad_sgemm_simple(0, 1, n_a_row, n_a_col, n_b_col, p->g, q[1]->x, q[0]->g); /* G_x <- G_y * trans(W) */ if (kad_is_back(q[1]) && q[0]->x) kad_sgemm_simple(1, 0, n_b_row, n_b_col, n_a_row, q[0]->x, p->g, q[1]->g); /* G_y <- trans(A) * G_y */ } return 0; } int kad_op_square(kad_node_t *p, int action) { int i, n; kad_node_t *q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { for (i = 0; i < n; ++i) p->x[i] = q->x[i] * q->x[i]; } else if (action == KAD_BACKWARD && kad_is_back(q)) { for (i = 0; i < n; ++i) q->g[i] += p->g[i] * (q->x[i] + q->x[i]); } return 0; } int kad_op_1minus(kad_node_t *p, int action) { int i, n; kad_node_t *q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { for (i = 0; i < n; ++i) p->x[i] = 1.0f - q->x[i]; } else if (action == KAD_BACKWARD && kad_is_back(q)) { kad_saxpy(n, -1.0f, p->g, q->g); } return 0; } int kad_op_exp(kad_node_t *p, int action) { int i, n; kad_node_t *q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { for (i = 0; i < n; ++i) p->x[i] = expf(q->x[i]); } else if (action == KAD_BACKWARD && kad_is_back(q)) { for (i = 0; i < n; ++i) q->g[i] += p->g[i] * p->x[i]; } return 0; } int kad_op_log(kad_node_t *p, int action) { int i, n; kad_node_t *q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { for (i = 0; i < n; ++i) p->x[i] = logf(q->x[i]); } else if (action == KAD_BACKWARD && kad_is_back(q)) { for (i = 0; i < n; ++i) q->g[i] += p->g[i] / q->x[i]; } return 0; } int kad_op_reduce_sum(kad_node_t *p, int action) { kad_node_t *q = p->child[0]; int i, j, k, axis, d0, d1; assert(p->ptr); axis = *(int32_t*)p->ptr; if (axis < 0 || axis >= q->n_d) return -1; for (i = 0, d0 = 1; i < axis; ++i) d0 *= q->d[i]; for (i = axis + 1, d1 = 1; i < q->n_d; ++i) d1 *= q->d[i]; if (action == KAD_SYNC_DIM) { p->n_d = q->n_d - 1; for (i = j = 0; i < q->n_d; ++i) if (i != axis) p->d[j++] = q->d[i]; } else if (action == KAD_FORWARD) { memset(p->x, 0, kad_len(p) * sizeof(float)); for (i = 0; i < d0; ++i) for (j = 0; j < q->d[axis]; ++j) for (k = 0; k < d1; ++k) p->x[i * d1 + k] += q->x[(i * q->d[axis] + j) * d1 + k]; } else if (action == KAD_BACKWARD && kad_is_back(q)) { for (i = 0; i < d0; ++i) for (j = 0; j < q->d[axis]; ++j) for (k = 0; k < d1; ++k) q->g[(i * q->d[axis] + j) * d1 + k] += p->g[i * d1 + k]; } return 0; } int kad_op_reduce_mean(kad_node_t *p, int action) { kad_node_t *q = p->child[0]; int i, j, k, axis, d0, d1; assert(p->ptr); axis = *(int32_t*)p->ptr; if (axis < 0 || axis >= q->n_d) return -1; for (i = 0, d0 = 1; i < axis; ++i) d0 *= q->d[i]; for (i = axis + 1, d1 = 1; i < q->n_d; ++i) d1 *= q->d[i]; if (action == KAD_SYNC_DIM) { p->n_d = q->n_d - 1; for (i = j = 0; i < q->n_d; ++i) if (i != axis) p->d[j++] = q->d[i]; } else if (action == KAD_FORWARD) { float t = 1.0f / q->d[axis]; memset(p->x, 0, kad_len(p) * sizeof(float)); for (i = 0; i < d0; ++i) for (j = 0; j < q->d[axis]; ++j) for (k = 0; k < d1; ++k) p->x[i * d1 + k] += t * q->x[(i * q->d[axis] + j) * d1 + k]; } else if (action == KAD_BACKWARD && kad_is_back(q)) { float t = 1.0f / q->d[axis]; for (i = 0; i < d0; ++i) for (j = 0; j < q->d[axis]; ++j) for (k = 0; k < d1; ++k) q->g[(i * q->d[axis] + j) * d1 + k] += t * p->g[i * d1 + k]; } return 0; } /********** Miscellaneous **********/ int kad_op_dropout(kad_node_t *p, int action) { int i, n; kad_node_t *q = p->child[0]; assert(p->child[1]->n_d == 0); n = kad_len(q); if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_ALLOC) { if (kad_is_back(p->child[0])) p->gtmp = realloc(p->gtmp, n); } else if (action == KAD_FORWARD) { float r = kad_is_const(q) || kad_is_var(q)? 0.0f : *p->child[1]->x, z = 1.0f / (1.0f - r); uint8_t *flag = (uint8_t*)p->gtmp; for (i = 0; i < n; ++i) { int kept = (kad_drand(p->ptr) >= r); p->x[i] = kept? q->x[i] * z : 0.0f; if (flag) flag[i] = kept; } } else if (action == KAD_BACKWARD && kad_is_back(p->child[0])) { float r = kad_is_const(q) || kad_is_var(q)? 0.0f : *p->child[1]->x, z = 1.0f / (1.0f - r); uint8_t *flag = (uint8_t*)p->gtmp; for (i = 0; i < n; ++i) if (flag[i]) q->g[i] += z * p->g[i]; } return 0; } int kad_op_sample_normal(kad_node_t *p, int action) /* not tested */ { int i, n; kad_node_t *q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_ALLOC) { if (kad_is_back(p->child[0])) p->gtmp = realloc(p->gtmp, n * sizeof(float)); } else if (action == KAD_FORWARD) { float *r = (float*)p->gtmp; for (i = 0; i < n; ++i) { float z; z = (float)kad_drand_normal(p->ptr); p->x[i] = q->x[i] * z; if (r) r[i] = z; } } else if (action == KAD_BACKWARD && kad_is_back(p->child[0])) { float *r = (float*)p->gtmp; for (i = 0; i < n; ++i) q->g[i] += p->g[i] * r[i]; } return 0; } int kad_op_slice(kad_node_t *p, int action) { kad_node_t *q = p->child[0]; int32_t *aux, *range; int i, axis, d0, d1; assert(p->ptr); aux = (int32_t*)p->ptr, axis = aux[0], range = aux + 1; if (axis < 0 || axis >= q->n_d) return -1; for (i = 0, d0 = 1; i < axis; ++i) d0 *= q->d[i]; for (i = axis + 1, d1 = 1; i < q->n_d; ++i) d1 *= q->d[i]; if (action == KAD_SYNC_DIM) { if (range[0] >= range[1] || range[0] < 0 || range[1] > q->d[axis]) return -1; kad_copy_dim1(p, q); p->d[axis] = range[1] - range[0]; } else if (action == KAD_FORWARD) { for (i = 0; i < d0; ++i) memcpy(&p->x[i * p->d[axis] * d1], &q->x[(i * q->d[axis] + range[0]) * d1], (range[1] - range[0]) * d1 * sizeof(float)); } else if (action == KAD_BACKWARD && kad_is_back(q)) { for (i = 0; i < d0; ++i) kad_saxpy((range[1] - range[0]) * d1, 1.0f, &p->g[i * p->d[axis] * d1], &q->g[(i * q->d[axis] + range[0]) * d1]); } return 0; } int kad_op_concat(kad_node_t *p, int action) { kad_node_t *q = p->child[0]; int32_t *aux; int i, j, k, axis, d0, d1; assert(p->ptr); aux = (int32_t*)p->ptr, axis = aux[0]; for (i = 0, d0 = 1; i < axis; ++i) d0 *= q->d[i]; for (i = axis + 1, d1 = 1; i < q->n_d; ++i) d1 *= q->d[i]; if (action == KAD_SYNC_DIM) { for (i = 1; i < p->n_child; ++i) { if (p->child[i]->n_d != q->n_d) return -1; for (j = 0; j < q->n_d; ++j) if (j != axis && q->d[j] != p->child[i]->d[j]) return -1; } kad_copy_dim1(p, q); for (i = 1; i < p->n_child; ++i) p->d[axis] += p->child[i]->d[axis]; } else if (action == KAD_FORWARD) { for (i = 0; i < d0; ++i) for (j = k = 0; j < p->n_child; ++j) { q = p->child[j]; memcpy(&p->x[(i * p->d[axis] + k) * d1], &q->x[i * q->d[axis] * d1], q->d[axis] * d1 * sizeof(float)); k += q->d[axis]; } } else if (action == KAD_BACKWARD) { for (i = 0; i < d0; ++i) for (j = k = 0; j < p->n_child; ++j) { q = p->child[j]; if (!kad_is_back(q)) continue; kad_saxpy(q->d[axis] * d1, 1.0f, &p->g[(i * p->d[axis] + k) * d1], &q->g[i * q->d[axis] * d1]); k += q->d[axis]; } } return 0; } int kad_op_reshape(kad_node_t *p, int action) { kad_node_t *q = p->child[0]; if (action == KAD_SYNC_DIM) { if (p->ptr) { int32_t *aux = (int32_t*)p->ptr; int i, len = 1, n_missing = 0; p->n_d = p->ptr_size / 4; for (i = 0; i < p->n_d; ++i) p->d[i] = aux[i]; for (i = 0; i < p->n_d; ++i) if (p->d[i] <= 0) ++n_missing; else len *= p->d[i]; if (n_missing == 0 && len != kad_len(q)) return -1; if (n_missing > 1) { /* attempt to infer missing dimensions except the last one */ for (i = 0; i < p->n_d; ++i) if (p->d[i] <= 0 && i < q->n_d) { p->d[i] = q->d[i], len *= p->d[i]; if (--n_missing == 1) break; } if (n_missing > 1) return -1; } if (n_missing == 1) { /* infer the last missing dimension */ if (kad_len(q) % len != 0) return -1; for (i = 0; i < p->n_d; ++i) if (p->d[i] <= 0) p->d[i] = kad_len(q) / len; } } else kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { memcpy(p->x, q->x, kad_len(p) * sizeof(float)); } else if (action == KAD_BACKWARD && kad_is_back(q)) { kad_saxpy(kad_len(p), 1.0f, p->g, q->g); } return 0; } int kad_op_reverse(kad_node_t *p, int action) { kad_node_t *q = p->child[0]; int axis, i, j, n, d0, d1; axis = p->ptr? *(int32_t*)p->ptr : 0; if (axis < 0) axis += q->n_d; assert(axis >= 0 && axis < q->n_d); for (i = 0, d0 = 1; i < axis; ++i) d0 *= q->d[i]; n = q->d[axis]; for (i = axis + 1, d1 = 1; i < q->n_d; ++i) d1 *= q->d[i]; if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { for (i = 0; i < d0; ++i) for (j = 0; j < n; ++j) memcpy(&p->x[(i * n + n - 1 - j) * d1], &q->x[(i * n + j) * d1], d1 * sizeof(float)); } else if (action == KAD_BACKWARD && kad_is_back(q)) { for (i = 0; i < d0; ++i) for (j = 0; j < n; ++j) kad_saxpy(d1, 1.0f, &p->g[(i * n + n - 1 - j) * d1], &q->g[(i * n + j) * d1]); } return 0; } /********** Cost functions **********/ int kad_op_mse(kad_node_t *p, int action) { kad_node_t *y1 = p->child[0]; /* test */ kad_node_t *y0 = p->child[1]; /* truth */ int i, n; n = kad_len(y0); if (action == KAD_SYNC_DIM) { if (n != kad_len(y1)) return -1; p->n_d = 0; } else if (action == KAD_FORWARD) { double cost = 0.0; for (i = 0; i < n; ++i) cost += (y1->x[i] - y0->x[i]) * (y1->x[i] - y0->x[i]); p->x[0] = (float)(cost / n); } else if (action == KAD_BACKWARD && kad_is_back(y1)) { float t = 2.0f * p->g[0] / n; for (i = 0; i < n; ++i) y1->g[i] += t * (y1->x[i] - y0->x[i]); } return 0; } int kad_op_ce_bin(kad_node_t *p, int action) { static const float tiny = 1e-9f; kad_node_t *y1 = p->child[0]; /* test */ kad_node_t *y0 = p->child[1]; /* truth */ int i, n; n = kad_len(y0); if (action == KAD_SYNC_DIM) { if (n != kad_len(y1)) return -1; p->n_d = 0; } else if (action == KAD_FORWARD) { double cost = 0.0; for (i = 0; i < n; ++i) { if (y0->x[i] > 0.0f) cost += y0->x[i] * log(y0->x[i] / (y1->x[i] > tiny? y1->x[i] : tiny)); if (1.0f - y0->x[i] > 0.0f) cost += (1.0f - y0->x[i]) * log((1.0f - y0->x[i]) / (1.0f - y1->x[i] > tiny? 1.0f - y1->x[i] : tiny)); } p->x[0] = (float)(cost / n); } else if (action == KAD_BACKWARD && kad_is_back(y1)) { float t = p->g[0] / n; for (i = 0; i < n; ++i) { if (y0->x[i] > 0.0f) y1->g[i] -= t * y0->x[i] / (y1->x[i] > tiny? y1->x[i] : tiny); if (1.0f - y0->x[i] > 0.0f) y1->g[i] += t * (1.0f - y0->x[i]) / (1.0f - y1->x[i] > tiny? 1.0f - y1->x[i] : tiny); } } return 0; } int kad_op_ce_bin_neg(kad_node_t *p, int action) { static const float tiny = 1e-9f; kad_node_t *y1 = p->child[0]; /* test */ kad_node_t *y0 = p->child[1]; /* truth */ int i, n; n = kad_len(y0); if (action == KAD_SYNC_DIM) { if (n != kad_len(y1)) return -1; p->n_d = 0; } else if (action == KAD_FORWARD) { double cost = 0.0; for (i = 0; i < n; ++i) { if (1.0f + y0->x[i] > 0.0f) cost += .5f * (1.0f + y0->x[i]) * log((1.0f + y0->x[i]) / (1.0f + y1->x[i] > tiny? 1.0f + y1->x[i] : tiny)); if (1.0f - y0->x[i] > 0.0f) cost += .5f * (1.0f - y0->x[i]) * log((1.0f - y0->x[i]) / (1.0f - y1->x[i] > tiny? 1.0f - y1->x[i] : tiny)); } p->x[0] = (float)(cost / n); } else if (action == KAD_BACKWARD && kad_is_back(y1)) { float t = p->g[0] / n; for (i = 0; i < n; ++i) { if (1.0f + y0->x[i] > 0.0f) y1->g[i] -= .5f * t * (1.0f + y0->x[i]) / (1.0f + y1->x[i] > tiny? 1.0f + y1->x[i] : tiny); if (1.0f - y0->x[i] > 0.0f) y1->g[i] += .5f * t * (1.0f - y0->x[i]) / (1.0f - y1->x[i] > tiny? 1.0f - y1->x[i] : tiny); } } return 0; } int kad_op_ce_multi(kad_node_t *p, int action) { static const float tiny = 1e-9f; kad_node_t *y1 = p->child[0]; /* test */ kad_node_t *y0 = p->child[1]; /* truth */ kad_node_t *c = 0; int i, j, n1, d0; n1 = y0->d[y0->n_d - 1]; d0 = kad_len(y0) / n1; if (p->n_child == 3) { c = p->child[2]; assert(c->n_d == 1 && c->d[0] == n1); } if (action == KAD_SYNC_DIM) { if (kad_len(y0) != kad_len(y1) || y0->d[y0->n_d - 1] != y1->d[y1->n_d - 1]) return -1; p->n_d = 0; } else if (action == KAD_FORWARD) { double cost = 0.0; if (c == 0) { for (j = 0; j < d0; ++j) { float *x1 = &y1->x[j * n1], *x0 = &y0->x[j * n1]; for (i = 0; i < n1; ++i) if (x0[i] > 0.0f) cost += x0[i] * log(x0[i] / (x1[i] > tiny? x1[i] : tiny)); } } else { for (j = 0; j < d0; ++j) { float *x1 = &y1->x[j * n1], *x0 = &y0->x[j * n1]; for (i = 0; i < n1; ++i) if (x0[i] > 0.0f) cost += c->x[i] * x0[i] * log(x0[i] / (x1[i] > tiny? x1[i] : tiny)); } } p->x[0] = (float)(cost / d0); } else if (action == KAD_BACKWARD && kad_is_back(y1)) { float t = p->g[0] / d0; if (c == 0) { for (j = 0; j < d0; ++j) { float *g = &y1->g[j * n1], *x1 = &y1->x[j * n1], *x0 = &y0->x[j * n1]; for (i = 0; i < n1; ++i) g[i] -= t * x0[i] / (x1[i] > tiny? x1[i] : tiny); } } else { for (j = 0; j < d0; ++j) { float *g = &y1->g[j * n1], *x1 = &y1->x[j * n1], *x0 = &y0->x[j * n1]; for (i = 0; i < n1; ++i) g[i] -= t * c->x[i] * x0[i] / (x1[i] > tiny? x1[i] : tiny); } } } return 0; } /********** Normalization **********/ int kad_op_stdnorm(kad_node_t *p, int action) { int i, j, n, m; kad_node_t *q = p->child[0]; assert(q->n_d > 0); n = q->d[q->n_d - 1]; m = kad_len(q) / n; if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_ALLOC) { p->gtmp = realloc(p->gtmp, m * sizeof(float)); } else if (action == KAD_FORWARD) { float *si = (float*)p->gtmp; for (j = 0; j < m; ++j) { float *px = &p->x[j * n], *qx = &q->x[j * n]; float avg, std_inv; double s; for (i = 0, s = 0.0; i < n; ++i) s += qx[i]; avg = (float)(s / n); for (i = 0; i < n; ++i) px[i] = qx[i] - avg; for (i = 0, s = 0.0; i < n; ++i) s += px[i] * px[i]; std_inv = s == 0.0? 1.0f : (float)(1.0 / sqrt(s / n)); for (i = 0; i < n; ++i) px[i] *= std_inv; si[j] = std_inv; } } else if (action == KAD_BACKWARD && kad_is_back(q)) { float *si = (float*)p->gtmp; for (j = 0; j < m; ++j) { float *pg = &p->g[j * n], *qg = &q->g[j * n], *px = &p->x[j * n], std_inv = si[j]; double s, t; for (i = 0, s = t = 0.0; i < n; ++i) s += pg[i], t += px[i] * pg[i]; s /= n, t /= n; for (i = 0; i < n; ++i) qg[i] += std_inv * (pg[i] - s - px[i] * t); } } return 0; } /********** Activation functions **********/ int kad_op_sigm(kad_node_t *p, int action) { int i, n; kad_node_t *q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { for (i = 0; i < n; ++i) p->x[i] = 1.0f / (1.0f + expf(-q->x[i])); } else if (action == KAD_BACKWARD && kad_is_back(q)) { for (i = 0; i < n; ++i) q->g[i] += p->g[i] * (p->x[i] * (1.0f - p->x[i])); } return 0; } int kad_op_tanh(kad_node_t *p, int action) { int i, n; kad_node_t *q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { for (i = 0; i < n; ++i) { if (q->x[i] < -20.0f) p->x[i] = -1.0f; else { float y; y = expf(-2.0f * q->x[i]); p->x[i] = (1.0f - y) / (1.0f + y); } } } else if (action == KAD_BACKWARD && kad_is_back(q)) { for (i = 0; i < n; ++i) q->g[i] += p->g[i] * (1.0f - p->x[i] * p->x[i]); } return 0; } int kad_op_relu(kad_node_t *p, int action) { int i, n; kad_node_t *q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { for (i = 0; i < n; ++i) p->x[i] = q->x[i] > 0.0f? q->x[i] : 0.0f; } else if (action == KAD_BACKWARD && kad_is_back(q)) { for (i = 0; i < n; ++i) if (q->x[i] > 0.0f) q->g[i] += p->g[i]; } return 0; } int kad_op_sin(kad_node_t *p, int action) { int i, n; kad_node_t *q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { for (i = 0; i < n; ++i) p->x[i] = sinf(q->x[i]); } else if (action == KAD_BACKWARD && kad_is_back(q)) { for (i = 0; i < n; ++i) q->g[i] += p->g[i] * cosf(q->x[i]); } return 0; } int kad_op_softmax(kad_node_t *p, int action) { int i, j, n1, d0; kad_node_t *q = p->child[0]; n1 = q->d[q->n_d - 1]; d0 = kad_len(q) / n1; if (action == KAD_SYNC_DIM) { kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { for (j = 0; j < d0; ++j) { float s, max, *x = &q->x[j * n1], *y = &p->x[j * n1]; for (i = 0, max = -FLT_MAX; i < n1; ++i) max = max > x[i]? max : x[i]; for (i = 0, s = 0.0f; i < n1; ++i) { y[i] = expf(x[i] - max); s += y[i]; } for (i = 0, s = 1.0f / s; i < n1; ++i) y[i] *= s; } } else if (action == KAD_BACKWARD && kad_is_back(q)) { for (j = 0; j < d0; ++j) { float s, *g = &p->g[j * n1], *y = &p->x[j * n1], *h = &q->g[j * n1]; for (i = 0, s = 0.0f; i < n1; ++i) s += g[i] * y[i]; for (i = 0; i < n1; ++i) h[i] += y[i] * (g[i] - s); } } return 0; } /********** Multi-node pooling **********/ int kad_op_avg(kad_node_t *p, int action) { int i, n; float tmp; kad_node_t *q; assert(p->n_child > 0); tmp = 1.0f / p->n_child; q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { for (i = 1; i < p->n_child; ++i) if (kad_len(p->child[i]) != n) return -1; kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { memcpy(p->x, q->x, n * sizeof(float)); for (i = 1; i < p->n_child; ++i) kad_saxpy(n, 1.0f, p->child[i]->x, p->x); for (i = 0; i < n; ++i) p->x[i] *= tmp; } else if (action == KAD_BACKWARD) { for (i = 0; i < p->n_child; ++i) if (kad_is_back(p->child[i])) kad_saxpy(n, tmp, p->g, p->child[i]->g); } return 0; } int kad_op_max(kad_node_t *p, int action) { int i, n; kad_node_t *q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { int *max_j; for (i = 1; i < p->n_child; ++i) if (kad_len(p->child[i]) != n) return -1; kad_copy_dim1(p, q); max_j = (int*)calloc(n, sizeof(int)); p->gtmp = max_j; } else if (action == KAD_FORWARD) { int j, *max_j = (int*)p->gtmp; memset(max_j, 0, n * sizeof(int)); memcpy(p->x, q->x, n * sizeof(float)); for (j = 1; j < p->n_child; ++j) for (i = 0, q = p->child[j]; i < n; ++i) if (q->x[i] > p->x[i]) p->x[i] = q->x[i], max_j[i] = j; } else if (action == KAD_BACKWARD) { int *max_j = (int*)p->gtmp; for (i = 0; i < n; ++i) p->child[max_j[i]]->g[i] += p->g[i]; } return 0; } int kad_op_stack(kad_node_t *p, int action) /* TODO: allow axis, as in TensorFlow */ { int i, n, axis = 0; kad_node_t *q; assert(p->n_child > 0); q = p->child[0]; n = kad_len(q); if (action == KAD_SYNC_DIM) { for (i = 1; i < p->n_child; ++i) if (kad_len(p->child[i]) != n) return -1; p->n_d = q->n_d + 1; for (i = 0; i < axis; ++i) p->d[i] = q->d[i]; p->d[axis] = p->n_child; for (; i < q->n_d; ++i) p->d[i+1] = q->d[i]; } else if (action == KAD_FORWARD) { /* TODO: doesn't work when axis != 0 */ for (i = 0; i < p->n_child; ++i) memcpy(&p->x[i * n], p->child[i]->x, n * sizeof(float)); } else if (action == KAD_BACKWARD) { for (i = 0; i < p->n_child; ++i) if (kad_is_back(p->child[i])) kad_saxpy(n, 1.0f, &p->g[i * n], p->child[i]->g); } return 0; } int kad_op_select(kad_node_t *p, int action) { kad_node_t *q; int i, n, which; which = *(int32_t*)p->ptr; if (which < 0) which += p->n_child; assert(which >= 0 && which < p->n_child); q = p->child[which]; n = kad_len(q); if (action == KAD_SYNC_DIM) { for (i = 0; i < p->n_child; ++i) if (p->child[i]->n_d != q->n_d || kad_len(p->child[i]) != n) break; if (i < p->n_child) return -1; kad_copy_dim1(p, q); } else if (action == KAD_FORWARD) { memcpy(p->x, q->x, n * sizeof(float)); } else if (action == KAD_BACKWARD && kad_is_back(q)) { kad_saxpy(n, 1.0f, p->g, q->g); } return 0; } /********** 2D convolution **********/ static void conv_rot180(int d0, int d1, float *x) /* rotate/reverse a weight martix */ { int i, j; for (i = 0; i < d0; ++i) { float tmp, *xi = &x[i * d1]; for (j = 0; j < d1>>1; ++j) tmp = xi[j], xi[j] = xi[d1-1-j], xi[d1-1-j] = tmp; } } static void conv2d_move_1to3(int d[4], const float *x, float *y) /* convert the NCHW shape to the NHWC shape */ { int i, j, k, l; for (i = 0; i < d[0]; ++i) for (j = 0; j < d[1]; ++j) for (k = 0; k < d[2]; ++k) { int