#define DS4_SERVER_TEST #define DS4_SERVER_TEST_NO_MAIN #include "../ds4_server.c" #ifndef DS4_NO_GPU #include "../ds4_gpu.h" #include bool ds4_test_dspark_cache_window_crop(void); static ds4_engine *test_engine_fast; static ds4_engine *test_engine_quality; static const char *test_model_path(void) { const char *model_path = getenv("DS4_TEST_MODEL"); return (model_path && model_path[0]) ? model_path : "ds4flash.gguf"; } static bool test_env_bool(const char *name) { const char *v = getenv(name); return v && v[0] && strcmp(v, "0") != 0; } static uint32_t test_env_u32(const char *name) { const char *v = getenv(name); if (!v || !v[0]) return 0; char *end = NULL; unsigned long n = strtoul(v, &end, 10); if (end == v) return 0; return n > UINT32_MAX ? UINT32_MAX : (uint32_t)n; } static uint64_t test_env_gib(const char *name) { const char *v = getenv(name); if (!v || !v[0]) return 0; char *end = NULL; unsigned long long n = strtoull(v, &end, 10); if (end == v || n == 0) return 0; const uint64_t one_gib = 1024ull * 1024ull * 1024ull; if (n > UINT64_MAX / one_gib) return UINT64_MAX; return (uint64_t)n * one_gib; } static char *test_save_env(const char *name) { const char *value = getenv(name); if (!value) return NULL; size_t len = strlen(value); char *copy = malloc(len + 1); TEST_ASSERT(copy != NULL); if (!copy) return NULL; memcpy(copy, value, len + 1); return copy; } static void test_restore_env(const char *name, char *saved) { if (saved) { setenv(name, saved, 1); free(saved); } else { unsetenv(name); } } typedef struct { char *cold_decode; char *batch_selected_addr; } test_streaming_prefill_env; static test_streaming_prefill_env test_force_canonical_streaming_prefill(void) { test_streaming_prefill_env saved = { .cold_decode = test_save_env("DS4_METAL_DISABLE_STREAMING_COLD_DECODE_PREFILL"), .batch_selected_addr = test_save_env("DS4_METAL_DISABLE_STREAMING_PREFILL_BATCH_SELECTED_ADDR"), }; if (test_env_bool("DS4_TEST_SSD_STREAMING")) { setenv("DS4_METAL_DISABLE_STREAMING_COLD_DECODE_PREFILL", "1", 1); setenv("DS4_METAL_DISABLE_STREAMING_PREFILL_BATCH_SELECTED_ADDR", "1", 1); } return saved; } static void test_restore_canonical_streaming_prefill( test_streaming_prefill_env saved) { test_restore_env("DS4_METAL_DISABLE_STREAMING_COLD_DECODE_PREFILL", saved.cold_decode); test_restore_env("DS4_METAL_DISABLE_STREAMING_PREFILL_BATCH_SELECTED_ADDR", saved.batch_selected_addr); } static ds4_backend test_model_backend(void) { const char *backend = getenv("DS4_TEST_BACKEND"); if (backend && !strcmp(backend, "cpu")) return DS4_BACKEND_CPU; #ifdef __APPLE__ return DS4_BACKEND_METAL; #else return DS4_BACKEND_CUDA; #endif } static ds4_engine *test_open_engine(bool quality) { ds4_engine *engine = NULL; /* DS4_TEST_MTP loads the MTP head on the fast engine so the speculative * verify regression can reuse it; draft=4 hits the multi-row verify path. */ const char *mtp = getenv("DS4_TEST_MTP"); ds4_engine_options opt = { .model_path = test_model_path(), .backend = test_model_backend(), .quality = quality, .ssd_streaming = test_env_bool("DS4_TEST_SSD_STREAMING"), .ssd_streaming_cold = test_env_bool("DS4_TEST_SSD_STREAMING_COLD"), .ssd_streaming_cache_experts = test_env_u32("DS4_TEST_SSD_STREAMING_CACHE_EXPERTS"), .ssd_streaming_cache_bytes = test_env_gib("DS4_TEST_SSD_STREAMING_CACHE_GB"), .ssd_streaming_preload_experts = test_env_u32("DS4_TEST_SSD_STREAMING_PRELOAD_EXPERTS"), .mtp_path = (mtp && mtp[0] && !quality) ? mtp : NULL, .mtp_draft_tokens = (mtp && mtp[0] && !quality) ? 4 : 0, }; TEST_ASSERT(ds4_engine_open(&engine, &opt) == 0); return engine; } static ds4_engine *test_get_engine(bool quality) { ds4_engine **slot = quality ? &test_engine_quality : &test_engine_fast; if (*slot) return *slot; *slot = test_open_engine(quality); return *slot; } static void test_close_engines(void) { ds4_engine_close(test_engine_fast); ds4_engine_close(test_engine_quality); test_engine_fast = NULL; test_engine_quality = NULL; } static void test_close_engine(bool quality) { ds4_engine **slot = quality ? &test_engine_quality : &test_engine_fast; ds4_engine_close(*slot); *slot = NULL; } static uint64_t test_round_up_u64(uint64_t n, uint64_t align) { return (n + align - 1) & ~(align - 1); } static uint32_t test_float_ordered_u32(float value) { uint32_t bits; memcpy(&bits, &value, sizeof(bits)); return (bits & 0x80000000u) != 0 ? ~bits : bits | 0x80000000u; } typedef struct { size_t mismatch_count; uint32_t max_ulp; float max_abs; } test_float_compare_stats; static test_float_compare_stats test_compare_float_bits( const float *reference, const float *actual, size_t count) { test_float_compare_stats stats = {0}; for (size_t i = 0; i < count; i++) { if (memcmp(&reference[i], &actual[i], sizeof(float)) != 0) { stats.mismatch_count++; } const uint32_t ref_ordered = test_float_ordered_u32(reference[i]); const uint32_t actual_ordered = test_float_ordered_u32(actual[i]); const uint32_t ulp = ref_ordered > actual_ordered ? ref_ordered - actual_ordered : actual_ordered - ref_ordered; if (ulp > stats.max_ulp) stats.max_ulp = ulp; const float abs_error = fabsf(reference[i] - actual[i]); if (abs_error > stats.max_abs) stats.max_abs = abs_error; } return stats; } #if defined(__APPLE__) static const uint32_t test_copy_f32_patterns[] = { 0x00000000u, 0x80000000u, /* signed zero */ 0x7f800000u, 0xff800000u, /* infinities */ 0x7fc00000u, 0x7fc12345u, 0xffc54321u, 0x7fa00001u, /* NaNs */ 0x00000001u, 0x007fffffu, 0x80000001u, 0x807fffffu, /* F32 subnormals */ 0x32ffffffu, 0x33000000u, 0x33000001u, 0x337fffffu, 0x33800000u, 0x33800001u, /* minimum F16 subnormal boundary */ 0x387fbfffu, 0x387fc000u, 0x387fffffu, 0x38800000u, 0x38800001u, /* maximum subnormal/minimum normal boundary */ 0x3f800fffu, 0x3f801000u, 0x3f801001u, 0x3f802fffu, 0x3f803000u, 0x3f803001u, /* round-to-nearest ties */ 0x477fdfffu, 0x477fe000u, 0x477fefffu, 0x477ff000u, 0x477ff001u, 0x47800000u, /* maximum/overflow boundary */ 0xc77fe000u, 0xbf801000u, 0x3eaaaaabu, 0xbeaaaaabu, }; static void test_fill_copy_f32_patterns(void *dst, uint32_t n, uint32_t salt) { uint8_t *bytes = dst; const uint32_t n_patterns = (uint32_t)(sizeof(test_copy_f32_patterns) / sizeof(test_copy_f32_patterns[0])); for (uint32_t i = 0; i < n; i++) { const uint32_t bits = test_copy_f32_patterns[(i + salt) % n_patterns]; memcpy(bytes + (uint64_t)i * sizeof(bits), &bits, sizeof(bits)); } } #endif static uint16_t test_float_to_f16(float f) { union { float f; uint32_t u; } v = { .f = f }; uint32_t sign = (v.u >> 16) & 0x8000u; int32_t exp = (int32_t)((v.u >> 23) & 0xffu) - 127 + 15; uint32_t mant = v.u & 0x7fffffu; if (exp <= 0) { if (exp < -10) return (uint16_t)sign; mant |= 0x800000u; uint32_t shift = (uint32_t)(14 - exp); uint32_t half_mant = mant >> shift; if ((mant >> (shift - 1)) & 1u) half_mant++; return (uint16_t)(sign | half_mant); } if (exp >= 31) return (uint16_t)(sign | 0x7c00u); uint32_t half = sign | ((uint32_t)exp << 10) | (mant >> 13); if (mant & 0x1000u) half++; return (uint16_t)half; } static float test_f16_to_f32(uint16_t h) { uint32_t sign = (uint32_t)(h & 0x8000u) << 16; uint32_t exp = (h >> 10) & 0x1fu; uint32_t mant = h & 0x03ffu; uint32_t bits; if (exp == 0) { if (mant == 0) { bits = sign; } else { exp = 1; while ((mant & 0x0400u) == 0) { mant <<= 1; exp--; } mant &= 0x03ffu; bits = sign | ((exp + 127u - 15u) << 23) | (mant << 13); } } else if (exp == 31) { bits = sign | 0x7f800000u | (mant << 13); } else { bits = sign | ((exp + 127u - 15u) << 23) | (mant << 13); } float f; memcpy(&f, &bits, sizeof(f)); return f; } static void test_fill_q8_0_weights(uint8_t *weights, uint32_t in_dim, uint32_t out_dim, uint32_t seed) { const uint32_t blocks = in_dim / 32u; const uint64_t row_bytes = (uint64_t)blocks * 34u; for (uint32_t o = 0; o < out_dim; o++) { uint8_t *row = weights + (uint64_t)o * row_bytes; for (uint32_t b = 0; b < blocks; b++) { float vals[32]; float amax = 0.0f; for (uint32_t i = 0; i < 32; i++) { const uint32_t k = b * 32u + i; const int v = (int)((o * 17u + k * 23u + (o ^ k) * 3u + seed * 29u + ((o + seed) ^ k) * 5u) % 67u) - 33; vals[i] = (float)v / 96.0f; float av = fabsf(vals[i]); if (av > amax) amax = av; } const uint16_t scale_bits = test_float_to_f16(amax / 127.0f); const float scale = test_f16_to_f32(scale_bits); memcpy(row + b * 34u, &scale_bits, sizeof(scale_bits)); int8_t *qs = (int8_t *)(row + b * 34u + 2u); for (uint32_t i = 0; i < 32; i++) { int q = scale != 0.0f ? (int)lrintf(vals[i] / scale) : 0; if (q > 127) q = 127; if (q < -128) q = -128; qs[i] = (int8_t)q; } } } } static void test_metal_f16_matvec_fast_nr0_4(void) { /* * This is the short regression for the long-context repetition failure. * Decode uses one-token F16 matvecs for several DS4 projections; the fast * nr0=4 variant must be numerically equivalent to the plain kernel. */ const uint32_t in_dim = 4096; const uint32_t out_dim = 512; const uint64_t weight_bytes = (uint64_t)in_dim * out_dim * sizeof(uint16_t); const uint64_t weight_alloc = test_round_up_u64(weight_bytes, (uint64_t)getpagesize()); void *weights_raw = NULL; TEST_ASSERT(posix_memalign(&weights_raw, (size_t)getpagesize(), (size_t)weight_alloc) == 0); if (!weights_raw) return; uint16_t *weights = weights_raw; memset(weights, 0, (size_t)weight_alloc); for (uint32_t o = 0; o < out_dim; o++) { for (uint32_t i = 0; i < in_dim; i++) { float w = (float)((int)((o * 3u + i * 5u) % 23u) - 11) / 64.0f; weights[(uint64_t)o * in_dim + i] = test_float_to_f16(w); } } ds4_gpu_tensor *x = ds4_gpu_tensor_alloc((uint64_t)in_dim * sizeof(float)); ds4_gpu_tensor *out = ds4_gpu_tensor_alloc((uint64_t)out_dim * sizeof(float)); TEST_ASSERT(x != NULL); TEST_ASSERT(out != NULL); if (!x || !out) { ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(out); free(weights_raw); return; } float *x_host = malloc((size_t)in_dim * sizeof(float)); float *out_host = malloc((size_t)out_dim * sizeof(float)); TEST_ASSERT(x_host != NULL); TEST_ASSERT(out_host != NULL); if (!x_host || !out_host) { free(x_host); free(out_host); ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(out); free(weights_raw); return; } for (uint32_t i = 0; i < in_dim; i++) { x_host[i] = (float)((int)(i % 31u) - 15) / 32.0f; } TEST_ASSERT(ds4_gpu_tensor_write(x, 0, x_host, (uint64_t)in_dim * sizeof(float)) != 0); TEST_ASSERT(ds4_gpu_set_model_map(weights_raw, weight_alloc) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(ds4_gpu_matmul_f16_tensor(out, weights_raw, weight_alloc, 0, in_dim, out_dim, x, 1) != 0); TEST_ASSERT(ds4_gpu_tensor_read(out, 0, out_host, (uint64_t)out_dim * sizeof(float)) != 0); float max_abs = 0.0f; for (uint32_t o = 0; o < out_dim; o++) { float ref = 0.0f; for (uint32_t i = 0; i < in_dim; i++) { float w = (float)((int)((o * 3u + i * 5u) % 23u) - 11) / 64.0f; ref += w * x_host[i]; } float err = fabsf(out_host[o] - ref); if (err > max_abs) max_abs = err; } TEST_ASSERT(max_abs < 0.02f); free(x_host); free(out_host); ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(out); free(weights_raw); } static void test_metal_f16_prefill_matmul(void) { const uint32_t in_dim = 128; const uint32_t out_dim = 64; const uint32_t n_tok = 128; const uint64_t weight_bytes = (uint64_t)out_dim * in_dim * sizeof(uint16_t); const uint64_t weight_alloc = test_round_up_u64(weight_bytes, (uint64_t)getpagesize()); const uint64_t x_bytes = (uint64_t)n_tok * in_dim * sizeof(float); const uint64_t out_bytes = (uint64_t)n_tok * out_dim * sizeof(float); void *weights_raw = NULL; TEST_ASSERT(posix_memalign(&weights_raw, (size_t)getpagesize(), (size_t)weight_alloc) == 0); if (!weights_raw) return; uint16_t *weights = weights_raw; memset(weights, 0, (size_t)weight_alloc); for (uint32_t o = 0; o < out_dim; o++) { for (uint32_t i = 0; i < in_dim; i++) { const int v = (int)((o * 11u + i * 13u + (o ^ i) * 5u) % 61u) - 30; weights[(uint64_t)o * in_dim + i] = test_float_to_f16((float)v / 96.0f); } } ds4_gpu_tensor *x = ds4_gpu_tensor_alloc(x_bytes); ds4_gpu_tensor *out = ds4_gpu_tensor_alloc(out_bytes); TEST_ASSERT(x != NULL); TEST_ASSERT(out != NULL); if (!x || !out) { ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(out); free(weights_raw); return; } float *x_host = malloc((size_t)x_bytes); float *out_host = malloc((size_t)out_bytes); TEST_ASSERT(x_host != NULL); TEST_ASSERT(out_host != NULL); if (!x_host || !out_host) { free(x_host); free(out_host); ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(out); free(weights_raw); return; } for (uint32_t t = 0; t < n_tok; t++) { for (uint32_t i = 0; i < in_dim; i++) { const int v = (int)((t * 7u + i * 17u + (t ^ i) * 3u) % 73u) - 36; x_host[(uint64_t)t * in_dim + i] = (float)v / 80.0f; } } for (uint32_t i = 0; i < n_tok * out_dim; i++) { out_host[i] = 12345.0f; } TEST_ASSERT(ds4_gpu_tensor_write(x, 0, x_host, x_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(out, 0, out_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(weights_raw, weight_alloc) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(ds4_gpu_matmul_f16_tensor(out, weights_raw, weight_alloc, 0, in_dim, out_dim, x, n_tok) != 0); TEST_ASSERT(ds4_gpu_tensor_read(out, 0, out_host, out_bytes) != 0); float max_abs = 0.0f; float rms = 0.0f; for (uint32_t t = 0; t < n_tok; t++) { for (uint32_t o = 0; o < out_dim; o++) { float ref = 0.0f; for (uint32_t i = 0; i < in_dim; i++) { ref += test_f16_to_f32(weights[(uint64_t)o * in_dim + i]) * x_host[(uint64_t)t * in_dim + i]; } const float got = out_host[(uint64_t)t * out_dim + o]; TEST_ASSERT(isfinite(got)); const float err = fabsf(got - ref); if (err > max_abs) max_abs = err; rms += err * err; } } rms = sqrtf(rms / (float)(n_tok * out_dim)); TEST_ASSERT(max_abs < 0.08f); TEST_ASSERT(rms < 0.02f); free(x_host); free(out_host); ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(out); free(weights_raw); } static void test_metal_q8_0_prefill_matmul(void) { const uint32_t in_dim = 128; const uint32_t out_dim = 64; const uint32_t n_tok = 128; const uint64_t row_bytes = (uint64_t)(in_dim / 32u) * 34u; const uint64_t weight_bytes = (uint64_t)out_dim * row_bytes; const uint64_t weight_alloc = test_round_up_u64(weight_bytes, (uint64_t)getpagesize()); const uint64_t x_bytes = (uint64_t)n_tok * in_dim * sizeof(float); const uint64_t out_bytes = (uint64_t)n_tok * out_dim * sizeof(float); void *weights_raw = NULL; TEST_ASSERT(posix_memalign(&weights_raw, (size_t)getpagesize(), (size_t)weight_alloc) == 0); if (!weights_raw) return; uint8_t *weights = weights_raw; memset(weights, 0, (size_t)weight_alloc); test_fill_q8_0_weights(weights, in_dim, out_dim, 0); ds4_gpu_tensor *x = ds4_gpu_tensor_alloc(x_bytes); ds4_gpu_tensor *out = ds4_gpu_tensor_alloc(out_bytes); TEST_ASSERT(x != NULL); TEST_ASSERT(out != NULL); if (!x || !out) { ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(out); free(weights_raw); return; } float *x_host = malloc((size_t)x_bytes); float *out_host = malloc((size_t)out_bytes); TEST_ASSERT(x_host != NULL); TEST_ASSERT(out_host != NULL); if (!x_host || !out_host) { free(x_host); free(out_host); ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(out); free(weights_raw); return; } for (uint32_t t = 0; t < n_tok; t++) { for (uint32_t i = 0; i < in_dim; i++) { const int v = (int)((t * 19u + i * 7u + (t ^ i)) % 71u) - 35; x_host[(uint64_t)t * in_dim + i] = (float)v / 80.0f; } } for (uint32_t i = 0; i < n_tok * out_dim; i++) { out_host[i] = 12345.0f; } TEST_ASSERT(ds4_gpu_tensor_write(x, 0, x_host, x_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(out, 0, out_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(weights_raw, weight_alloc) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(ds4_gpu_matmul_q8_0_tensor(out, weights_raw, weight_alloc, 0, in_dim, out_dim, x, n_tok) != 0); TEST_ASSERT(ds4_gpu_tensor_read(out, 0, out_host, out_bytes) != 0); float max_abs = 0.0f; float rms = 0.0f; for (uint32_t t = 0; t < n_tok; t++) { for (uint32_t o = 0; o < out_dim; o++) { const uint8_t *row = weights + (uint64_t)o * row_bytes; float ref = 0.0f; for (uint32_t b = 0; b < in_dim / 32u; b++) { uint16_t scale_bits; memcpy(&scale_bits, row + b * 34u, sizeof(scale_bits)); const float scale = test_f16_to_f32(scale_bits); const int8_t *qs = (const int8_t *)(row + b * 34u + 2u); for (uint32_t i = 0; i < 32; i++) { ref += scale * (float)qs[i] * x_host[(uint64_t)t * in_dim + b * 32u + i]; } } const float got = out_host[(uint64_t)t * out_dim + o]; TEST_ASSERT(isfinite(got)); const float err = fabsf(got - ref); if (err > max_abs) max_abs = err; rms += err * err; } } rms = sqrtf(rms / (float)(n_tok * out_dim)); TEST_ASSERT(max_abs < 0.08f); TEST_ASSERT(rms < 0.02f); free(x_host); free(out_host); ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(out); free(weights_raw); } static void test_metal_pack_slot_rows_f32(void) { const uint32_t n_rows = 3; const uint32_t width = 5; const uint32_t n_slots = 4; const uint32_t slot_cap = 6; const uint64_t slot_count = (uint64_t)n_slots * slot_cap * width; const uint64_t out_count = (uint64_t)n_rows * n_slots * width; const uint64_t slot_bytes = slot_count * sizeof(float); const uint64_t out_bytes = out_count * sizeof(float); ds4_gpu_tensor *slots = ds4_gpu_tensor_alloc(slot_bytes); ds4_gpu_tensor *out = ds4_gpu_tensor_alloc(out_bytes); TEST_ASSERT(slots != NULL); TEST_ASSERT(out != NULL); if (!slots || !out) { ds4_gpu_tensor_free(slots); ds4_gpu_tensor_free(out); return; } float *slot_host = malloc((size_t)slot_bytes); float *out_host = malloc((size_t)out_bytes); TEST_ASSERT(slot_host != NULL); TEST_ASSERT(out_host != NULL); if (!slot_host || !out_host) { free(slot_host); free(out_host); ds4_gpu_tensor_free(slots); ds4_gpu_tensor_free(out); return; } for (uint32_t slot = 0; slot < n_slots; slot++) { for (uint32_t row = 0; row < slot_cap; row++) { for (uint32_t col = 0; col < width; col++) { slot_host[((uint64_t)slot * slot_cap + row) * width + col] = (float)(slot * 1000u + row * 100u + col); } } } for (uint64_t i = 0; i < out_count; i++) out_host[i] = -1.0f; TEST_ASSERT(ds4_gpu_tensor_write(slots, 0, slot_host, slot_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(out, 0, out_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_pack_slot_rows_f32_tensor(out, slots, n_rows, width, n_slots, slot_cap) != 0); TEST_ASSERT(ds4_gpu_tensor_read(out, 0, out_host, out_bytes) != 0); for (uint32_t row = 0; row < n_rows; row++) { for (uint32_t slot = 0; slot < n_slots; slot++) { for (uint32_t col = 0; col < width; col++) { const float ref = slot_host[((uint64_t)slot * slot_cap + row) * width + col]; const float got = out_host[((uint64_t)row * n_slots + slot) * width + col]; TEST_ASSERT(got == ref); } } } free(slot_host); free(out_host); ds4_gpu_tensor_free(slots); ds4_gpu_tensor_free(out); } static void test_metal_store_raw_kv_batch_wrap(void) { const uint32_t raw_cap = 5; const uint32_t head_dim = 3; const uint32_t n_tokens = 4; const uint32_t pos0 = 3; const uint64_t kv_count = (uint64_t)n_tokens * head_dim; const uint64_t raw_count = (uint64_t)raw_cap * head_dim; const uint64_t kv_bytes = kv_count * sizeof(float); const uint64_t raw_bytes = raw_count * sizeof(float); ds4_gpu_tensor *kv = ds4_gpu_tensor_alloc(kv_bytes); ds4_gpu_tensor *raw = ds4_gpu_tensor_alloc(raw_bytes); TEST_ASSERT(kv != NULL); TEST_ASSERT(raw != NULL); if (!kv || !raw) { ds4_gpu_tensor_free(kv); ds4_gpu_tensor_free(raw); return; } float kv_host[12]; float raw_host[15]; for (uint32_t t = 0; t < n_tokens; t++) { for (uint32_t d = 0; d < head_dim; d++) { kv_host[(uint64_t)t * head_dim + d] = (float)(100u * t + d); } } for (uint64_t i = 0; i < raw_count; i++) raw_host[i] = -1.0f; TEST_ASSERT(ds4_gpu_tensor_write(kv, 0, kv_host, kv_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(raw, 0, raw_host, raw_bytes) != 0); TEST_ASSERT(ds4_gpu_store_raw_kv_batch_tensor(raw, kv, raw_cap, pos0, n_tokens, head_dim) != 0); TEST_ASSERT(ds4_gpu_tensor_read(raw, 0, raw_host, raw_bytes) != 0); for (uint32_t t = 0; t < n_tokens; t++) { const uint32_t row = (pos0 + t) % raw_cap; for (uint32_t d = 0; d < head_dim; d++) { const float ref = kv_host[(uint64_t)t * head_dim + d]; const float got = raw_host[(uint64_t)row * head_dim + d]; TEST_ASSERT(got == ref); } } for (uint32_t d = 0; d < head_dim; d++) { TEST_ASSERT(raw_host[(uint64_t)2u * head_dim + d] == -1.0f); } ds4_gpu_tensor_free(kv); ds4_gpu_tensor_free(raw); } static void test_dspark_cache_window_crop(void) { TEST_ASSERT(ds4_test_dspark_cache_window_crop()); } static void test_metal_q8_0_decode_pair_exact_case( uint32_t out0_dim, uint32_t out1_dim, uint32_t seed0, uint32_t seed1) { /* Exercise the Q-A/KV contract with unequal, odd output extents and * independently page-aligned model ranges. The paired kernel must be * bit-identical to two standalone decode matvec dispatches. */ const uint32_t in_dim = 4096; const uint64_t page = (uint64_t)getpagesize(); const uint64_t row_bytes = (uint64_t)(in_dim / 32u) * 34u; const uint64_t weight0_bytes = (uint64_t)out0_dim * row_bytes; const uint64_t weight1_bytes = (uint64_t)out1_dim * row_bytes; const uint64_t weight1_offset = test_round_up_u64(weight0_bytes, page); const uint64_t weight_alloc = test_round_up_u64(weight1_offset + weight1_bytes, page); void *weights_raw = NULL; TEST_ASSERT(posix_memalign(&weights_raw, (size_t)page, (size_t)weight_alloc) == 0); if (!weights_raw) return; memset(weights_raw, 0, (size_t)weight_alloc); test_fill_q8_0_weights((uint8_t *)weights_raw, in_dim, out0_dim, seed0); test_fill_q8_0_weights((uint8_t *)weights_raw + weight1_offset, in_dim, out1_dim, seed1); const uint64_t x_bytes = (uint64_t)in_dim * sizeof(float); const uint64_t out0_bytes = (uint64_t)out0_dim * sizeof(float); const uint64_t out1_bytes = (uint64_t)out1_dim * sizeof(float); ds4_gpu_tensor *x = ds4_gpu_tensor_alloc(x_bytes); ds4_gpu_tensor *ref0 = ds4_gpu_tensor_alloc(out0_bytes); ds4_gpu_tensor *ref1 = ds4_gpu_tensor_alloc(out1_bytes); ds4_gpu_tensor *pair0 = ds4_gpu_tensor_alloc(out0_bytes); ds4_gpu_tensor *pair1 = ds4_gpu_tensor_alloc(out1_bytes); TEST_ASSERT(x != NULL); TEST_ASSERT(ref0 != NULL); TEST_ASSERT(ref1 != NULL); TEST_ASSERT(pair0 != NULL); TEST_ASSERT(pair1 != NULL); if (!x || !ref0 || !ref1 || !pair0 || !pair1) { ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(ref0); ds4_gpu_tensor_free(ref1); ds4_gpu_tensor_free(pair0); ds4_gpu_tensor_free(pair1); free(weights_raw); return; } float *x_host = malloc((size_t)x_bytes); float *ref0_host = malloc((size_t)out0_bytes); float *ref1_host = malloc((size_t)out1_bytes); float *pair0_host = malloc((size_t)out0_bytes); float *pair1_host = malloc((size_t)out1_bytes); TEST_ASSERT(x_host != NULL); TEST_ASSERT(ref0_host != NULL); TEST_ASSERT(ref1_host != NULL); TEST_ASSERT(pair0_host != NULL); TEST_ASSERT(pair1_host != NULL); if (!x_host || !ref0_host || !ref1_host || !pair0_host || !pair1_host) { free(x_host); free(ref0_host); free(ref1_host); free(pair0_host); free(pair1_host); ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(ref0); ds4_gpu_tensor_free(ref1); ds4_gpu_tensor_free(pair0); ds4_gpu_tensor_free(pair1); free(weights_raw); return; } for (uint32_t i = 0; i < in_dim; i++) { const int v = (int)((i * 29u + (i ^ (i >> 3u)) * 7u) % 127u) - 63; x_host[i] = (float)v / 72.0f; } TEST_ASSERT(ds4_gpu_tensor_write(x, 0, x_host, x_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(weights_raw, weight_alloc) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(ds4_gpu_matmul_q8_0_tensor(ref0, weights_raw, weight_alloc, 0, in_dim, out0_dim, x, 1) != 0); TEST_ASSERT(ds4_gpu_matmul_q8_0_tensor(ref1, weights_raw, weight_alloc, weight1_offset, in_dim, out1_dim, x, 1) != 0); TEST_ASSERT(ds4_gpu_matmul_q8_0_pair_tensor(pair0, pair1, weights_raw, weight_alloc, 0, weight1_offset, in_dim, out0_dim, out1_dim, x, 1) != 0); TEST_ASSERT(ds4_gpu_tensor_read(ref0, 0, ref0_host, out0_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read(ref1, 0, ref1_host, out1_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read(pair0, 0, pair0_host, out0_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read(pair1, 0, pair1_host, out1_bytes) != 0); uint32_t mismatch0 = 0; uint32_t mismatch1 = 0; float max_abs0 = 0.0f; float max_abs1 = 0.0f; for (uint32_t i = 0; i < out0_dim; i++) { if (memcmp(&ref0_host[i], &pair0_host[i], sizeof(float)) != 0) mismatch0++; const float err = fabsf(ref0_host[i] - pair0_host[i]); if (err > max_abs0) max_abs0 = err; } for (uint32_t i = 0; i < out1_dim; i++) { if (memcmp(&ref1_host[i], &pair1_host[i], sizeof(float)) != 0) mismatch1++; const float err = fabsf(ref1_host[i] - pair1_host[i]); if (err > max_abs1) max_abs1 = err; } if (mismatch0 != 0 || mismatch1 != 0) { fprintf(stderr, "ds4-test: paired Q8_0 exactness mismatches=%u/%u max_abs=%g, %u/%u max_abs=%g\n", mismatch0, out0_dim, max_abs0, mismatch1, out1_dim, max_abs1); } TEST_ASSERT(mismatch0 == 0); TEST_ASSERT(mismatch1 == 0); free(x_host); free(ref0_host); free(ref1_host); free(pair0_host); free(pair1_host); ds4_gpu_tensor_free(x); ds4_gpu_tensor_free(ref0); ds4_gpu_tensor_free(ref1); ds4_gpu_tensor_free(pair0); ds4_gpu_tensor_free(pair1); free(weights_raw); } static void test_metal_q8_0_decode_pair_exact(void) { /* Cover both possible one-bank tail directions. Distinct seeds ensure a * mistaken A-for-B weight binding cannot compare equal by construction. */ test_metal_q8_0_decode_pair_exact_case(77, 19, 11, 97); test_metal_q8_0_decode_pair_exact_case(19, 77, 23, 131); } #if defined(__APPLE__) static void test_metal_f16_compressor_pair_state_store_exact_case( uint32_t width, uint32_t ratio, uint32_t pos, uint32_t ape_type, uint32_t seed, bool test_decode_pack) { const uint32_t in_dim = 4096u; const uint32_t coff = ratio == 4u ? 2u : 1u; const uint32_t head_dim = width / coff; const uint32_t state_rows = coff * ratio; const bool emit = ((pos + 1u) % ratio) == 0u; TEST_ASSERT(!test_decode_pack || (ratio == 4u && emit && (head_dim == 128u || head_dim == 512u))); const uint64_t page = (uint64_t)getpagesize(); const uint64_t weight_bytes = (uint64_t)width * in_dim * sizeof(uint16_t); const uint64_t score_weight_offset = test_round_up_u64(weight_bytes, page); const uint64_t ape_offset = test_round_up_u64( score_weight_offset + weight_bytes, page); const uint64_t ape_elem_bytes = ape_type == 1u ? 2u : 4u; const uint64_t ape_bytes = (uint64_t)ratio * width * ape_elem_bytes; const uint64_t norm_offset = test_round_up_u64(ape_offset + ape_bytes, page); const uint64_t model_bytes = test_round_up_u64( norm_offset + (uint64_t)head_dim * sizeof(float), page); const uint64_t x_bytes = (uint64_t)in_dim * sizeof(float); const uint64_t out_bytes = (uint64_t)width * sizeof(float); const uint64_t state_count = (uint64_t)state_rows * width; const uint64_t state_bytes = state_count * sizeof(float); const uint64_t comp_bytes = (uint64_t)head_dim * sizeof(float); void *model_raw = NULL; TEST_ASSERT(posix_memalign(&model_raw, (size_t)page, (size_t)model_bytes) == 0); ds4_gpu_tensor *x = ds4_gpu_tensor_alloc(x_bytes); ds4_gpu_tensor *ref_kv = ds4_gpu_tensor_alloc(out_bytes); ds4_gpu_tensor *ref_score = ds4_gpu_tensor_alloc(out_bytes); ds4_gpu_tensor *fused_kv = ds4_gpu_tensor_alloc(out_bytes); ds4_gpu_tensor *fused_score = ds4_gpu_tensor_alloc(out_bytes); ds4_gpu_tensor *ref_state_kv = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *ref_state_score = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *fused_state_kv = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *fused_state_score = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *ref_comp = ds4_gpu_tensor_alloc(comp_bytes); ds4_gpu_tensor *fused_comp = ds4_gpu_tensor_alloc(comp_bytes); float *x_host = malloc((size_t)x_bytes); float *ref_kv_host = malloc((size_t)out_bytes); float *ref_score_host = malloc((size_t)out_bytes); float *fused_kv_host = malloc((size_t)out_bytes); float *fused_score_host = malloc((size_t)out_bytes); float *ref_state_kv_host = malloc((size_t)state_bytes); float *ref_state_score_host = malloc((size_t)state_bytes); float *fused_state_kv_host = malloc((size_t)state_bytes); float *fused_state_score_host = malloc((size_t)state_bytes); float *ref_comp_host = malloc((size_t)comp_bytes); float *fused_comp_host = malloc((size_t)comp_bytes); TEST_ASSERT(model_raw != NULL); TEST_ASSERT(x != NULL); TEST_ASSERT(ref_kv != NULL); TEST_ASSERT(ref_score != NULL); TEST_ASSERT(fused_kv != NULL); TEST_ASSERT(fused_score != NULL); TEST_ASSERT(ref_state_kv != NULL); TEST_ASSERT(ref_state_score != NULL); TEST_ASSERT(fused_state_kv != NULL); TEST_ASSERT(fused_state_score != NULL); TEST_ASSERT(ref_comp != NULL); TEST_ASSERT(fused_comp != NULL); TEST_ASSERT(x_host != NULL); TEST_ASSERT(ref_kv_host != NULL); TEST_ASSERT(ref_score_host != NULL); TEST_ASSERT(fused_kv_host != NULL); TEST_ASSERT(fused_score_host != NULL); TEST_ASSERT(ref_state_kv_host != NULL); TEST_ASSERT(ref_state_score_host != NULL); TEST_ASSERT(fused_state_kv_host != NULL); TEST_ASSERT(fused_state_score_host != NULL); TEST_ASSERT(ref_comp_host != NULL); TEST_ASSERT(fused_comp_host != NULL); const bool allocated = model_raw && x && ref_kv && ref_score && fused_kv && fused_score && ref_state_kv && ref_state_score && fused_state_kv && fused_state_score && ref_comp && fused_comp && x_host && ref_kv_host && ref_score_host && fused_kv_host && fused_score_host && ref_state_kv_host && ref_state_score_host && fused_state_kv_host && fused_state_score_host && ref_comp_host && fused_comp_host; const char *pair_disable_env = "DS4_METAL_DISABLE_COMPRESSOR_PAIR_PROJ"; const char *store_disable_env = "DS4_METAL_DISABLE_COMPRESSOR_STORE_ONE"; const char *decode_pack_disable_env = "DS4_METAL_DISABLE_PRE_M5_COMPRESSOR_RATIO4_DECODE_PACK_FUSION"; const char *exact_reduction_disable_env = "DS4_METAL_DISABLE_PRE_M5_COMPRESSOR_EXACT_REDUCTION_FUSION"; const char *exact_reduction_poison_env = "DS4_METAL_TEST_POISON_COMPRESSOR_EXACT_REDUCTION_SCRATCH"; char *saved_pair_disable = test_save_env(pair_disable_env); char *saved_store_disable = test_save_env(store_disable_env); char *saved_decode_pack_disable = test_save_env(decode_pack_disable_env); char *saved_exact_reduction_disable = test_save_env(exact_reduction_disable_env); char *saved_exact_reduction_poison = test_save_env(exact_reduction_poison_env); test_float_compare_stats kv_stats = {0}; test_float_compare_stats score_stats = {0}; test_float_compare_stats state_kv_stats = {0}; test_float_compare_stats state_score_stats = {0}; test_float_compare_stats comp_stats = {0}; if (allocated) { memset(model_raw, 0, (size_t)model_bytes); uint16_t *kv_weights = model_raw; uint16_t *score_weights = (uint16_t *)((uint8_t *)model_raw + score_weight_offset); for (uint32_t o = 0; o < width; o++) { for (uint32_t i = 0; i < in_dim; i++) { const int kv_value = (int)((o * 17u + i * 23u + (o ^ i) * 3u + seed * 29u) % 67u) - 33; const int score_value = (int)((o * 31u + i * 11u + (o ^ (i >> 2u)) * 5u + seed * 19u) % 71u) - 35; const uint64_t wi = (uint64_t)o * in_dim + i; kv_weights[wi] = test_float_to_f16( (float)kv_value / 96.0f); score_weights[wi] = test_float_to_f16( (float)score_value / 104.0f); } } if (ape_type == 1u) { uint16_t *ape = (uint16_t *)((uint8_t *)model_raw + ape_offset); for (uint64_t i = 0; i < (uint64_t)ratio * width; i++) { const int value = (int)((i * 13u + (i ^ (i >> 3u)) * 7u + seed * 17u) % 61u) - 30; ape[i] = test_float_to_f16((float)value / 80.0f); } } else { float *ape = (float *)((uint8_t *)model_raw + ape_offset); for (uint64_t i = 0; i < (uint64_t)ratio * width; i++) { const int value = (int)((i * 13u + (i ^ (i >> 3u)) * 7u + seed * 17u) % 61u) - 30; ape[i] = (float)value / 80.0f; } } float *norm = (float *)((uint8_t *)model_raw + norm_offset); for (uint32_t i = 0; i < head_dim; i++) { norm[i] = 0.75f + (float)((i * 7u + seed * 3u) % 23u) / 64.0f; } for (uint32_t i = 0; i < in_dim; i++) { const int value = (int)((i * 29u + (i ^ (i >> 4u)) * 9u + seed * 11u) % 127u) - 63; x_host[i] = (float)value / 88.0f; } for (uint32_t i = 0; i < width; i++) { const uint32_t poison = 0x7fc00001u + (i & 0x3ffu); memcpy(ref_kv_host + i, &poison, sizeof(poison)); memcpy(ref_score_host + i, &poison, sizeof(poison)); memcpy(fused_kv_host + i, &poison, sizeof(poison)); memcpy(fused_score_host + i, &poison, sizeof(poison)); } for (uint64_t i = 0; i < state_count; i++) { const int kv_value = (int)((i * 5u + seed * 13u) % 97u) - 48; const int score_value = (int)((i * 7u + seed * 5u) % 101u) - 50; ref_state_kv_host[i] = (float)kv_value / 64.0f; fused_state_kv_host[i] = ref_state_kv_host[i]; ref_state_score_host[i] = (float)score_value / 72.0f; fused_state_score_host[i] = ref_state_score_host[i]; } if (test_decode_pack) { static const uint32_t edge_bits[8] = { 0x00000000u, 0x80000000u, 0x00000001u, 0x80000001u, 0x3f800000u, 0xbf800000u, 0x42a00000u, 0xc2a00000u, }; for (uint32_t col = 0; col < 4u; col++) { for (uint32_t row = 0; row < 8u; row++) { const uint64_t state_col = (row >= 4u ? head_dim : 0u) + col; const uint64_t state_index = (uint64_t)row * width + state_col; const uint32_t score_bits = edge_bits[(row + col) & 7u]; const uint32_t kv_bits = edge_bits[(7u - row + col) & 7u]; memcpy(ref_state_score_host + state_index, &score_bits, sizeof(score_bits)); memcpy(fused_state_score_host + state_index, &score_bits, sizeof(score_bits)); memcpy(ref_state_kv_host + state_index, &kv_bits, sizeof(kv_bits)); memcpy(fused_state_kv_host + state_index, &kv_bits, sizeof(kv_bits)); } } } for (uint32_t i = 0; i < head_dim; i++) { const uint32_t poison = 0x7fc01001u + (i & 0x3ffu); memcpy(ref_comp_host + i, &poison, sizeof(poison)); memcpy(fused_comp_host + i, &poison, sizeof(poison)); } TEST_ASSERT(ds4_gpu_tensor_write(x, 0, x_host, x_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_kv, 0, ref_kv_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_score, 0, ref_score_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_kv, 0, fused_kv_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_score, 0, fused_score_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_state_kv, 0, ref_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_state_score, 0, ref_state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_kv, 0, fused_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_score, 0, fused_state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_comp, 0, ref_comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_comp, 0, fused_comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(model_raw, model_bytes) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(unsetenv(pair_disable_env) == 0); TEST_ASSERT(unsetenv(store_disable_env) == 0); TEST_ASSERT(setenv(exact_reduction_disable_env, "1", 1) == 0); TEST_ASSERT(unsetenv(exact_reduction_poison_env) == 0); if (test_decode_pack) { TEST_ASSERT(setenv(decode_pack_disable_env, "1", 1) == 0); } TEST_ASSERT(ds4_gpu_matmul_f16_pair_tensor( ref_kv, ref_score, model_raw, model_bytes, 0, score_weight_offset, in_dim, width, x, 1) != 0); TEST_ASSERT(ds4_gpu_compressor_update_tensor( ref_kv, ref_score, ref_state_kv, ref_state_score, ref_comp, model_raw, model_bytes, ape_offset, ape_type, norm_offset, 0, head_dim, ratio, pos, 0, 0, 0, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f, false, test_decode_pack, false) != 0); TEST_ASSERT(ds4_gpu_matmul_f16_pair_compressor_store_tensor( fused_kv, fused_score, fused_state_kv, fused_state_score, model_raw, model_bytes, 0, score_weight_offset, ape_offset, ape_type, in_dim, width, x, ratio, pos) == 1); if (test_decode_pack) { TEST_ASSERT(unsetenv(decode_pack_disable_env) == 0); TEST_ASSERT(unsetenv(exact_reduction_disable_env) == 0); TEST_ASSERT(setenv(exact_reduction_poison_env, "1", 1) == 0); } TEST_ASSERT(ds4_gpu_compressor_update_tensor( fused_kv, fused_score, fused_state_kv, fused_state_score, fused_comp, model_raw, model_bytes, ape_offset, ape_type, norm_offset, 0, head_dim, ratio, pos, 0, 0, 0, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f, true, test_decode_pack, false) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_kv, 0, ref_kv_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_score, 0, ref_score_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_kv, 0, fused_kv_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_score, 0, fused_score_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_state_kv, 0, ref_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_state_score, 0, ref_state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_state_kv, 0, fused_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_state_score, 0, fused_state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_comp, 0, ref_comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_comp, 0, fused_comp_host, comp_bytes) != 0); kv_stats = test_compare_float_bits( ref_kv_host, fused_kv_host, width); score_stats = test_compare_float_bits( ref_score_host, fused_score_host, width); state_kv_stats = test_compare_float_bits( ref_state_kv_host, fused_state_kv_host, (size_t)state_count); state_score_stats = test_compare_float_bits( ref_state_score_host, fused_state_score_host, (size_t)state_count); comp_stats = test_compare_float_bits( ref_comp_host, fused_comp_host, head_dim); } test_restore_env(pair_disable_env, saved_pair_disable); test_restore_env(store_disable_env, saved_store_disable); test_restore_env(decode_pack_disable_env, saved_decode_pack_disable); test_restore_env(exact_reduction_disable_env, saved_exact_reduction_disable); test_restore_env( exact_reduction_poison_env, saved_exact_reduction_poison); fprintf(stderr, "ds4-test: compressor pair state-store exact width=%u ratio=%u " "pos=%u emit=%u ape=%s decode_pack=%u exact_reduce=%u " "proj=%zu/%zu state=%zu/%zu " "comp=%zu max_ulp=%u/%u/%u/%u/%u\n", width, ratio, pos, emit ? 1u : 0u, ape_type == 1u ? "f16" : "f32", test_decode_pack ? 1u : 0u, test_decode_pack ? 1u : 0u, kv_stats.mismatch_count, score_stats.mismatch_count, state_kv_stats.mismatch_count, state_score_stats.mismatch_count, comp_stats.mismatch_count, kv_stats.max_ulp, score_stats.max_ulp, state_kv_stats.max_ulp, state_score_stats.max_ulp, comp_stats.max_ulp); TEST_ASSERT(kv_stats.mismatch_count == 0); TEST_ASSERT(score_stats.mismatch_count == 0); TEST_ASSERT(state_kv_stats.mismatch_count == 0); TEST_ASSERT(state_score_stats.mismatch_count == 0); TEST_ASSERT(comp_stats.mismatch_count == 0); free(fused_comp_host); free(ref_comp_host); free(fused_state_score_host); free(fused_state_kv_host); free(ref_state_score_host); free(ref_state_kv_host); free(fused_score_host); free(fused_kv_host); free(ref_score_host); free(ref_kv_host); free(x_host); ds4_gpu_tensor_free(fused_comp); ds4_gpu_tensor_free(ref_comp); ds4_gpu_tensor_free(fused_state_score); ds4_gpu_tensor_free(fused_state_kv); ds4_gpu_tensor_free(ref_state_score); ds4_gpu_tensor_free(ref_state_kv); ds4_gpu_tensor_free(fused_score); ds4_gpu_tensor_free(fused_kv); ds4_gpu_tensor_free(ref_score); ds4_gpu_tensor_free(ref_kv); ds4_gpu_tensor_free(x); free(model_raw); } static void test_metal_f16_compressor_pair_state_store_exact(void) { test_metal_f16_compressor_pair_state_store_exact_case( 256, 4, 8, 0, 17, false); test_metal_f16_compressor_pair_state_store_exact_case( 256, 4, 11, 1, 23, true); test_metal_f16_compressor_pair_state_store_exact_case( 1024, 4, 11, 1, 29, true); test_metal_f16_compressor_pair_state_store_exact_case( 512, 128, 255, 1, 43, false); } static void test_metal_compressor_ape_add_exact_case( uint32_t head_dim, uint32_t ratio, uint32_t pos0, uint32_t n_tokens, uint32_t ape_type, uint32_t seed, bool test_pack_fusion) { const uint32_t coff = ratio == 4u ? 2u : 1u; const uint32_t width = coff * head_dim; const uint32_t state_rows = coff * ratio; const uint32_t n_comp = n_tokens / ratio; const uint64_t input_count = (uint64_t)n_tokens * width; const uint64_t state_count = (uint64_t)state_rows * width; const uint64_t comp_count = (uint64_t)n_comp * head_dim; const uint64_t input_bytes = input_count * sizeof(float); const uint64_t state_bytes = state_count * sizeof(float); const uint64_t comp_bytes = comp_count * sizeof(float); const uint64_t ape_elem_bytes = ape_type == 1u ? 