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Precompute compressed lenghts of the training data #2

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Precompute compressed lenghts of the training data #2

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43 changes: 40 additions & 3 deletions src/knn.c
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Original file line number Diff line number Diff line change
Expand Up @@ -34,6 +34,7 @@ Nob_String_View deflate_sv(Arena *arena, Nob_String_View sv)
typedef struct {
size_t klass;
Nob_String_View text;
float c;
} Sample;

typedef struct {
Expand Down Expand Up @@ -74,10 +75,9 @@ typedef struct {
size_t capacity;
} NCDs;

float ncd(Arena *arena, Nob_String_View a, Nob_String_View b, float cb)
float ncd(Arena *arena, Nob_String_View a, float ca, Nob_String_View b, float cb)
{
Nob_String_View ab = nob_sv_from_cstr(arena_sprintf(arena, SV_Fmt" "SV_Fmt, SV_Arg(a), SV_Arg(b)));
float ca = deflate_sv(arena, a).count;
float cab = deflate_sv(arena, ab).count;
float mn = ca; if (mn > cb) mn = cb;
float mx = ca; if (mx < cb) mx = cb;
Expand All @@ -102,13 +102,28 @@ typedef struct {
Arena arena;
} Klassify_State;

void *precompute_train_c_thread(void *params)
{
Klassify_State *state = params;

float ca;
for (size_t i = 0; i < state->train_count; ++i) {
ca = deflate_sv(&state->arena, state->train[i].text).count;
state->train[i].c = ca;
}

return NULL;
}


void *klassify_thread(void *params)
{
Klassify_State *state = params;

float cb = deflate_sv(&state->arena, state->text).count;
for (size_t i = 0; i < state->train_count; ++i) {
float distance = ncd(&state->arena, state->train[i].text, state->text, cb);
float distance = ncd(&state->arena, state->train[i].text, state->train[i].c,
state->text, cb);
arena_reset(&state->arena);
nob_da_append(&state->ncds, ((NCD) {
.distance = distance,
Expand Down Expand Up @@ -147,6 +162,22 @@ void klass_predictor_init(Klass_Predictor *kp, Samples train_samples)
memset(kp->states, 0, kp->nprocs*sizeof(Klassify_State));
}

void klass_predictor_precompute_train_c(Klass_Predictor *kp)
{
for (size_t i = 0; i < kp->nprocs; ++i) {
kp->states[i].train = kp->train_samples.items + i*kp->chunk_size;
kp->states[i].train_count = kp->chunk_size;
if (i == kp->nprocs - 1) kp->states[i].train_count += kp->chunk_rem;
arena_reset(&kp->states[i].arena);
if (pthread_create(&kp->threads[i], NULL, precompute_train_c_thread,
&kp->states[i]) != 0) {
nob_log(NOB_ERROR, "Could not create thread");
exit(1);
}
}
}


size_t klass_predictor_predict(Klass_Predictor *kp, Nob_String_View text, size_t k)
{
for (size_t i = 0; i < kp->nprocs; ++i) {
Expand Down Expand Up @@ -231,6 +262,12 @@ int main(int argc, char **argv)
Klass_Predictor kp = {0};
klass_predictor_init(&kp, train_samples);

nob_log(NOB_INFO, "Pre-computing training lengths");
double begin = clock_get_secs();
klass_predictor_precompute_train_c(&kp);
double end = clock_get_secs();
nob_log(NOB_INFO, "Elapsed Time: %.3lf secs", end - begin);

if (argc <= 0) {
interactive_mode(&kp);
} else {
Expand Down