536 lines
20 KiB
C
536 lines
20 KiB
C
/* SPDX-License-Identifier: AGPL-3.0-or-later */
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/* Copyright (C) 2026 David (Corey) Herrera */
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/*
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* test_contiguous_chunk.c — Contiguous Chunk Retrieval Experiments
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*
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* Follow-up to HybridMem Phase 7b (B=C=2/3).
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* Tests whether fragment count (seams between chunks from different contexts)
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* is the root cause of retrieval failure.
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*
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* Experiment 1: top_k sweep — fewer chunks = fewer seams = better?
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* Experiment 2: evict_fraction sweep — larger chunks = more coherence = better?
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* Experiment 3: best contiguous config vs Phase 7b baseline
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*
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* Usage:
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* ./examples/test_contiguous_chunk \
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* --model ../models/base/RWKV-X-3.6B-64k-Base.safetensors \
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* --vocab rwkvx/data/rwkv_vocab_v20230424.txt \
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* --filler ../docs/architecture/rwkv-x-deep-dive.md \
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* --max-filler 8000 --max-tokens 48 --cache-size 8 --quantize
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*/
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#include "rwkvx/rwkvx.h"
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#include "tensor/tensor.h"
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#include <ctype.h>
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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#include <time.h>
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typedef struct {
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const char *fact;
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const char *question;
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const char *key_detail;
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} fact_entry;
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static const fact_entry FACTS[] = {
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{
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"The secret project codename is AURORA-7 and the lead researcher is Dr. Kimura.",
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"What is the secret project codename and who leads it?",
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"AURORA"
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},
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{
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"The server room temperature must be maintained at exactly 18.5 degrees Celsius.",
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"What temperature must the server room be maintained at?",
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"18.5"
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},
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{
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"Employee badge number 4472 belongs to Sarah Chen from the quantum computing division.",
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"What is Sarah Chen's badge number?",
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"4472"
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}
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};
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#define N_FACTS 3
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static char* read_file(const char *path) {
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FILE *fp = fopen(path, "r");
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if (!fp) return NULL;
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fseek(fp, 0, SEEK_END);
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long len = ftell(fp);
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fseek(fp, 0, SEEK_SET);
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char *buf = (char*)malloc(len + 1);
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size_t nread = fread(buf, 1, len, fp);
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buf[nread] = '\0';
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fclose(fp);
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return buf;
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}
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static void rmdir_recursive(const char *path) {
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char cmd[512];
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snprintf(cmd, sizeof(cmd), "rm -rf %s", path);
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system(cmd);
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}
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/* Case-insensitive substring search */
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static int contains_ci(const char *haystack, const char *needle) {
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if (!haystack || !needle) return 0;
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int hlen = (int)strlen(haystack);
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int nlen = (int)strlen(needle);
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for (int i = 0; i <= hlen - nlen; i++) {
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int match = 1;
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for (int j = 0; j < nlen; j++) {
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if (tolower((unsigned char)haystack[i + j]) !=
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tolower((unsigned char)needle[j])) {
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match = 0;
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break;
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}
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}
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if (match) return 1;
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}
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return 0;
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}
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/* Generate tokens greedily from a prefilled state. */
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static char* generate(rx_model *model, rx_tokenizer *tok, rx_state *state,
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tm_tensor *logits, int max_tokens, rx_config cfg) {
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rx_sampling_params params = rx_sampling_defaults();
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params.temperature = 0.0f;
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uint32_t *gen_tokens = (uint32_t*)calloc(max_tokens, sizeof(uint32_t));
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int n_gen = 0;
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tm_tensor *cur_logits = logits;
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for (int i = 0; i < max_tokens; i++) {
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if (!cur_logits) break;
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uint32_t token = rx_sample(cur_logits, ¶ms, NULL, cfg.vocab_size);
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if (i > 0) tm_free(cur_logits);
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if (token == 0) { cur_logits = NULL; break; }
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gen_tokens[n_gen++] = token;
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cur_logits = rx_forward(model, token, state);
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}
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if (cur_logits && cur_logits != logits) tm_free(cur_logits);
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char *text = rx_tokenizer_decode(tok, gen_tokens, n_gen);
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free(gen_tokens);
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return text;
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}
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/* Run a single test pass with given HybridMem config.