2u : 4u; const uint64_t ape_bytes = (uint64_t)width * ratio * ape_elem_bytes; const uint64_t page = (uint64_t)getpagesize(); const uint64_t norm_offset = test_round_up_u64(ape_bytes, page); const uint64_t model_bytes = test_round_up_u64( norm_offset + (uint64_t)head_dim * sizeof(float), page); ds4_gpu_tensor *kv = ds4_gpu_tensor_alloc(input_bytes); ds4_gpu_tensor *sc = ds4_gpu_tensor_alloc(input_bytes); ds4_gpu_tensor *ref_comp = ds4_gpu_tensor_alloc(comp_bytes); ds4_gpu_tensor *fused_comp = ds4_gpu_tensor_alloc(comp_bytes); ds4_gpu_tensor *ref_state_kv = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *ref_state_score = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *fused_state_kv = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *fused_state_score = ds4_gpu_tensor_alloc(state_bytes); TEST_ASSERT(kv != NULL); TEST_ASSERT(sc != NULL); TEST_ASSERT(ref_comp != NULL); TEST_ASSERT(fused_comp != NULL); TEST_ASSERT(ref_state_kv != NULL); TEST_ASSERT(ref_state_score != NULL); TEST_ASSERT(fused_state_kv != NULL); TEST_ASSERT(fused_state_score != NULL); float *kv_host = malloc((size_t)input_bytes); float *sc_host = malloc((size_t)input_bytes); float *ref_comp_host = malloc((size_t)comp_bytes); float *fused_comp_host = malloc((size_t)comp_bytes); float *ref_state_kv_host = malloc((size_t)state_bytes); float *ref_state_score_host = malloc((size_t)state_bytes); float *fused_state_kv_host = malloc((size_t)state_bytes); float *fused_state_score_host = malloc((size_t)state_bytes); const uint64_t poison_count = input_count > state_count ? input_count : state_count; float *poison_host = test_pack_fusion ? malloc((size_t)(poison_count * sizeof(float))) : NULL; TEST_ASSERT(kv_host != NULL); TEST_ASSERT(sc_host != NULL); TEST_ASSERT(ref_comp_host != NULL); TEST_ASSERT(fused_comp_host != NULL); TEST_ASSERT(ref_state_kv_host != NULL); TEST_ASSERT(ref_state_score_host != NULL); TEST_ASSERT(fused_state_kv_host != NULL); TEST_ASSERT(fused_state_score_host != NULL); TEST_ASSERT(!test_pack_fusion || poison_host != NULL); void *model_raw = NULL; TEST_ASSERT(posix_memalign(&model_raw, (size_t)page, (size_t)model_bytes) == 0); const bool allocated = kv && sc && ref_comp && fused_comp && ref_state_kv && ref_state_score && fused_state_kv && fused_state_score && kv_host && sc_host && ref_comp_host && fused_comp_host && ref_state_kv_host && ref_state_score_host && fused_state_kv_host && fused_state_score_host && (!test_pack_fusion || poison_host) && model_raw; const char *disable_env = "DS4_METAL_DISABLE_COMPRESSOR_APE_ADD"; const char *pack_disable_env = "DS4_METAL_DISABLE_COMPRESSOR_RATIO4_PACK_FUSION"; char *saved_disable = test_save_env(disable_env); char *saved_pack_disable = test_save_env(pack_disable_env); test_float_compare_stats comp_stats = {0}; test_float_compare_stats state_kv_stats = {0}; test_float_compare_stats state_score_stats = {0}; if (allocated) { memset(model_raw, 0, (size_t)model_bytes); if (ape_type == 1u) { uint16_t *ape = model_raw; for (uint64_t i = 0; i < (uint64_t)width * ratio; i++) { const int value = (int)((i * 17u + (i ^ (i >> 4u)) * 5u + seed * 13u) % 127u) - 63; ape[i] = test_float_to_f16((float)value / 80.0f); } } else { float *ape = model_raw; for (uint64_t i = 0; i < (uint64_t)width * ratio; i++) { const int value = (int)((i * 17u + (i ^ (i >> 4u)) * 5u + seed * 13u) % 127u) - 63; ape[i] = (float)value / 80.0f; } } float *norm = (float *)((uint8_t *)model_raw + norm_offset); for (uint32_t i = 0; i < head_dim; i++) { norm[i] = 0.75f + (float)((i * 7u + seed) % 19u) / 64.0f; } for (uint64_t i = 0; i < input_count; i++) { const int kv_value = (int)((i * 29u + (i ^ (i >> 5u)) * 3u + seed * 23u) % 181u) - 90; const int sc_value = (int)((i * 31u + (i ^ (i >> 3u)) * 11u + seed * 17u) % 173u) - 86; kv_host[i] = (float)kv_value / 112.0f; sc_host[i] = (float)sc_value / 96.0f; } kv_host[0] = -0.0f; sc_host[0] = -0.0f; // Exercise exact-add edge values in the first active APE row. Using // bit patterns avoids host fast-math rewriting signed zeros or // subnormals before the legacy and fused Metal paths see them. const uint32_t cutoff = (n_tokens / ratio) * ratio; const uint32_t edge_token = cutoff < n_tokens ? cutoff : cutoff - ratio; const uint64_t edge_ape = (uint64_t)((pos0 + edge_token) % ratio) * width; float *edge_score = sc_host + (uint64_t)edge_token * width; static const uint16_t edge_f16[] = { 0x0000u, 0x8000u, 0x0001u, 0x8001u, 0x3c00u, 0xbc00u, 0x7bffu, 0xfbffu, }; static const uint32_t edge_f32[] = { 0x00000000u, 0x80000000u, 0x00000001u, 0x80000001u, 0x3f800000u, 0xbf800000u, 0x7f7fffffu, 0xff7fffffu, }; static const uint32_t edge_score_f16[] = { 0x80000000u, 0x00000000u, 0x00000000u, 0x80000000u, 0xbf800000u, 0x3f800000u, 0xc77fe000u, 0x477fe000u, }; static const uint32_t edge_score_f32[] = { 0x80000000u, 0x00000000u, 0x00000000u, 0x80000000u, 0xbf800000u, 0x3f800000u, 0xff7fffffu, 0x7f7fffffu, }; if (ape_type == 1u) { uint16_t *ape = model_raw; memcpy(ape + edge_ape, edge_f16, sizeof(edge_f16)); for (uint32_t i = 0; i < 8u; i++) { memcpy(edge_score + i, edge_score_f16 + i, sizeof(uint32_t)); } } else { uint32_t *ape = model_raw; memcpy(ape + edge_ape, edge_f32, sizeof(edge_f32)); for (uint32_t i = 0; i < 8u; i++) { memcpy(edge_score + i, edge_score_f32 + i, sizeof(uint32_t)); } } for (uint64_t i = 0; i < state_count; i++) { ref_state_kv_host[i] = 1234.0f; fused_state_kv_host[i] = 1234.0f; ref_state_score_host[i] = -1234.0f; fused_state_score_host[i] = -1234.0f; } TEST_ASSERT(ds4_gpu_tensor_write(kv, 0, kv_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(sc, 0, sc_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_state_kv, 0, ref_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_kv, 0, fused_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_state_score, 0, ref_state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_score, 0, fused_state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(model_raw, model_bytes) != 0); ds4_gpu_set_quality(false); if (test_pack_fusion) { TEST_ASSERT(unsetenv(disable_env) == 0); } else { TEST_ASSERT(setenv(disable_env, "1", 1) == 0); } TEST_ASSERT(setenv(pack_disable_env, "1", 1) == 0); TEST_ASSERT(ds4_gpu_compressor_prefill_tensor( ref_comp, ref_state_kv, ref_state_score, kv, sc, model_raw, model_bytes, 0, ape_type, norm_offset, 0, head_dim, ratio, pos0, n_tokens, 0, 0, false, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f) != 0); if (test_pack_fusion) { // Overwrite every persistent pack cell with qNaN payloads through // the legacy replay path. This makes an omitted candidate write // observable even for plane-zero padding, which normal legacy // packing would otherwise leave at the correct 0/-inf values. for (uint64_t i = 0; i < poison_count; i++) { const uint32_t bits = 0x7fc00001u + (uint32_t)(i & 0x3ffu); memcpy(poison_host + i, &bits, sizeof(bits)); } TEST_ASSERT(ds4_gpu_tensor_write( kv, 0, poison_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( sc, 0, poison_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_kv, 0, poison_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_score, 0, poison_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_compressor_prefill_ratio4_replay_tensor( fused_comp, fused_state_kv, fused_state_score, kv, sc, model_raw, model_bytes, 0, ape_type, norm_offset, 0, head_dim, 0, n_comp * ratio, 0, 0, false, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f) != 0); TEST_ASSERT(ds4_gpu_tensor_write( kv, 0, kv_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( sc, 0, sc_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_kv, 0, fused_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_score, 0, fused_state_score_host, state_bytes) != 0); TEST_ASSERT(unsetenv(pack_disable_env) == 0); } else { TEST_ASSERT(unsetenv(disable_env) == 0); } TEST_ASSERT(ds4_gpu_compressor_prefill_tensor( fused_comp, fused_state_kv, fused_state_score, kv, sc, model_raw, model_bytes, 0, ape_type, norm_offset, 0, head_dim, ratio, pos0, n_tokens, 0, 0, false, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f) != 0); if (test_pack_fusion) { TEST_ASSERT(ds4_gpu_tensor_read( kv, 0, poison_host, input_bytes) != 0); TEST_ASSERT(memcmp(kv_host, poison_host, (size_t)input_bytes) == 0); TEST_ASSERT(ds4_gpu_tensor_read( sc, 0, poison_host, input_bytes) != 0); TEST_ASSERT(memcmp(sc_host, poison_host, (size_t)input_bytes) == 0); } TEST_ASSERT(ds4_gpu_tensor_read( ref_comp, 0, ref_comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_comp, 0, fused_comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_state_kv, 0, ref_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_state_kv, 0, fused_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_state_score, 0, ref_state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_state_score, 0, fused_state_score_host, state_bytes) != 0); comp_stats = test_compare_float_bits( ref_comp_host, fused_comp_host, (size_t)comp_count); state_kv_stats = test_compare_float_bits( ref_state_kv_host, fused_state_kv_host, (size_t)state_count); state_score_stats = test_compare_float_bits( ref_state_score_host, fused_state_score_host, (size_t)state_count); } test_restore_env(disable_env, saved_disable); test_restore_env(pack_disable_env, saved_pack_disable); fprintf(stderr, "ds4-test: compressor %s exact head=%u ratio=%u pos=%u " "tokens=%u ape=%s comp=%zu/%llu state_kv=%zu/%llu " "state_score=%zu/%llu max_ulp=%u/%u/%u\n", test_pack_fusion ? "ratio4 pack" : "APE add", head_dim, ratio, pos0, n_tokens, ape_type == 1u ? "f16" : "f32", comp_stats.mismatch_count, (unsigned long long)comp_count, state_kv_stats.mismatch_count, (unsigned long long)state_count, state_score_stats.mismatch_count, (unsigned long long)state_count, comp_stats.max_ulp, state_kv_stats.max_ulp, state_score_stats.max_ulp); TEST_ASSERT(comp_stats.mismatch_count == 