/* SPDX-License-Identifier: AGPL-3.0-or-later */ /* Copyright (C) 2026 David (Corey) Herrera */ /* * test_hybridmem_retrieval.c — A/B test of HybridMem retrieval with real inference * * Feeds: [fact] [filler from file] [question about fact] * Run A: small cache, NO disk backup → fact is evicted and lost * Run B: small cache, WITH disk backup → fact is evicted but retrievable * * Both runs use identical cache size so the only variable is disk retrieval. * * Usage: * ./examples/test_hybridmem_retrieval \ * --model ../models/base/RWKV-X-0.2B-64k-Base.safetensors \ * --vocab rwkvx/data/rwkv_vocab_v20230424.txt \ * --filler docs/architecture/rwkv-x-deep-dive.md */ #include "rwkvx/rwkvx.h" #include "tensor/tensor.h" #include #include #include #include #include /* Read entire file into malloc'd string. Returns NULL on error. */ static char* read_file(const char *path) { FILE *fp = fopen(path, "r"); if (!fp) return NULL; fseek(fp, 0, SEEK_END); long len = ftell(fp); fseek(fp, 0, SEEK_SET); char *buf = (char*)malloc(len + 1); size_t read = fread(buf, 1, len, fp); buf[read] = '\0'; fclose(fp); return buf; } /* Generate tokens from a state that has already been prefilled. * Returns malloc'd string of generated text. */ static char* generate(rx_model *model, rx_tokenizer *tok, rx_state *state, tm_tensor *logits, int max_tokens, rx_config cfg) { rx_sampling_params params = rx_sampling_defaults(); params.temperature = 0.0f; /* greedy for reproducibility */ uint32_t *gen_tokens = (uint32_t*)calloc(max_tokens, sizeof(uint32_t)); int n_gen = 0; tm_tensor *cur_logits = logits; for (int i = 0; i < max_tokens; i++) { if (!cur_logits) break; uint32_t token = rx_sample(cur_logits, ¶ms, NULL, cfg.vocab_size); if (i > 0) tm_free(cur_logits); if (token == 0) { cur_logits = NULL; break; } /* end-of-text */ gen_tokens[n_gen++] = token; cur_logits = rx_forward(model, token, state); } if (cur_logits && cur_logits != logits) tm_free(cur_logits); char *text = rx_tokenizer_decode(tok, gen_tokens, n_gen); free(gen_tokens); return text; } /* Recursive rm -rf for cleanup */ static void rmdir_recursive(const char *path) { char cmd[512]; snprintf(cmd, sizeof(cmd), "rm -rf %s", path); system(cmd); } 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 hm_top_k = 5; int max_filler_chars = 2000; int max_tokens = 32; int quantize = 0; 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], "--hm-top-k") == 0 && i + 1 < argc) hm_top_k = 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], "--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" " --hm-top-k N Retrieval count (default: 5)\n" " --max-filler N Max chars of filler text (default: 2000)\n" " --max-tokens N Tokens to generate (default: 32)\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; } srand(42); /* 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 quantized)" : ""); 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); /* Build prompt: fact + filler + question */ const char *fact = "The secret project codename is AURORA-7 and the lead researcher is Dr. Kimura."; const char *question = "\n\nQuestion: What is the secret project codename and who leads it?\nAnswer:"; char *filler_raw = read_file(filler_path); if (!filler_raw) { fprintf(stderr, "Failed to read filler file: %s\n", filler_path); return 1; } /* Truncate filler */ int filler_len = (int)strlen(filler_raw); if (filler_len > max_filler_chars) { filler_raw[max_filler_chars] = '\0'; filler_len = max_filler_chars; } /* Assemble full prompt */ int prompt_len = (int)(strlen(fact) + 2 + filler_len + strlen(question) + 1); char *prompt = (char*)malloc(prompt_len); snprintf(prompt, prompt_len, "%s\n\n%s%s", fact, filler_raw, question); free(filler_raw); /* Tokenize */ uint32_t *tokens = (uint32_t*)malloc(32768 * sizeof(uint32_t)); int n_tokens = rx_tokenizer_encode(tok, prompt, tokens, 32768); fprintf(stderr, "\n==========================================\n"); fprintf(stderr, "HybridMem A/B Retrieval Test\n"); fprintf(stderr, "==========================================\n"); fprintf(stderr, "Prompt tokens: %d\n", n_tokens); fprintf(stderr, "Cache size: %d (per attn layer)\n", cache_size); fprintf(stderr, "HM top-k: %d\n", hm_top_k); fprintf(stderr, "Generate: %d tokens (greedy)\n", max_tokens); fprintf(stderr, "Fact: \"%s\"\n", fact); fprintf(stderr, "Question: \"%s\"\n", question); fprintf(stderr, "\n"); /* ============================================================ * Run A: Small cache, NO HybridMem (evicted entries are lost) * ============================================================ */ fprintf(stderr, "--- Run A: cache_size=%d, NO HybridMem ---\n", cache_size); { rx_hybridmem_config hm_cfg = rx_hybridmem_config_defaults(); hm_cfg.store_dir = NULL; /* no disk backup */ hm_cfg.max_cache_len = cache_size; rx_state *state_a = rx_state_new_with_hybridmem(model, &hm_cfg); if (!state_a) { fprintf(stderr, "Failed to create state A\n"); return 1; } struct timespec t0, t1; clock_gettime(CLOCK_MONOTONIC, &t0); tm_tensor *logits_a = NULL; for (int i = 0; i < n_tokens; i++) { if (logits_a) tm_free(logits_a); logits_a = rx_forward(model, tokens[i], state_a); } clock_gettime(CLOCK_MONOTONIC, &t1); double ms = (t1.tv_sec - t0.tv_sec) * 1000.0 + (t1.tv_nsec - t0.tv_nsec) / 1e6; fprintf(stderr, "Prefill: %d tokens in %.1fms (%.1f tok/s)\n", n_tokens, ms, n_tokens * 1000.0 / ms); char *output_a = generate(model, tok, state_a, logits_a, max_tokens, cfg); tm_free(logits_a); rx_state_free(state_a); fprintf(stderr, "Output A: %s\n\n", output_a ? output_a : "(null)"); free(output_a); } /* ============================================================ * Run B: Small cache, WITH HybridMem (evicted entries retrievable) * ============================================================ */ const char *hm_dir = "/tmp/hm_ab_test"; rmdir_recursive(hm_dir); fprintf(stderr, "--- Run B: cache_size=%d, WITH HybridMem (top_k=%d) ---\n", cache_size, hm_top_k); { rx_hybridmem_config hm_cfg = rx_hybridmem_config_defaults(); hm_cfg.store_dir = hm_dir; hm_cfg.max_cache_len = cache_size; hm_cfg.top_k = hm_top_k; rx_state *state_b = rx_state_new_with_hybridmem(model, &hm_cfg); if (!state_b) { fprintf(stderr, "Failed to create state B\n"); return 1; } struct timespec t0, t1; clock_gettime(CLOCK_MONOTONIC, &t0); tm_tensor *logits_b = NULL; for (int i = 0; i < n_tokens; i++) { if (logits_b) tm_free(logits_b); logits_b = rx_forward(model, tokens[i], state_b); } clock_gettime(CLOCK_MONOTONIC, &t1); double ms = (t1.tv_sec - t0.tv_sec) * 1000.0 + (t1.tv_nsec - t0.tv_nsec) / 1e6; fprintf(stderr, "Prefill: %d tokens in %.1fms (%.1f tok/s)\n", n_tokens, ms, n_tokens * 1000.0 / ms); char *output_b = generate(model, tok, state_b, logits_b, max_tokens, cfg); tm_free(logits_b); rx_state_flush(state_b); rx_state_free(state_b); fprintf(stderr, "Output B: %s\n\n", output_b ? output_b : "(null)"); /* Check disk artifacts exist */ struct stat sb; char shard_path[512]; snprintf(shard_path, sizeof(shard_path), "%s/shard_0000.safetensors", hm_dir); if (stat(shard_path, &sb) == 0) { fprintf(stderr, "HybridMem shard: %s (%lld bytes)\n", shard_path, (long long)sb.st_size); } else { fprintf(stderr, "WARNING: No shard file found at %s\n", shard_path); } free(output_b); } /* Cleanup */ rmdir_recursive(hm_dir); free(prompt); free(tokens); rx_model_free(model); rx_tokenizer_free(tok); fprintf(stderr, "\n==========================================\n"); fprintf(stderr, "Compare outputs above. If HybridMem retrieval works,\n"); fprintf(stderr, "Run B should reference AURORA-7 / Dr. Kimura more than Run A.\n"); fprintf(stderr, "==========================================\n"); return 0; }