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* Returns 1 if key_detail found in output, 0 otherwise. */
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static int run_pass(rx_model *model, rx_tokenizer *tok, rx_config cfg,
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uint32_t *tokens, int n_tokens, int max_gen_tokens,
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rx_hybridmem_config *hm_cfg, const char *key_detail,
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const char *label) {
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rx_state *state = rx_state_new_with_hybridmem(model, hm_cfg);
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if (!state) {
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fprintf(stderr, " %s: failed to create state\n", label);
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return 0;
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}
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tm_tensor *logits = NULL;
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for (int i = 0; i < n_tokens; i++) {
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if (logits) tm_free(logits);
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logits = rx_forward(model, tokens[i], state);
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}
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char *out = generate(model, tok, state, logits, max_gen_tokens, cfg);
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tm_free(logits);
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rx_state_free(state);
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int hit = contains_ci(out, key_detail);
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fprintf(stderr, " %s: %s [%s]\n", label, out ? out : "(null)",
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hit ? "HIT" : "miss");
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free(out);
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return hit;
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}
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/* Build prompt: fact + filler + question */
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static char* build_prompt(const fact_entry *fe, const char *filler) {
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char question_full[512];
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snprintf(question_full, sizeof(question_full),
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"\n\nQuestion: %s\nAnswer:", fe->question);
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int pl = (int)(strlen(fe->fact) + 2 + strlen(filler) + strlen(question_full) + 1);
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char *prompt = (char*)malloc(pl);
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snprintf(prompt, pl, "%s\n\n%s%s", fe->fact, filler, question_full);
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return prompt;
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}
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/* ================================================================
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* Experiment 1: top_k sweep
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* ================================================================ */
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static void experiment_1(rx_model *model, rx_tokenizer *tok, rx_config cfg,
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const char *filler, int cache_size, int max_tokens) {
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int top_k_values[] = {0, 1, 2, 3, 5};
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int n_tk = 5;
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float evict_fraction = 0.5f;
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fprintf(stderr, "\n==========================================\n");
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fprintf(stderr, "EXPERIMENT 1: top_k Sweep (Fragment Count)\n");
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fprintf(stderr, "==========================================\n");
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fprintf(stderr, "cache_size=%d, evict_fraction=%.2f\n", cache_size, evict_fraction);
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fprintf(stderr, "top_k values: 0 (baseline), 1, 2, 3, 5\n\n");
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int hits[5][N_FACTS];
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memset(hits, 0, sizeof(hits));
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for (int f = 0; f < N_FACTS; f++) {
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const fact_entry *fe = &FACTS[f];
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fprintf(stderr, "--- Fact %d: \"%s\" ---\n", f + 1, fe->key_detail);
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char *prompt = build_prompt(fe, filler);
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uint32_t *tokens = (uint32_t*)malloc(32768 * sizeof(uint32_t));
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int n_tokens = rx_tokenizer_encode(tok, prompt, tokens, 32768);
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fprintf(stderr, " Prompt: %d tokens\n", n_tokens);
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for (int ti = 0; ti < n_tk; ti++) {
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int tk = top_k_values[ti];
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char label[64];
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char hm_dir[256];
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snprintf(hm_dir, sizeof(hm_dir), "/tmp/hm_contiguous_exp1_%d_%d", f, tk);