ik = (i * d[2] + k) * d[3], ijk = ((i * d[1] + j) * d[2] + k) * d[3]; for (l = 0; l < d[3]; ++l) y[(ik + l) * d[1] + j] = x[ijk + l]; } } static void conv2d_add_3to1(int d[4], const float *y, float *x) /* convert the NHWC shape back to NCHW and add to another NCHW-shaped array */ { int i, j, k, l; for (i = 0; i < d[0]; ++i) for (j = 0; j < d[1]; ++j) for (k = 0; k < d[2]; ++k) { int ik = (i * d[2] + k) * d[3], ijk = ((i * d[1] + j) * d[2] + k) * d[3]; for (l = 0; l < d[3]; ++l) x[ijk + l] += y[(ik + l) * d[1] + j]; } } #define conv_out_size(in_size, aux) (((in_size) - (aux)->kernel_size + (aux)->pad[0] + (aux)->pad[1]) / (aux)->stride + 1) #define process_row_for(_xx, _ww, _yy, _wn, _pn, _stride, _pad, _t) do { \ int j, l; \ if (_stride > 1) { \ for (l = 0; l < _wn; ++l) { \ const float *xl = &_xx[l - _pad]; \ for (j = 0; j < _pn; ++j, xl += _stride) _t[j] = *xl; \ kad_saxpy(_pn, _ww[l], _t, _yy); \ } \ } else for (l = 0; l < _wn; ++l) kad_saxpy(_pn, _ww[l], &_xx[l - _pad], _yy); \ } while (0) #define process_row_back_x(_xx, _ww, _yy, _wn, _pn, _stride, _pad, _t) do { \ int j, l; \ if (_stride > 1) { \ for (l = 0; l < _wn; ++l) { \ float *xl = &_xx[l - _pad]; \ memset(_t, 0, _pn * sizeof(float)); \ kad_saxpy(_pn, _ww[l], _yy, _t); \ for (j = 0; j < _pn; ++j, xl += _stride) *xl += _t[j]; \ } \ } else for (l = 0; l < _wn; ++l) kad_saxpy(_pn, _ww[l], _yy, &_xx[l - _pad]); \ } while (0) #define process_row_back_w(_xx, _ww, _yy, _wn, _pn, _stride, _pad, _t) do { \ int j, l; \ if (_stride > 1) { \ for (l = 0; l < _wn; ++l) { \ const float *xl = &_xx[l - _pad]; \ for (j = 0; j < _pn; ++j, xl += _stride) _t[j] = *xl; \ _ww[l] += kad_sdot(_pn, _yy, _t); \ } \ } else for (l = 0; l < _wn; ++l) _ww[l] += kad_sdot(_pn, _yy, &_xx[l - _pad]); \ } while (0) /* Forward and backward passes are implemented with two different algorithms. * The first is faster for small kernels with few input channels; otherwise the * second algorithm is faster. Both algorithms should produce identical * results, up to the precision of "float". */ int kad_op_conv2d(kad_node_t *p, int action) /* in the number-channel-height-width (NCHW) shape */ { #define conv2d_loop1(_x, _w, _y, _tmp, _row_func) do { /* for the NCHW shape */ \ int n, c1, c0, i, k, ii; \ for (n = 0; n < q->d[0]; ++n) /* mini-batch */ \ for (c1 = 0; c1 < w->d[0]; ++c1) /* output channel */ \ for (c0 = 0; c0 < w->d[1]; ++c0) /* input channel */ \ for (k = 0; k < w->d[2]; ++k) { /* kernel row */ \ float *_ww = &(_w)[((c1 * w->d[1] + c0) * w->d[2] + k) * w->d[3]]; \ for (i = 0, ii = k - aux[0].pad[0]; i < p->d[2] && ii >= 0 && ii < q->d[2]; ++i, ii += aux[0].stride) { /* output row */ \ float *_xx = &(_x)[((n * q->d[1] + c0) * q->d[2] + ii) * q->d[3]]; \ float *_yy = &(_y)[((n * p->d[1] + c1) * p->d[2] + i) * p->d[3]]; \ if (x_padded) { \ memcpy(x_padded + aux[1].pad[0], _xx, q->d[3] * sizeof(float)); \ _xx = x_padded + aux[1].pad[0]; \ } \ _row_func(_xx, _ww, _yy, w->d[3], p->d[3], aux[1].stride, aux[1].pad[0], (_tmp)); \ } /* ~i */ \ } /* ~k, c0, c1, n */ \ } while (0) #define conv2d_loop2(_x, _w, _y, _code) do { /* for the NHWC shape */ \ int n, c1, i, j, k, ii, j_skip = aux[1].stride * q->d[1], m = w->d[3] * w->d[1]; \ for (n = 0; n < q->d[0]; ++n) /* mini-batch */ \ for (c1 = 0; c1 < w->d[0]; ++c1) /* output channel */ \ for (k = 0; k < w->d[2]; ++k) { /* kernel row */ \ float *_ww = &(_w)[(c1 * w->d[2] + k) * m]; \ for (i = 0, ii = k - aux[0].pad[0]; i < p->d[2] && ii >= 0 && ii < q->d[2]; ++i, ii += aux[0].stride) { /* output and input row */ \ float *_xx = &(_x)[(n * q->d[2] + ii) * q->d[3] * q->d[1]]; \ float *_yy = &(_y)[((n * p->d[1] + c1) * p->d[2] + i) * p->d[3]]; \ if (x_padded) { \ memcpy(x_padded + aux[1].pad[0] * q->d[1], _xx, q->d[3] * q->d[1] * sizeof(float)); \ _xx = x_padded; \ } \ for (j = 0; j < p->d[3]; ++j, _xx += j_skip, ++_yy) _code; /* output and input column */ \ } /* ~i */ \ } /* ~k, c1, n */ \ } while (0) conv_conf_t *aux = (conv_conf_t*)p->ptr; kad_node_t *q = p->child[0], *w = p->child[1]; float *t = 0, *q1 = 0, *w1 = 0, *x_padded = 0; int algo_switch = 0; if (action == KAD_FORWARD || action == KAD_BACKWARD) { /* allocate working space */ if (w->d[3] * w->d[1] < 16) { t = (float*)malloc(p->d[3] * sizeof(float)); x_padded = aux[1].pad[0] + aux[1].pad[1] > 0? (float*)calloc(q->d[3] + aux[1].pad[0] + aux[1].pad[1], sizeof(float)) : 0; } else { q1 = (float*)malloc(kad_len(q) * sizeof(float)); w1 = (float*)malloc(kad_len(w) * sizeof(float)); x_padded = aux[1].pad[0] + aux[1].pad[1] > 0? (float*)calloc((q->d[3] + aux[1].pad[0] + aux[1].pad[1]) * q->d[1], sizeof(float)) : 0; algo_switch = 1; } } if (action == KAD_SYNC_DIM) { if (q->n_d != 4 || w->n_d != 