0); TEST_ASSERT(state_kv_stats.mismatch_count == 0); TEST_ASSERT(state_score_stats.mismatch_count == 0); free(model_raw); free(poison_host); free(fused_state_score_host); free(fused_state_kv_host); free(ref_state_score_host); free(ref_state_kv_host); free(fused_comp_host); free(ref_comp_host); free(sc_host); free(kv_host); ds4_gpu_tensor_free(fused_state_score); ds4_gpu_tensor_free(fused_state_kv); ds4_gpu_tensor_free(ref_state_score); ds4_gpu_tensor_free(ref_state_kv); ds4_gpu_tensor_free(fused_comp); ds4_gpu_tensor_free(ref_comp); ds4_gpu_tensor_free(sc); ds4_gpu_tensor_free(kv); } static void test_metal_compressor_ape_add_exact(void) { test_metal_compressor_ape_add_exact_case(128, 4, 3, 16, 1, 7, false); test_metal_compressor_ape_add_exact_case(512, 4, 0, 16, 1, 13, false); test_metal_compressor_ape_add_exact_case(512, 4, 1, 14, 0, 19, false); test_metal_compressor_ape_add_exact_case(512, 128, 127, 257, 1, 31, false); } static void test_metal_compressor_ratio4_pack_exact(void) { test_metal_compressor_ape_add_exact_case(128, 4, 0, 4, 1, 37, true); test_metal_compressor_ape_add_exact_case(512, 4, 0, 8, 1, 41, true); test_metal_compressor_ape_add_exact_case(512, 4, 1, 14, 0, 43, true); } static void test_metal_compressor_ratio4_replay_pack_exact_case( uint32_t head_dim, uint32_t n_tokens, uint32_t seed) { const uint32_t width = 2u * head_dim; const uint32_t n_comp = n_tokens / 4u; const uint64_t input_count = (uint64_t)n_tokens * width; const uint64_t state_count = (uint64_t)8u * width; const uint64_t comp_count = (uint64_t)n_comp * head_dim; const uint64_t input_bytes = input_count * sizeof(float); const uint64_t state_bytes = state_count * sizeof(float); const uint64_t comp_bytes = comp_count * sizeof(float); const uint64_t ape_bytes = (uint64_t)4u * width * sizeof(uint16_t); const uint64_t page = (uint64_t)getpagesize(); const uint64_t norm_offset = test_round_up_u64(ape_bytes, page); const uint64_t model_bytes = test_round_up_u64( norm_offset + (uint64_t)head_dim * sizeof(float), page); ds4_gpu_tensor *kv = ds4_gpu_tensor_alloc(input_bytes); ds4_gpu_tensor *sc = ds4_gpu_tensor_alloc(input_bytes); ds4_gpu_tensor *ref_comp = ds4_gpu_tensor_alloc(comp_bytes); ds4_gpu_tensor *fused_comp = ds4_gpu_tensor_alloc(comp_bytes); ds4_gpu_tensor *ref_state_kv = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *ref_state_score = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *fused_state_kv = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *fused_state_score = ds4_gpu_tensor_alloc(state_bytes); float *kv_host = malloc((size_t)input_bytes); float *sc_host = malloc((size_t)input_bytes); float *state_kv_host = malloc((size_t)state_bytes); float *state_score_host = malloc((size_t)state_bytes); float *source_after_host = malloc((size_t)input_bytes); float *ref_comp_host = malloc((size_t)comp_bytes); float *fused_comp_host = malloc((size_t)comp_bytes); float *ref_state_kv_host = malloc((size_t)state_bytes); float *fused_state_kv_host = malloc((size_t)state_bytes); float *ref_state_score_host = malloc((size_t)state_bytes); float *fused_state_score_host = malloc((size_t)state_bytes); void *model_raw = NULL; TEST_ASSERT(posix_memalign( &model_raw, (size_t)page, (size_t)model_bytes) == 0); TEST_ASSERT(kv != NULL); TEST_ASSERT(sc != NULL); TEST_ASSERT(ref_comp != NULL); TEST_ASSERT(fused_comp != NULL); TEST_ASSERT(ref_state_kv != NULL); TEST_ASSERT(ref_state_score != NULL); TEST_ASSERT(fused_state_kv != NULL); TEST_ASSERT(fused_state_score != NULL); TEST_ASSERT(kv_host != NULL); TEST_ASSERT(sc_host != NULL); TEST_ASSERT(state_kv_host != NULL); TEST_ASSERT(state_score_host != NULL); TEST_ASSERT(source_after_host != NULL); TEST_ASSERT(ref_comp_host != NULL); TEST_ASSERT(fused_comp_host != NULL); TEST_ASSERT(ref_state_kv_host != NULL); TEST_ASSERT(fused_state_kv_host != NULL); TEST_ASSERT(ref_state_score_host != NULL); TEST_ASSERT(fused_state_score_host != NULL); TEST_ASSERT(model_raw != NULL); const char *ape_disable_env = "DS4_METAL_DISABLE_COMPRESSOR_APE_ADD"; const char *pack_disable_env = "DS4_METAL_DISABLE_COMPRESSOR_RATIO4_PACK_FUSION"; char *saved_ape_disable = test_save_env(ape_disable_env); char *saved_pack_disable = test_save_env(pack_disable_env); test_float_compare_stats comp_stats = {0}; test_float_compare_stats state_kv_stats = {0}; test_float_compare_stats state_score_stats = {0}; const bool allocated = kv && sc && ref_comp && fused_comp && ref_state_kv && ref_state_score && fused_state_kv && fused_state_score && kv_host && sc_host && state_kv_host && state_score_host && source_after_host && ref_comp_host && fused_comp_host && ref_state_kv_host && fused_state_kv_host && ref_state_score_host && fused_state_score_host && model_raw; if (allocated) { memset(model_raw, 0, (size_t)model_bytes); uint16_t *ape = model_raw; for (uint64_t i = 0; i < (uint64_t)4u * width; i++) { const int value = (int)((i * 19u + (i ^ (i >> 3u)) * 7u + seed * 11u) % 113u) - 56; ape[i] = test_float_to_f16((float)value / 72.0f); } float *norm = (float *)((uint8_t *)model_raw + norm_offset); for (uint32_t i = 0; i < head_dim; i++) { norm[i] = 0.875f + (float)((i * 5u + seed) % 17u) / 64.0f; } for (uint64_t i = 0; i < input_count; i++) { const int kv_value = (int)((i * 31u + (i ^ (i >> 4u)) * 5u + seed * 13u) % 193u) - 96; const int sc_value = (int)((i * 37u + (i ^ (i >> 5u)) * 9u + seed * 17u) % 181u) - 90; kv_host[i] = (float)kv_value / 104.0f; sc_host[i] = (float)sc_value / 88.0f; } for (uint64_t i = 0; i < state_count; i++) { const int kv_value = (int)((i * 23u + (i ^ (i >> 2u)) * 3u + seed * 29u) % 167u) - 83; const int sc_value = (int)((i * 41u + (i ^ (i >> 6u)) * 11u + seed * 7u) % 157u) - 78; state_kv_host[i] = (float)kv_value / 80.0f; state_score_host[i] = (float)sc_value / 92.0f; } const uint32_t negative_zero = 0x80000000u; memcpy(kv_host, &negative_zero, sizeof(negative_zero)); memcpy(state_kv_host, &negative_zero, sizeof(negative_zero)); TEST_ASSERT(ds4_gpu_tensor_write(kv, 0, kv_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(sc, 0, sc_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_state_kv, 0, state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_kv, 0, state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_state_score, 0, state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_score, 0, state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(model_raw, model_bytes) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(unsetenv(ape_disable_env) == 0); TEST_ASSERT(setenv(pack_disable_env, "1", 1) == 0); TEST_ASSERT(ds4_gpu_compressor_prefill_ratio4_replay_tensor( ref_comp, ref_state_kv, ref_state_score, kv, sc, model_raw, model_bytes, 0, 1, norm_offset, 0, head_dim, 0, n_tokens, 0, 0, false, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f) != 0); // Poison every persistent pack cell through the legacy full-fill path // so a missing candidate write cannot inherit the reference value. for (uint64_t i = 0; i < input_count; i++) { const uint32_t bits = 0x7fc00001u + (uint32_t)(i & 0x3ffu); memcpy(kv_host + i, &bits, sizeof(bits)); memcpy(sc_host + i, &bits, sizeof(bits)); } for (uint64_t i = 0; i < state_count; i++) { const uint32_t bits = 0x7fc00401u + (uint32_t)(i & 0x3ffu); memcpy(ref_state_kv_host + i, &bits, sizeof(bits)); memcpy(ref_state_score_host + i, &bits, sizeof(bits)); } TEST_ASSERT(ds4_gpu_tensor_write(kv, 0, kv_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(sc, 0, sc_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_kv, 0, ref_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_score, 0, ref_state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_compressor_prefill_ratio4_replay_tensor( fused_comp, fused_state_kv, fused_state_score, kv, sc, model_raw, model_bytes, 0, 1, norm_offset, 0, head_dim, 0, n_tokens, 0, 0, false, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f) != 0); // Restore finite sources and the candidate's original replay state. for (uint64_t i = 0; i < input_count; i++) { const int kv_value = (int)((i * 31u + (i ^ (i >> 4u)) * 5u + seed * 13u) % 193u) - 96; const int sc_value = (int)((i * 37u + (i ^ (i >> 5u)) * 9u + seed * 17u) % 181u) - 90; kv_host[i] = (float)kv_value / 104.0f; sc_host[i] = (float)sc_value / 88.0f; } memcpy(kv_host, &negative_zero, sizeof(negative_zero)); TEST_ASSERT(ds4_gpu_tensor_write(kv, 0, kv_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(sc, 0, sc_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_kv, 0, state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_state_score, 0, state_score_host, state_bytes) != 0); TEST_ASSERT(unsetenv(pack_disable_env) == 0); TEST_ASSERT(ds4_gpu_compressor_prefill_ratio4_replay_tensor( fused_comp, fused_state_kv, fused_state_score, kv, sc, model_raw, model_bytes, 0, 1, norm_offset, 0, head_dim, 0, n_tokens, 0, 0, false, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f) != 0); TEST_ASSERT(ds4_gpu_tensor_read( kv, 0, source_after_host, input_bytes) != 0); TEST_ASSERT(memcmp(kv_host, source_after_host, (size_t)input_bytes) == 0); TEST_ASSERT(ds4_gpu_tensor_read( sc, 0, source_after_host, input_bytes) != 0); TEST_ASSERT(memcmp(sc_host, source_after_host, (size_t)input_bytes) == 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_comp, 0, ref_comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_comp, 0, fused_comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_state_kv, 0, ref_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_state_kv, 0, fused_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_state_score, 0, ref_state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_state_score, 0, fused_state_score_host, state_bytes) != 0); comp_stats = test_compare_float_bits( ref_comp_host, fused_comp_host, (size_t)comp_count); state_kv_stats = test_compare_float_bits( ref_state_kv_host, fused_state_kv_host, (size_t)state_count); state_score_stats = test_compare_float_bits( ref_state_score_host, fused_state_score_host, (size_t)state_count); } test_restore_env(ape_disable_env, saved_ape_disable); test_restore_env(pack_disable_env, saved_pack_disable); fprintf(stderr, "ds4-test: compressor ratio4 replay pack exact head=%u " "tokens=%u comp=%zu/%llu state_kv=%zu/%llu " "state_score=%zu/%llu max_ulp=%u/%u/%u\n", head_dim, n_tokens, comp_stats.mismatch_count, (unsigned long long)comp_count, state_kv_stats.mismatch_count, (unsigned long long)state_count, state_score_stats.mismatch_count, (unsigned long long)state_count, comp_stats.max_ulp, state_kv_stats.max_ulp, state_score_stats.max_ulp); TEST_ASSERT(comp_stats.mismatch_count == 0); TEST_ASSERT(state_kv_stats.mismatch_count == 0); TEST_ASSERT(state_score_stats.mismatch_count == 0); free(model_raw); free(fused_state_score_host); free(ref_state_score_host); free(fused_state_kv_host); free(ref_state_kv_host); free(fused_comp_host); free(ref_comp_host); free(source_after_host); free(state_score_host); free(state_kv_host); free(sc_host); free(kv_host); ds4_gpu_tensor_free(fused_state_score); ds4_gpu_tensor_free(fused_state_kv); ds4_gpu_tensor_free(ref_state_score); ds4_gpu_tensor_free(ref_state_kv); ds4_gpu_tensor_free(fused_comp); ds4_gpu_tensor_free(ref_comp); ds4_gpu_tensor_free(sc); ds4_gpu_tensor_free(kv); } static void test_metal_compressor_ratio4_replay_pack_exact(void) { test_metal_compressor_ratio4_replay_pack_exact_case(128, 4, 47); test_metal_compressor_ratio4_replay_pack_exact_case(512, 8, 53); } static void test_metal_compressor_ratio4_direct_pool_exact_case( uint32_t head_dim, uint32_t pos0, uint32_t n_tokens, uint32_t ape_type, bool replay, uint32_t seed) { const uint32_t ratio = 4u; const uint32_t width = 2u * head_dim; const uint32_t state_rows = 8u; const uint32_t n_comp = n_tokens / ratio; const uint64_t input_count = (uint64_t)n_tokens * width; const uint64_t state_count = (uint64_t)state_rows * width; const uint64_t comp_count = (uint64_t)n_comp * head_dim; const uint64_t input_bytes = input_count * sizeof(float); const uint64_t state_bytes = state_count * sizeof(float); const uint64_t comp_bytes = comp_count * sizeof(float); const uint64_t ape_elem_bytes = ape_type == 1u ? 2u : 4u; const uint64_t ape_bytes = (uint64_t)ratio * width * ape_elem_bytes; const uint64_t page = (uint64_t)getpagesize(); const uint64_t norm_offset = test_round_up_u64(ape_bytes, page); const uint64_t model_bytes = test_round_up_u64( norm_offset + (uint64_t)head_dim * sizeof(float), page); TEST_ASSERT(n_comp != 0); TEST_ASSERT(!replay || ((pos0 & 3u) == 0u && (n_tokens & 3u) == 0u)); ds4_gpu_tensor *kv = ds4_gpu_tensor_alloc(input_bytes); ds4_gpu_tensor *sc = ds4_gpu_tensor_alloc(input_bytes); ds4_gpu_tensor *ref_comp = ds4_gpu_tensor_alloc(comp_bytes); ds4_gpu_tensor *direct_comp = ds4_gpu_tensor_alloc(comp_bytes); ds4_gpu_tensor *ref_state_kv = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *ref_state_score = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *direct_state_kv = ds4_gpu_tensor_alloc(state_bytes); ds4_gpu_tensor *direct_state_score = ds4_gpu_tensor_alloc(state_bytes); float *kv_host = malloc((size_t)input_bytes); float *sc_host = malloc((size_t)input_bytes); float *source_after_host = malloc((size_t)input_bytes); float *state_kv_host = malloc((size_t)state_bytes); float *state_score_host = malloc((size_t)state_bytes); float *ref_comp_host = malloc((size_t)comp_bytes); float *direct_comp_host = malloc((size_t)comp_bytes); float *ref_state_kv_host = malloc((size_t)state_bytes); float *direct_state_kv_host = malloc((size_t)state_bytes); float *ref_state_score_host = malloc((size_t)state_bytes); float *direct_state_score_host = malloc((size_t)state_bytes); void *model_raw = NULL; TEST_ASSERT(posix_memalign( &model_raw, (size_t)page, (size_t)model_bytes) == 0); TEST_ASSERT(kv != NULL); TEST_ASSERT(sc != NULL); TEST_ASSERT(ref_comp != NULL); TEST_ASSERT(direct_comp != NULL); TEST_ASSERT(ref_state_kv != NULL); TEST_ASSERT(ref_state_score != NULL); TEST_ASSERT(direct_state_kv != NULL); TEST_ASSERT(direct_state_score != NULL); TEST_ASSERT(kv_host != NULL); TEST_ASSERT(sc_host != NULL); TEST_ASSERT(source_after_host != NULL); TEST_ASSERT(state_kv_host != NULL); TEST_ASSERT(state_score_host != NULL); TEST_ASSERT(ref_comp_host != NULL); TEST_ASSERT(direct_comp_host != NULL); TEST_ASSERT(ref_state_kv_host != NULL); TEST_ASSERT(direct_state_kv_host != NULL); TEST_ASSERT(ref_state_score_host != NULL); TEST_ASSERT(direct_state_score_host != NULL); TEST_ASSERT(model_raw != NULL); const char *ape_disable_env = "DS4_METAL_DISABLE_COMPRESSOR_APE_ADD"; const char *pack_disable_env = "DS4_METAL_DISABLE_COMPRESSOR_RATIO4_PACK_FUSION"; const char *direct_disable_env = "DS4_METAL_DISABLE_COMPRESSOR_RATIO4_DIRECT_POOL"; char *saved_ape_disable = test_save_env(ape_disable_env); char *saved_pack_disable = test_save_env(pack_disable_env); char *saved_direct_disable = test_save_env(direct_disable_env); test_float_compare_stats comp_stats = {0}; test_float_compare_stats state_kv_stats = {0}; test_float_compare_stats state_score_stats = {0}; const bool allocated = kv && sc && ref_comp && direct_comp && ref_state_kv && ref_state_score && direct_state_kv && direct_state_score && kv_host && sc_host && source_after_host && state_kv_host && state_score_host && ref_comp_host && direct_comp_host && ref_state_kv_host && direct_state_kv_host && ref_state_score_host && direct_state_score_host && model_raw; if (allocated) { memset(model_raw, 0, (size_t)model_bytes); if (ape_type == 1u) { uint16_t *ape = model_raw; for (uint64_t i = 0; i < (uint64_t)ratio * width; i++) { const int value = (int)((i * 17u + (i ^ (i >> 4u)) * 5u + seed * 13u) % 127u) - 63; ape[i] = test_float_to_f16((float)value / 80.0f); } } else { float *ape = model_raw; for (uint64_t i = 0; i < (uint64_t)ratio * width; i++) { const int value = (int)((i * 17u + (i ^ (i >> 4u)) * 5u + seed * 13u) % 127u) - 63; ape[i] = (float)value / 80.0f; } } float *norm = (float *)((uint8_t *)model_raw + norm_offset); for (uint32_t i = 0; i < head_dim; i++) { norm[i] = 0.75f + (float)((i * 7u + seed) % 19u) / 64.0f; } for (uint64_t i = 0; i < input_count; i++) { const uint32_t token = (uint32_t)(i / width); const uint32_t col = (uint32_t)(i - (uint64_t)token * width); const int kv_value = (int)(((uint64_t)token * 37u + (uint64_t)col * 29u + (col >= head_dim ? 71u : 3u) + seed * 23u) % 193u) - 96; const int sc_value = (int)(((uint64_t)token * 41u + (uint64_t)col * 31u + (col >= head_dim ? 17u : 83u) + seed * 11u) % 181u) - 90; kv_host[i] = (float)kv_value / 104.0f; sc_host[i] = (float)sc_value / 32.0f; } const uint32_t negative_zero = 0x80000000u; memcpy(kv_host, &negative_zero, sizeof(negative_zero)); memcpy(sc_host + width + head_dim, &negative_zero, sizeof(negative_zero)); for (uint32_t row = 0; row < state_rows; row++) { for (uint32_t col = 0; col < width; col++) { const uint64_t i = (uint64_t)row * width + col; if (replay && row < ratio && col < head_dim) { const int kv_value = (int)(((uint64_t)row * 43u + (uint64_t)col * 19u + seed * 29u) % 167u) - 83; const int sc_value = (int)(((uint64_t)row * 47u + (uint64_t)col * 23u + seed * 7u) % 157u) - 78; state_kv_host[i] = (float)kv_value / 80.0f; state_score_host[i] = (float)sc_value / 28.0f; } else { const uint32_t kv_bits = 0x7fc00001u + (uint32_t)(i & 0x3ffu); const uint32_t score_bits = 0x7fc00401u + (uint32_t)(i & 0x3ffu); memcpy(state_kv_host + i, &kv_bits, sizeof(kv_bits)); memcpy(state_score_host + i, &score_bits, sizeof(score_bits)); } } } for (uint64_t i = 0; i < comp_count; i++) { const uint32_t bits = 0x7fc00801u + (uint32_t)(i & 0x3ffu); memcpy(ref_comp_host + i, &bits, sizeof(bits)); memcpy(direct_comp_host + i, &bits, sizeof(bits)); } TEST_ASSERT(ds4_gpu_tensor_write(kv, 0, kv_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(sc, 0, sc_host, input_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_comp, 0, ref_comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( direct_comp, 0, direct_comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_state_kv, 0, state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( direct_state_kv, 0, state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( ref_state_score, 0, state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( direct_state_score, 0, state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(model_raw, model_bytes) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(unsetenv(ape_disable_env) == 0); TEST_ASSERT(setenv(direct_disable_env, "1", 1) == 0); TEST_ASSERT(unsetenv(pack_disable_env) == 0); int ref_ok; if (replay) { ref_ok = ds4_gpu_compressor_prefill_ratio4_replay_tensor( ref_comp, ref_state_kv, ref_state_score, kv, sc, model_raw, model_bytes, 0, ape_type, norm_offset, 0, head_dim, pos0, n_tokens, 0, 0, false, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f); } else { ref_ok = ds4_gpu_compressor_prefill_tensor( ref_comp, ref_state_kv, ref_state_score, kv, sc, model_raw, model_bytes, 0, ape_type, norm_offset, 0, head_dim, ratio, pos0, n_tokens, 0, 0, false, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f); } TEST_ASSERT(ref_ok != 0); TEST_ASSERT(ds4_gpu_tensor_read( kv, 0, source_after_host, input_bytes) != 0); TEST_ASSERT(memcmp(kv_host, source_after_host, (size_t)input_bytes) == 0); TEST_ASSERT(ds4_gpu_tensor_read( sc, 0, source_after_host, input_bytes) != 0); TEST_ASSERT(memcmp(sc_host, source_after_host, (size_t)input_bytes) == 0); TEST_ASSERT(unsetenv(direct_disable_env) == 0); TEST_ASSERT(setenv(pack_disable_env, "1", 1) == 0); int direct_ok; if (replay) { direct_ok = ds4_gpu_compressor_prefill_ratio4_replay_tensor( direct_comp, direct_state_kv, direct_state_score, kv, sc, model_raw, model_bytes, 0, ape_type, norm_offset, 0, head_dim, pos0, n_tokens, 0, 0, false, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f); } else { direct_ok = ds4_gpu_compressor_prefill_tensor( direct_comp, direct_state_kv, direct_state_score, kv, sc, model_raw, model_bytes, 0, ape_type, norm_offset, 0, head_dim, ratio, pos0, n_tokens, 