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rmdir_recursive(hm_dir);
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rx_hybridmem_config hm_cfg = rx_hybridmem_config_defaults();
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if (tk == 0) {
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hm_cfg.store_dir = NULL;
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snprintf(label, sizeof(label), "top_k=0 (no HM)");
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} else {
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hm_cfg.store_dir = hm_dir;
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hm_cfg.top_k = tk;
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hm_cfg.evict_fraction = evict_fraction;
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snprintf(label, sizeof(label), "top_k=%d ", tk);
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}
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hm_cfg.max_cache_len = cache_size;
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hits[ti][f] = run_pass(model, tok, cfg, tokens, n_tokens,
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max_tokens, &hm_cfg, fe->key_detail, label);
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rmdir_recursive(hm_dir);
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}
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free(prompt);
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free(tokens);
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fprintf(stderr, "\n");
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}
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/* Summary table */
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fprintf(stderr, "--- Experiment 1 Summary ---\n");
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fprintf(stderr, "%-20s", "Fact");
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for (int ti = 0; ti < n_tk; ti++)
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fprintf(stderr, " tk=%d", top_k_values[ti]);
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fprintf(stderr, "\n");
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int totals[5] = {0};
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for (int f = 0; f < N_FACTS; f++) {
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fprintf(stderr, "%-20s", FACTS[f].key_detail);
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for (int ti = 0; ti < n_tk; ti++) {
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fprintf(stderr, " %s ", hits[ti][f] ? "HIT" : "miss");
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totals[ti] += hits[ti][f];
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}
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fprintf(stderr, "\n");
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}
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fprintf(stderr, "%-20s", "TOTAL");
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for (int ti = 0; ti < n_tk; ti++)
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fprintf(stderr, " %d/%d ", totals[ti], N_FACTS);
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fprintf(stderr, "\n\n");
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/* Verdict */
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fprintf(stderr, "VERDICT: ");
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if (totals[1] >= totals[4]) {
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fprintf(stderr, "PASS — top_k=1 (%d) >= top_k=5 (%d). Fewer seams helps.\n",
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totals[1], totals[4]);
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} else {
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fprintf(stderr, "FAIL — top_k=5 (%d) > top_k=1 (%d). More entries helps more than coherence.\n",
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totals[4], totals[1]);
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}
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}
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/* ================================================================
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* Experiment 2: evict_fraction sweep
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* ================================================================ */
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static void experiment_2(rx_model *model, rx_tokenizer *tok, rx_config cfg,
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const char *filler, int cache_size, int max_tokens) {
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float ef_values[] = {0.25f, 0.5f, 0.75f, 1.0f};
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int n_ef = 4;
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int top_k = 1;
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fprintf(stderr, "\n==========================================\n");
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fprintf(stderr, "EXPERIMENT 2: Chunk Size Sweep\n");
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fprintf(stderr, "==========================================\n");
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fprintf(stderr, "cache_size=%d, top_k=%d\n", cache_size, top_k);
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fprintf(stderr, "evict_fraction values: 0.25 (%d tok), 0.5 (%d tok), 0.75 (%d tok), 1.0 (%d tok)\n\n",
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(int)(cache_size * 0.25f), (int)(cache_size * 0.5f),
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(int)(cache_size * 0.75f), cache_size);
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int hits[4][N_FACTS];