4) return -1; if (q->d[1] != w->d[1]) return -1; /* unmatched input channels */ p->n_d = 4; p->d[0] = q->d[0], p->d[1] = w->d[0], p->d[2] = conv_out_size(q->d[2], &aux[0]), p->d[3] = conv_out_size(q->d[3], &aux[1]); } else if (action == KAD_FORWARD) { conv_rot180(w->d[0] * w->d[1], w->d[2] * w->d[3], w->x); memset(p->x, 0, kad_len(p) * sizeof(float)); if (!algo_switch) { /* this is the first algorithm */ conv2d_loop1(q->x, w->x, p->x, t, process_row_for); } else { /* this is the second algorithm */ conv2d_move_1to3(q->d, q->x, q1); conv2d_move_1to3(w->d, w->x, w1); conv2d_loop2(q1, w1, p->x, (*_yy += kad_sdot(m, _ww, _xx))); } conv_rot180(w->d[0] * w->d[1], w->d[2] * w->d[3], w->x); } else if (action == KAD_BACKWARD) { if (kad_is_back(p->child[0])) { /* backprop to the input array */ conv_rot180(w->d[0] * w->d[1], w->d[2] * w->d[3], w->x); if (!algo_switch) { conv2d_loop1(q->g, w->x, p->g, t, process_row_back_x); } else { memset(q1, 0, kad_len(q) * sizeof(float)); conv2d_move_1to3(w->d, w->x, w1); conv2d_loop2(q1, w1, p->g, kad_saxpy(m, *_yy, _ww, _xx)); conv2d_add_3to1(q->d, q1, q->g); } conv_rot180(w->d[0] * w->d[1], w->d[2] * w->d[3], w->x); } if (kad_is_back(p->child[1])) { /* backprop to the weight matrix */ conv_rot180(w->d[0] * w->d[1], w->d[2] * w->d[3], w->g); if (!algo_switch) { conv2d_loop1(q->x, w->g, p->g, t, process_row_back_w); } else { conv2d_move_1to3(q->d, q->x, q1); memset(w1, 0, kad_len(w) * sizeof(float)); conv2d_loop2(q1, w1, p->g, kad_saxpy(m, *_yy, _xx, _ww)); conv2d_add_3to1(w->d, w1, w->g); } conv_rot180(w->d[0] * w->d[1], w->d[2] * w->d[3], w->g); } } free(t); free(q1); free(w1); free(x_padded); return 0; } int kad_op_max2d(kad_node_t *p, int action) { conv_conf_t *aux = (conv_conf_t*)p->ptr; kad_node_t *q = p->child[0]; if (action == KAD_SYNC_DIM) { if (q->n_d != 4) return -1; p->n_d = 4; p->d[0] = q->d[0], p->d[1] = q->d[1], p->d[2] = conv_out_size(q->d[2], &aux[0]), p->d[3] = conv_out_size(q->d[3], &aux[1]); } else if (action == KAD_ALLOC) { p->gtmp = realloc(p->gtmp, kad_len(p) * sizeof(int)); } else if (action == KAD_FORWARD) { int rest = 1, len, t, i; int *f = (int*)p->gtmp; len = kad_len(p); for (i = 0; i < len; ++i) p->x[i] = -FLT_MAX; for (i = 0; i < p->n_d - 2; ++i) rest *= p->d[i]; for (t = 0; t < rest; ++t) { int i, j, k, l, p_row = p->d[p->n_d - 2], p_col = p->d[p->n_d - 1]; for (i = 0; i < p_row; ++i) { int u = (t * p_row + i) * p_col; for (k = 0; k < aux[0].kernel_size; ++k) { int v, v0, v_end, ii = i * aux[0].stride + k - aux[0].pad[0]; if (ii < 0 || ii >= q->d[p->n_d - 2]) continue; v0 = (t * q->d[p->n_d - 2] + ii) * q->d[p->n_d - 1]; v_end = v0 + q->d[p->n_d - 1]; for (l = 0; l < aux[1].kernel_size; ++l) for (j = 0, v = v0 + (l > aux[1].pad[0]? l - aux[1].pad[0] : 0); j < p_col && v < v_end; ++j, v += aux[1].stride) if (p->x[u + j] < q->x[v]) p->x[u + j] = q->x[v], f[u + j] = v; } /* ~k */ } /* ~i */ } } else if (action == KAD_BACKWARD) { int i, len, *f = (int*)p->gtmp; len = kad_len(p); for (i = 0; i < len; ++i) q->g[f[i]] += p->g[i]; } return 0; } /********** 1D convolution **********/ static void conv1d_move_1to2(int d[3], const float *x, float *y) { int i, j, k; for (k = 0; k < d[0]; ++k) for (j = 0; j < d[1]; ++j) for (i = 0; i < d[2]; ++i) y[(k * d[2] + i) * d[1] + j] = x[(k * d[1] + j) * d[2] + i]; } static void conv1d_add_2to1(int d[3], const float *y, float *x) { int i, j, k; for (k = 0; k < d[0]; ++k) for (j = 0; j < d[1]; ++j) for (i = 0; i < d[2]; ++i) x[(k * d[1] + j) * d[2] + i] += y[(k * d[2] + i) * d[1] + j]; } int kad_op_conv1d(kad_node_t *p, int action) /* in the number-channel-width (NCW) shape */ { #define conv1d_loop1(_x, _w, _y, _tmp, _row_func) do { /* for the NCW shape */ \ int n, c1, c0; \ for (n = 0; n < q->d[0]; ++n) /* mini-batch */ \ for (c1 = 0; c1 < w->d[0]; ++c1) /* output channel */ \ for (c0 = 0; c0 < w->d[1]; ++c0) { /* input channel */ \ float *_ww = &(_w)[(c1 * w->d[1] + c0) * w->d[2]]; \ float *_xx = &(_x)[(n * q->d[1] + c0) * q->d[2]]; \ float *_yy = &(_y)[(n * p->d[1] + c1) * p->d[2]]; \ if (x_padded) { \ memcpy(x_padded + aux->pad[0], _xx, q->d[2] * sizeof(float)); \ _xx = x_padded + aux->pad[0]; \ } \ _row_func(_xx, _ww, _yy, w->d[2], p->d[2], aux->stride, aux->pad[0], (_tmp)); \ } /* ~c0, c1, n */ \ } while (0) #define conv1d_loop2(_x, _w, _y, _code) do { /* for the NWC shape */ \ int n, c1, j, j_skip = aux->stride * q->d[1], m = w->d[2] * w->d[1]; \ for (n = 0; n < q->d[0]; ++n) /* mini-batch */ \ for (c1 = 0; c1 < w->d[0]; ++c1) { /* output channel */ \ float *_ww = &(_w)[c1 * m]; \ float *_xx = &(_x)[n * q->d[1] * q->d[2]]; \ float *_yy = &(_y)[(n * p->d[1] + c1) * p->d[2]]; \ if (x_padded) { \ memcpy(x_padded + aux->pad[0] * q->d[1], _xx, q->d[2] * q->d[1] * sizeof(float)); \ _xx = x_padded; \ } \ for (j = 0; j < p->d[2]; ++j, _xx += j_skip, ++_yy) _code; \ } /* ~c1, n */ \ } while (0) conv_conf_t *aux = (conv_conf_t*)p->ptr; kad_node_t *q = p->child[0], *w = p->child[1]; float *t = 0, *q1 = 0, *w1 = 0, *x_padded = 0; int algo_switch = 0; if (action == KAD_FORWARD || action == KAD_BACKWARD) { /* allocate working space */ if (w->d[2] * w->d[1] < 32) { t = (float*)malloc(p->d[2] * sizeof(float)); x_padded = aux->pad[0] + aux->pad[1] > 0? (float*)calloc(q->d[2] + aux->pad[0] + aux->pad[1], sizeof(float)) : 0; } else { q1 = (float*)malloc(kad_len(q) * sizeof(float)); w1 = (float*)malloc(kad_len(w) * sizeof(float)); x_padded = aux->pad[0] + aux->pad[1] > 0? (float*)calloc((q->d[2] + aux->pad[0] + aux->pad[1]) * q->d[1], sizeof(float)) : 0; algo_switch = 1; } } if (action == KAD_SYNC_DIM) { if (q->n_d != 3 || w->n_d != 3) return -1; if (q->d[1] != w->d[1]) return -1; /* unmatched input channels */ p->n_d = 3; p->d[0] = q->d[0], p->d[1] = w->d[0], p->d[2] = conv_out_size(q->d[2], aux); } else if (action == KAD_FORWARD) { conv_rot180(w->d[0] * w->d[1], w->d[2], w->x); memset(p->x, 0, kad_len(p) * sizeof(float)); if (!algo_switch) { /* this is the first algorithm */ conv1d_loop1(q->x, w->x, p->x, t, process_row_for); } else { /* this is the second algorithm */ conv1d_move_1to2(q->d, q->x, q1); conv1d_move_1to2(w->d, w->x, w1); conv1d_loop2(q1, w1, p->x, (*_yy += kad_sdot(m, _ww, _xx))); } conv_rot180(w->d[0] * w->d[1], w->d[2], w->x); } else if (action == KAD_BACKWARD) { if (kad_is_back(p->child[0])) { /* backprop to the input array */ conv_rot180(w->d[0] * w->d[1], w->d[2], w->x); if (!algo_switch) { conv1d_loop1(q->g, w->x, p->g, t, process_row_back_x); } else { memset(q1, 0, kad_len(q) * sizeof(float)); conv1d_move_1to2(w->d, w->x, w1); conv1d_loop2(q1, w1, p->g, kad_saxpy(m, *_yy, _ww, _xx)); conv1d_add_2to1(q->d, q1, q->g); } conv_rot180(w->d[0] * w->d[1], w->d[2], w->x); } if (kad_is_back(p->child[1])) { /* backprop to the weight matrix */ conv_rot180(w->d[0] * w->d[1], w->d[2], w->g); if (!algo_switch) { conv1d_loop1(q->x, w->g, p->g, t, process_row_back_w); } else { conv1d_move_1to2(q->d, q->x, q1); memset(w1, 0, kad_len(w) * sizeof(float)); conv1d_loop2(q1, w1, p->g, kad_saxpy(m, *_yy, _xx, _ww)); conv1d_add_2to1(w->d, w1, w->g); } conv_rot180(w->d[0] * w->d[1], w->d[2], w->g); } } free(t); free(q1); free(w1); free(x_padded); return 0; } int kad_op_max1d(kad_node_t *p, int action) { conv_conf_t *aux = (conv_conf_t*)p->ptr; kad_node_t *q = p->child[0]; if (action == KAD_SYNC_DIM) { if (q->n_d != 3) return -1; p->n_d = 3; p->d[0] = q->d[0], p->d[1] = q->d[1], p->d[2] = conv_out_size(q->d[2], aux); } else if (action == KAD_ALLOC) { p->gtmp = realloc(p->gtmp, kad_len(p) * sizeof(int)); } else if (action == KAD_FORWARD) { int rest = 1, len, t, i; int *f = (int*)p->gtmp; len = kad_len(p); for (i = 0; i < len; ++i) p->x[i] = -FLT_MAX; for (i = 0; i < p->n_d - 1; ++i) rest *= p->d[i]; for (t = 0; t < rest; ++t) { int j, l, p_width = p->d[p->n_d - 1]; int u = t * p_width, v, v0 = t * q->d[p->n_d - 1], v_end = v0 + q->d[p->n_d - 1]; for (l = 0; l < aux->kernel_size; ++l) for (j = 0, v = v0 + (l > aux->pad[0]? l - aux->pad[0] : 0); j < p_width && v < v_end; ++j, v += aux->stride) if (p->x[u + j] < q->x[v]) p->x[u + j] = q->x[v], f[u + j] = v; } } else if (action == KAD_BACKWARD) { int i, len, *f = (int*)p->gtmp; len = kad_len(p); for (i = 0; i < len; ++i) q->g[f[i]] += p->g[i]; } return 0; } int kad_op_avg1d(kad_node_t *p, int action) { conv_conf_t *aux = (conv_conf_t*)p->ptr; kad_node_t *q = p->child[0]; if (action == KAD_SYNC_DIM) { if (q->n_d != 3) return -1; p->n_d = 3; p->d[0] = q->d[0], p->d[1] = q->d[1], p->d[2] = conv_out_size(q->d[2], aux); } else if (action == KAD_ALLOC) { p->gtmp = realloc(p->gtmp, kad_len(p) * sizeof(int)); } else if (action == KAD_FORWARD) { int rest = 1, len, t, i; int *f = (int*)p->gtmp; len = kad_len(p); for (i = 0; i < len; ++i) p->x[i] = 0.0f, f[i] = 0; for (i = 0; i < p->n_d - 1; ++i) rest *= p->d[i]; for (t = 0; t < rest; ++t) { int j, l, p_width = p->d[p->n_d - 1]; int u = t * p_width, v, v0 = t * q->d[p->n_d - 1], v_end = v0 + q->d[p->n_d - 1]; for (l = 0; l < aux->kernel_size; ++l) for (j = 0, v = v0 + (l > aux->pad[0]? l - aux->pad[0] : 0); j < p_width && v < v_end; ++j, v += aux->stride) p->x[u + j] += q->x[v], ++f[u + j]; } for (i = 0; i < len; ++i) p->x[i] /= f[i]; } else if (action == KAD_BACKWARD) { int rest = 1, t, i; int *f = (int*)p->gtmp; for (i = 0; i < p->n_d - 1; ++i) rest *= p->d[i]; for (t = 0; t < rest; ++t) { int j, l, p_width = p->d[p->n_d - 1]; int u = t * p_width, v, v0 = t * q->d[p->n_d - 1], v_end = v0 + q->d[p->n_d - 1]; for (l = 0; l < aux->kernel_size; ++l) for (j = 0, v = v0 + (l > aux->pad[0]? l - aux->pad[0] : 0); j < p_width && v < v_end; ++j, v += aux->stride) q->g[v] += p->g[u + j] / f[u + j]; } } return 0; } /********** List of operators **********/ kad_op_f kad_op_list[KAD_MAX_OP] = { 0, kad_op_add, /* 1: element-wise addition */ kad_op_mul, /* 2: element-wise multiplication */ kad_op_cmul, /* 3: column multiplication */ kad_op_ce_bin_neg, /* 4: binary cross-entropy for (-1,1) */ kad_op_square, /* 5: square */ kad_op_sigm, /* 6: sigmoid */ kad_op_tanh, /* 7: tanh */ kad_op_relu, /* 8: ReLU */ kad_op_matmul, /* 9: matrix multiplication */ kad_op_avg, /* 10: general average pooling (not for ConvNet) */ kad_op_1minus, /* 11: 1-x */ kad_op_select, /* 12: choose between one of the children */ kad_op_ce_multi, /* 13: multi-class cross-entropy */ kad_op_softmax, /* 14: softmax */ kad_op_dropout, /* 15: dropout */ kad_op_conv2d, /* 16: 2D convolution */ kad_op_max2d, /* 17: 2D max pooling (for 2D ConvNet) */ kad_op_conv1d, /* 18: 1D convolution */ kad_op_max1d, /* 19: 1D max pooling (for 1D ConvNet) */ kad_op_slice, /* 20: slice data at a dimension */ kad_op_max, /* 21: general max pooling */ kad_op_ce_bin, /* 22: binary cross-entropy for (0,1) */ kad_op_sub, /* 23: element-wise subtraction */ kad_op_sample_normal, /* 24: sample from a normal distribution */ kad_op_reduce_sum, /* 25 */ kad_op_reduce_mean, /* 26 */ kad_op_log, /* 27: log() */ kad_op_avg1d, /* 28: 1D average pooling (for 1D ConvNet) */ kad_op_mse, /* 29: mean square error */ kad_op_reshape, /* 30 */ kad_op_concat, /* 31 */ kad_op_stdnorm, /* 32: layer normalization */ kad_op_exp, /* 33: exp() */ kad_op_sin, /* 34: sin() */ kad_op_stack, /* 35: tf.stack, but on the first axis only */ kad_op_reverse /* 36: tf.reverse, but on one axis only */ }; char *kad_op_name[KAD_MAX_OP] = { 0, "add", "mul", "cmul", "ce_bin_neg", "square", "sigm", "tanh", "relu", "matmul", "avg", "1minus", "select", "ce_multi", "softmax", "dropout", "conv2d", "max2d", "conv1d", "max1d", "slice", "max", "ce_bin", "sub", "sample_normal", "reduce_sum", "reduce_mean", "log", "avg1d", "mse", "reshape", "concat", "stdnorm", "exp", "sin", "stack", "reverse" }; /************************** *** Debugging routines *** **************************/ void kad_trap_fe(void) { #ifdef __SSE__ _MM_SET_EXCEPTION_MASK(_MM_GET_EXCEPTION_MASK() & ~(_MM_MASK_INVALID | _MM_MASK_DIV_ZERO)); #endif } void kad_print_graph(FILE *fp, int n, kad_node_t **v) { int i, j; for (i = 0; i < n; ++i) v[i]->tmp = i; for (i = 0; i < n; ++i) { kad_node_t *p = v[i]; fprintf(fp, "%d\t%x:%x\t%d\t", i, p->flag, p->ext_flag, p->ext_label); if (p->pre) fprintf(fp, "%d\t", p->pre->tmp); else fprintf(fp, ".\t"); fputs("[", fp); for (j = 0; j < p->n_d; ++j) { if (j) fputc(',', fp); fprintf(fp, "%d", p->d[j]); } fprintf(fp, "]\t"); if (p->n_child) { fprintf(fp, "%s(", kad_op_name[p->op]); for (j = 0; j < p->n_child; ++j) { if (j) fputc(',', fp); fprintf(fp, "$%d", p->child[j]->tmp); } fprintf(fp, ")"); } else fprintf(fp, "%s", kad_is_feed(p)? "feed" : kad_is_var(p)? "var" : kad_is_const(p)? "const" : "N/A"); fputc('\n', fp); } for (i = 0; i < n; ++i) v[i]->tmp = 0; } static void kad_add_delta(int n, kad_node_t **a, float c, float *delta) { int i, k; for (i = k = 0; i < n; ++i) if (kad_is_var(a[i])) { kad_saxpy(kad_len(a[i]), c, &delta[k], a[i]->x); k += kad_len(a[i]); } } void kad_check_grad(int n, kad_node_t **a, int from) { const float eps = 1e-5f, rel = 1e-7f / eps; int i, k, n_var; float *g0, *delta, f0, f_minus, f_plus, s0, s1, rel_err, p_m_err; n_var = kad_size_var(n, a); g0 = (float*)calloc(n_var, sizeof(float)); f0 = *kad_eval_at(n, a, from); kad_grad(n, a, from); for (i = k = 0; i < n; ++i) if (kad_is_var(a[i])) { memcpy(&g0[k], a[i]->g, kad_len(a[i]) * sizeof(float)); k += kad_len(a[i]); } delta = (float*)calloc(n_var, sizeof(float)); for (k = 0; k < n_var; ++k) delta[k] = (float)kad_drand(0) * eps; kad_add_delta(n, a, 1.0f, delta); f_plus = *kad_eval_at(n, a, from); kad_add_delta(n, a, -2.0f, delta); f_minus = *kad_eval_at(n, a, from); kad_add_delta(n, a, 1.0f, delta); s0 = kad_sdot(n_var, g0, delta); s1 = .5f * (f_plus - f_minus); fprintf(stderr, "Gradient check -- %g <=> %g @ %g -- ", s0/eps, s1/eps, f0); if (fabs(s1) >= rel * eps) { rel_err = fabsf(fabsf(s0) - fabsf(s1)) / (fabsf(s0) + fabsf(s1)); p_m_err = fabsf(f_plus + f_minus - 2.0f * f0) / fabsf(f_plus - f_minus); fprintf(stderr, "rel_err:%g p_m_err:%g -- ", rel_err, p_m_err); if (rel_err >= rel && rel_err > p_m_err) fprintf(stderr, "failed\n"); else fprintf(stderr, "passed\n"); } else fprintf(stderr, "skipped\n"); free(delta); free(g0); }