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memset(hits, 0, sizeof(hits));
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for (int f = 0; f < N_FACTS; f++) {
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const fact_entry *fe = &FACTS[f];
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fprintf(stderr, "--- Fact %d: \"%s\" ---\n", f + 1, fe->key_detail);
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char *prompt = build_prompt(fe, filler);
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uint32_t *tokens = (uint32_t*)malloc(32768 * sizeof(uint32_t));
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int n_tokens = rx_tokenizer_encode(tok, prompt, tokens, 32768);
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fprintf(stderr, " Prompt: %d tokens\n", n_tokens);
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for (int ei = 0; ei < n_ef; ei++) {
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float ef = ef_values[ei];
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int evict_count = (int)(cache_size * ef);
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if (evict_count < 1) evict_count = 1;
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char label[64];
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char hm_dir[256];
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snprintf(hm_dir, sizeof(hm_dir), "/tmp/hm_contiguous_exp2_%d_%d", f, ei);
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rmdir_recursive(hm_dir);
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rx_hybridmem_config hm_cfg = rx_hybridmem_config_defaults();
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hm_cfg.store_dir = hm_dir;
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hm_cfg.max_cache_len = cache_size;
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hm_cfg.top_k = top_k;
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hm_cfg.evict_fraction = ef;
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snprintf(label, sizeof(label), "ef=%.2f (%d tok)", ef, evict_count);
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hits[ei][f] = run_pass(model, tok, cfg, tokens, n_tokens,
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max_tokens, &hm_cfg, fe->key_detail, label);
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rmdir_recursive(hm_dir);
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}
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free(prompt);
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free(tokens);
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fprintf(stderr, "\n");
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}
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/* Summary table */
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fprintf(stderr, "--- Experiment 2 Summary ---\n");
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fprintf(stderr, "%-20s", "Fact");
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for (int ei = 0; ei < n_ef; ei++)
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fprintf(stderr, " ef=%.2f", ef_values[ei]);
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fprintf(stderr, "\n");
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int totals[4] = {0};
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for (int f = 0; f < N_FACTS; f++) {
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fprintf(stderr, "%-20s", FACTS[f].key_detail);
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for (int ei = 0; ei < n_ef; ei++) {
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fprintf(stderr, " %s ", hits[ei][f] ? "HIT" : "miss");
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totals[ei] += hits[ei][f];
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}
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fprintf(stderr, "\n");
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}
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fprintf(stderr, "%-20s", "TOTAL");
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for (int ei = 0; ei < n_ef; ei++)
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fprintf(stderr, " %d/%d ", totals[ei], N_FACTS);
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fprintf(stderr, "\n\n");
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/* Verdict */
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fprintf(stderr, "VERDICT: ");
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if (totals[3] >= totals[0] && totals[3] >= totals[1]) {
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fprintf(stderr, "PASS — ef=1.0 (%d) >= smaller chunks. Larger chunks help.\n", totals[3]);
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} else if (totals[0] == totals[1] && totals[1] == totals[2] && totals[2] == totals[3]) {
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fprintf(stderr, "INCONCLUSIVE — all chunk sizes tied at %d/%d.\n", totals[0], N_FACTS);
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} else {
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fprintf(stderr, "MIXED — no clear trend. ef=0.25:%d, 0.5:%d, 0.75:%d, 1.0:%d\n",
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totals[0], totals[1], totals[2], totals[3]);
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}
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}
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/* ================================================================
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* Experiment 3: Best contiguous vs Phase 7b baseline
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* ================================================================ */
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static void experiment_3(rx_model *model, rx_tokenizer *tok, rx_config cfg,
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const char *filler, int cache_size, int max_tokens) {
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fprintf(stderr, "\n==========================================\n");
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fprintf(stderr, "EXPERIMENT 3: Best Contiguous vs Phase 7b\n");
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fprintf(stderr, "==========================================\n");
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fprintf(stderr, "A: No HybridMem (baseline)\n");
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fprintf(stderr, "B: Phase 7b config (top_k=5, ef=0.5)\n");
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fprintf(stderr, "C: Best contiguous (top_k=1, ef=1.0)\n\n");
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int hits_a[N_FACTS], hits_b[N_FACTS], hits_c[N_FACTS];
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memset(hits_a, 0, sizeof(hits_a));
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memset(hits_b, 0, sizeof(hits_b));
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memset(hits_c, 0, sizeof(hits_c));
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for (int f = 0; f < N_FACTS; f++) {
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const fact_entry *fe = &FACTS[f];
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fprintf(stderr, "--- Fact %d: \"%s\" ---\n", f + 1, fe->key_detail);
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char *prompt = build_prompt(fe, filler);
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uint32_t *tokens = (uint32_t*)malloc(32768 * sizeof(uint32_t));
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int n_tokens = rx_tokenizer_encode(tok, prompt, tokens, 32768);
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fprintf(stderr, " Prompt: %d tokens\n", n_tokens);
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/* Condition A: no HybridMem */
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{
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rx_hybridmem_config hm_cfg = rx_hybridmem_config_defaults();
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hm_cfg.store_dir = NULL;
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hm_cfg.max_cache_len = cache_size;
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hits_a[f] = run_pass(model, tok, cfg, tokens, n_tokens,
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max_tokens, &hm_cfg, fe->key_detail,
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"A (no HM) ");
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}
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/* Condition B: Phase 7b config */
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{
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const char *hm_dir = "/tmp/hm_contiguous_exp3_b";
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rmdir_recursive(hm_dir);
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rx_hybridmem_config hm_cfg = rx_hybridmem_config_defaults();
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hm_cfg.store_dir = hm_dir;
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hm_cfg.max_cache_len = cache_size;
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hm_cfg.top_k = 5;
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hm_cfg.evict_fraction = 0.5f;
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hits_b[f] = run_pass(model, tok, cfg, tokens, n_tokens,
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max_tokens, &hm_cfg, fe->key_detail,
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"B (7b: tk=5 ef=.5)");
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rmdir_recursive(hm_dir);
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}
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/* Condition C: best contiguous */
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{
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const char *hm_dir = "/tmp/hm_contiguous_exp3_c";
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rmdir_recursive(hm_dir);
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rx_hybridmem_config hm_cfg = rx_hybridmem_config_defaults();
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hm_cfg.store_dir = hm_dir;
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hm_cfg.max_cache_len = cache_size;
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hm_cfg.top_k = 1;
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hm_cfg.evict_fraction = 1.0f;
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hits_c[f] = run_pass(model, tok, cfg, tokens, n_tokens,
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max_tokens, &hm_cfg, fe->key_detail,
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"C (tk=1, ef=1.0) ");
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rmdir_recursive(hm_dir);
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}
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free(prompt);
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free(tokens);
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fprintf(stderr, "\n");
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}
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/* Summary */
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int total_a = 0, total_b = 0, total_c = 0;
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fprintf(stderr, "--- Experiment 3 Summary ---\n");
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fprintf(stderr, "%-12s A(noHM) B(7b) C(contig)\n", "Fact");
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for (int f = 0; f < N_FACTS; f++) {
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fprintf(stderr, "%-12s %s %s %s\n", FACTS[f].key_detail,
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hits_a[f] ? "HIT" : "miss",
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hits_b[f] ? "HIT" : "miss",
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hits_c[f] ? "HIT" : "miss");
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total_a += hits_a[f];
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total_b += hits_b[f];
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total_c += hits_c[f];
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}
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fprintf(stderr, "%-12s %d/%d %d/%d %d/%d\n\n", "TOTAL",
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total_a, N_FACTS, total_b, N_FACTS, total_c, N_FACTS);
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fprintf(stderr, "VERDICT: ");
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if (total_c > total_b) {
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fprintf(stderr, "PASS — Contiguous (%d) > Phase 7b (%d). Fragment reduction works!\n",
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total_c, total_b);
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} else if (total_c == total_b) {
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fprintf(stderr, "TIED — Contiguous (%d) = Phase 7b (%d). No improvement from contiguity.\n",
|
|
total_c, total_b);
|
|
} else {
|
|
fprintf(stderr, "FAIL — Phase 7b (%d) > Contiguous (%d). More entries beats coherence.\n",
|
|
total_b, total_c);
|
|
}
|
|
}
|
|
|
|
/* ================================================================
|
|
* Main
|
|
* ================================================================ */
|
|
|
|
int main(int argc, char **argv) {
|
|
const char *model_path = NULL;
|
|
const char *vocab_path = NULL;
|
|
const char *filler_path = NULL;
|
|
int cache_size = 8;
|
|
int max_filler_chars = 8000;
|
|
int max_tokens = 48;
|
|
int quantize = 0;
|
|
int experiment = 0; /* 0 = all, 1/2/3 = specific */
|
|
|
|
for (int i = 1; i < argc; i++) {
|
|
if (strcmp(argv[i], "--model") == 0 && i + 1 < argc)
|
|
model_path = argv[++i];
|
|
else if (strcmp(argv[i], "--vocab") == 0 && i + 1 < argc)
|
|
vocab_path = argv[++i];
|
|
else if (strcmp(argv[i], "--filler") == 0 && i + 1 < argc)
|
|
filler_path = argv[++i];
|
|
else if (strcmp(argv[i], "--cache-size") == 0 && i + 1 < argc)
|
|
cache_size = atoi(argv[++i]);
|
|
else if (strcmp(argv[i], "--max-filler") == 0 && i + 1 < argc)
|
|
max_filler_chars = atoi(argv[++i]);
|
|
else if (strcmp(argv[i], "--max-tokens") == 0 && i + 1 < argc)
|
|
max_tokens = atoi(argv[++i]);
|
|
else if (strcmp(argv[i], "--experiment") == 0 && i + 1 < argc)
|
|
experiment = atoi(argv[++i]);
|
|
else if (strcmp(argv[i], "--quantize") == 0)
|
|
quantize = 1;
|
|
else if (strcmp(argv[i], "--help") == 0) {
|
|
fprintf(stderr,
|
|
"Usage: %s --model PATH --vocab PATH --filler PATH [options]\n"
|
|
" --cache-size N KV cache slots per attn layer (default: 8)\n"
|
|
" --max-filler N Max chars of filler text (default: 8000)\n"
|
|
" --max-tokens N Max generated tokens (default: 48)\n"
|
|
" --experiment N Run only experiment N (1, 2, or 3; default: all)\n"
|
|
" --quantize Quantize weights to INT8\n",
|
|
argv[0]);
|
|
return 0;
|
|
}
|
|
}
|
|
|
|
if (!model_path || !vocab_path || !filler_path) {
|
|
fprintf(stderr, "Error: --model, --vocab, and --filler are required\n");
|
|
return 1;
|
|
}
|
|
|
|
/* Load shared resources */
|
|
fprintf(stderr, "Loading tokenizer...\n");
|
|
rx_tokenizer *tok = rx_tokenizer_new(vocab_path);
|
|
if (!tok) { fprintf(stderr, "Failed to load tokenizer\n"); return 1; }
|
|
|
|
fprintf(stderr, "Loading model%s...\n", quantize ? " (INT8)" : "");
|
|
rx_model *model = quantize ? rx_model_load_q8(model_path)
|
|
: rx_model_load(model_path);
|
|
if (!model) { fprintf(stderr, "Failed to load model\n"); return 1; }
|
|
rx_config cfg = rx_model_config(model);
|
|
|
|
/* Load filler */
|
|
char *filler_raw = read_file(filler_path);
|
|
if (!filler_raw) { fprintf(stderr, "Failed to read filler: %s\n", filler_path); return 1; }
|
|
if ((int)strlen(filler_raw) > max_filler_chars)
|
|
filler_raw[max_filler_chars] = '\0';
|
|
|
|
fprintf(stderr, "\n==========================================\n");
|
|
fprintf(stderr, "Contiguous Chunk Retrieval Experiments\n");
|
|
fprintf(stderr, "==========================================\n");
|
|
fprintf(stderr, "Model: %s%s\n", model_path, quantize ? " (INT8)" : "");
|
|
fprintf(stderr, "Filler: %d chars\n", (int)strlen(filler_raw));
|
|
fprintf(stderr, "Cache size: %d, Max gen tokens: %d\n", cache_size, max_tokens);
|
|
|
|
struct timespec t_start, t_end;
|
|
clock_gettime(CLOCK_MONOTONIC, &t_start);
|
|
|
|
if (experiment == 0 || experiment == 1)
|
|
experiment_1(model, tok, cfg, filler_raw, cache_size, max_tokens);
|
|
|
|
if (experiment == 0 || experiment == 2)
|
|
experiment_2(model, tok, cfg, filler_raw, cache_size, max_tokens);
|
|
|
|
if (experiment == 0 || experiment == 3)
|
|
experiment_3(model, tok, cfg, filler_raw, cache_size, max_tokens);
|
|
|
|
clock_gettime(CLOCK_MONOTONIC, &t_end);
|
|
double elapsed = (t_end.tv_sec - t_start.tv_sec) +
|
|
(t_end.tv_nsec - t_start.tv_nsec) / 1e9;
|
|
|
|
fprintf(stderr, "\n==========================================\n");
|
|
fprintf(stderr, "Total wall time: %.1f min\n", elapsed / 60.0);
|
|
fprintf(stderr, "==========================================\n");
|
|
|
|
/* Cleanup */
|
|
free(filler_raw);
|
|
rx_model_free(model);
|
|
rx_tokenizer_free(tok);
|
|
return 0;
|
|
}
|