0, 0, false, 10000.0f, 1.0f, 0.0f, 1.0f, 32.0f, 1.0f, 1.0e-6f); } TEST_ASSERT(direct_ok != 0); TEST_ASSERT(ds4_gpu_tensor_read( kv, 0, source_after_host, input_bytes) != 0); TEST_ASSERT(memcmp(kv_host, source_after_host, (size_t)input_bytes) == 0); TEST_ASSERT(ds4_gpu_tensor_read( sc, 0, source_after_host, input_bytes) != 0); TEST_ASSERT(memcmp(sc_host, source_after_host, (size_t)input_bytes) == 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_comp, 0, ref_comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( direct_comp, 0, direct_comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_state_kv, 0, ref_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( direct_state_kv, 0, direct_state_kv_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_state_score, 0, ref_state_score_host, state_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( direct_state_score, 0, direct_state_score_host, state_bytes) != 0); comp_stats = test_compare_float_bits( ref_comp_host, direct_comp_host, (size_t)comp_count); state_kv_stats = test_compare_float_bits( ref_state_kv_host, direct_state_kv_host, (size_t)state_count); state_score_stats = test_compare_float_bits( ref_state_score_host, direct_state_score_host, (size_t)state_count); } test_restore_env(ape_disable_env, saved_ape_disable); test_restore_env(pack_disable_env, saved_pack_disable); test_restore_env(direct_disable_env, saved_direct_disable); fprintf(stderr, "ds4-test: compressor ratio4 direct pool exact mode=%s " "head=%u pos=%u tokens=%u comp_rows=%u ape=%s " "comp=%zu/%llu state_kv=%zu/%llu state_score=%zu/%llu " "max_ulp=%u/%u/%u\n", replay ? "replay" : "prefill", head_dim, pos0, n_tokens, n_comp, ape_type == 1u ? "f16" : "f32", comp_stats.mismatch_count, (unsigned long long)comp_count, state_kv_stats.mismatch_count, (unsigned long long)state_count, state_score_stats.mismatch_count, (unsigned long long)state_count, comp_stats.max_ulp, state_kv_stats.max_ulp, state_score_stats.max_ulp); TEST_ASSERT(comp_stats.mismatch_count == 0); TEST_ASSERT(state_kv_stats.mismatch_count == 0); TEST_ASSERT(state_score_stats.mismatch_count == 0); free(model_raw); free(direct_state_score_host); free(ref_state_score_host); free(direct_state_kv_host); free(ref_state_kv_host); free(direct_comp_host); free(ref_comp_host); free(state_score_host); free(state_kv_host); free(source_after_host); free(sc_host); free(kv_host); ds4_gpu_tensor_free(direct_state_score); ds4_gpu_tensor_free(direct_state_kv); ds4_gpu_tensor_free(ref_state_score); ds4_gpu_tensor_free(ref_state_kv); ds4_gpu_tensor_free(direct_comp); ds4_gpu_tensor_free(ref_comp); ds4_gpu_tensor_free(sc); ds4_gpu_tensor_free(kv); } static void test_metal_compressor_ratio4_direct_pool_exact(void) { /* n_comp == 1 deliberately stays on the exact GGML reduction path. */ test_metal_compressor_ratio4_direct_pool_exact_case( 512, 0, 4, 1, false, 59); test_metal_compressor_ratio4_direct_pool_exact_case( 512, 1, 16, 0, false, 61); test_metal_compressor_ratio4_direct_pool_exact_case( 128, 3, 14, 1, false, 67); test_metal_compressor_ratio4_direct_pool_exact_case( 512, 2048, 8, 1, true, 71); test_metal_compressor_ratio4_direct_pool_exact_case( 128, 12, 12, 0, true, 73); test_metal_compressor_ratio4_direct_pool_exact_case( 128, 8, 4, 1, true, 79); } static void test_metal_inplace_rope_pair_exact(void) { typedef struct { uint32_t head_dim; uint32_t n_rot; uint32_t n_head; uint32_t n_tok; uint32_t pos0; bool inverse; float ext_factor; } rope_case; static const rope_case cases[] = { { 512, 64, 64, 1, UINT32_MAX, false, 1.0f }, { 512, 64, 1, 1, 2047, false, 1.0f }, { 512, 64, 64, 1, 65533, true, 1.0f }, { 128, 64, 64, 1, 37, false, 0.0f }, { 512, 64, 4, 32, 0, false, 0.0f }, { 512, 64, 7, 33, 2047, true, 1.0f }, { 128, 64, 64, 34, 65533, false, 1.0f }, { 128, 64, 64, 35, 37, true, 0.0f }, { 128, 64, 4, 35, UINT32_MAX - 16u, true, 1.0f }, }; const char *disable_env = "DS4_METAL_DISABLE_INPLACE_ROPE_PAIR"; const char *shared_disable_env = "DS4_METAL_DISABLE_SHARED_ROPE_COEFF"; const char *affine_disable_env = "DS4_METAL_DISABLE_AFFINE_ROPE_PAIR"; char *saved_disable = test_save_env(disable_env); char *saved_shared_disable = test_save_env(shared_disable_env); char *saved_affine_disable = test_save_env(affine_disable_env); size_t total_pair_mismatch = 0; size_t total_shared_mismatch = 0; size_t total_affine_mismatch = 0; size_t total_pair_prefix_mismatch = 0; size_t total_pair_tail_mismatch = 0; size_t total_shared_prefix_mismatch = 0; size_t total_shared_tail_mismatch = 0; size_t total_affine_prefix_mismatch = 0; size_t total_affine_tail_mismatch = 0; size_t total_elements = 0; for (size_t ci = 0; ci < sizeof(cases) / sizeof(cases[0]); ci++) { const rope_case *c = &cases[ci]; const size_t elements = (size_t)c->n_tok * c->n_head * c->head_dim; const uint64_t bytes = (uint64_t)elements * sizeof(float); const uint32_t n_nope = c->head_dim - c->n_rot; const float freq_base = c->ext_factor != 0.0f ? 160000.0f : 10000.0f; const float freq_scale = c->ext_factor != 0.0f ? 1.0f / 16.0f : 1.0f; const uint32_t n_ctx_orig = c->ext_factor != 0.0f ? 65536u : 0u; float attn_factor = 1.0f; if (c->ext_factor != 0.0f) { attn_factor /= 1.0f + 0.1f * logf(1.0f / freq_scale); } ds4_gpu_tensor *reference = ds4_gpu_tensor_alloc(bytes); ds4_gpu_tensor *pair_candidate = ds4_gpu_tensor_alloc(bytes); ds4_gpu_tensor *shared_candidate = ds4_gpu_tensor_alloc(bytes); ds4_gpu_tensor *affine_candidate = ds4_gpu_tensor_alloc(bytes); float *input = malloc((size_t)bytes); float *reference_host = malloc((size_t)bytes); float *pair_host = malloc((size_t)bytes); float *shared_host = malloc((size_t)bytes); float *affine_host = malloc((size_t)bytes); TEST_ASSERT(reference != NULL); TEST_ASSERT(pair_candidate != NULL); TEST_ASSERT(shared_candidate != NULL); TEST_ASSERT(affine_candidate != NULL); TEST_ASSERT(input != NULL); TEST_ASSERT(reference_host != NULL); TEST_ASSERT(pair_host != NULL); TEST_ASSERT(shared_host != NULL); TEST_ASSERT(affine_host != NULL); const bool allocated = reference && pair_candidate && shared_candidate && affine_candidate && input && reference_host && pair_host && shared_host && affine_host; if (allocated) { for (size_t i = 0; i < elements; i++) { const uint32_t key = (uint32_t)(i * 37u + (i ^ (i >> 5u)) * 11u + ci * 101u); const int value = (int)(key % 4093u) - 2046; input[i] = (float)value / 1024.0f; if ((i + ci * 17u) % 257u == 0u) { const uint32_t negative_zero = 0x80000000u; memcpy(&input[i], &negative_zero, sizeof(negative_zero)); } } TEST_ASSERT(ds4_gpu_tensor_write(reference, 0, input, bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( pair_candidate, 0, input, bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( shared_candidate, 0, input, bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( affine_candidate, 0, input, bytes) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(setenv(affine_disable_env, "1", 1) == 0); TEST_ASSERT(setenv(disable_env, "1", 1) == 0); TEST_ASSERT(setenv(shared_disable_env, "1", 1) == 0); TEST_ASSERT(ds4_gpu_rope_tail_tensor( reference, c->n_tok, c->n_head, c->head_dim, c->n_rot, c->pos0, n_ctx_orig, c->inverse, freq_base, freq_scale, c->ext_factor, attn_factor, 32.0f, 1.0f) != 0); TEST_ASSERT(unsetenv(disable_env) == 0); TEST_ASSERT(ds4_gpu_rope_tail_tensor( pair_candidate, c->n_tok, c->n_head, c->head_dim, c->n_rot, c->pos0, n_ctx_orig, c->inverse, freq_base, freq_scale, c->ext_factor, attn_factor, 32.0f, 1.0f) != 0); TEST_ASSERT(unsetenv(shared_disable_env) == 0); TEST_ASSERT(ds4_gpu_rope_tail_tensor( shared_candidate, c->n_tok, c->n_head, c->head_dim, c->n_rot, c->pos0, n_ctx_orig, c->inverse, freq_base, freq_scale, c->ext_factor, attn_factor, 32.0f, 1.0f) != 0); TEST_ASSERT(setenv(shared_disable_env, "1", 1) == 0); TEST_ASSERT(unsetenv(affine_disable_env) == 0); TEST_ASSERT(ds4_gpu_rope_tail_tensor( affine_candidate, c->n_tok, c->n_head, c->head_dim, c->n_rot, c->pos0, n_ctx_orig, c->inverse, freq_base, freq_scale, c->ext_factor, attn_factor, 32.0f, 1.0f) != 0); TEST_ASSERT(ds4_gpu_tensor_read( reference, 0, reference_host, bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( pair_candidate, 0, pair_host, bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( shared_candidate, 0, shared_host, bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( affine_candidate, 0, affine_host, bytes) != 0); const test_float_compare_stats pair_stats = test_compare_float_bits( reference_host, pair_host, elements); const test_float_compare_stats shared_stats = test_compare_float_bits( pair_host, shared_host, elements); const test_float_compare_stats affine_stats = test_compare_float_bits( pair_host, affine_host, elements); size_t pair_prefix_mismatch = 0; size_t pair_tail_mismatch = 0; size_t shared_prefix_mismatch = 0; size_t shared_tail_mismatch = 0; size_t affine_prefix_mismatch = 0; size_t affine_tail_mismatch = 0; for (uint32_t t = 0; t < c->n_tok; t++) { for (uint32_t h = 0; h < c->n_head; h++) { const size_t row = ((size_t)t * c->n_head + h) * c->head_dim; for (uint32_t d = 0; d < n_nope; d++) { if (memcmp(&input[row + d], &pair_host[row + d], sizeof(float)) != 0) { pair_prefix_mismatch++; } if (memcmp(&input[row + d], &shared_host[row + d], sizeof(float)) != 0) { shared_prefix_mismatch++; } if (memcmp(&input[row + d], &affine_host[row + d], sizeof(float)) != 0) { affine_prefix_mismatch++; } } for (uint32_t d = n_nope; d < c->head_dim; d++) { if (memcmp(&reference_host[row + d], &pair_host[row + d], sizeof(float)) != 0) { pair_tail_mismatch++; } if (memcmp(&pair_host[row + d], &shared_host[row + d], sizeof(float)) != 0) { shared_tail_mismatch++; } if (memcmp(&pair_host[row + d], &affine_host[row + d], sizeof(float)) != 0) { affine_tail_mismatch++; } } } } fprintf(stderr, "ds4-test: in-place RoPE exactness case=%zu " "shape=%ux%ux%u pos=%u inverse=%d ext=%g " "pair=%zu/%zu shared=%zu/%zu affine=%zu/%zu " "pair_prefix=%zu pair_tail=%zu " "shared_prefix=%zu shared_tail=%zu " "affine_prefix=%zu affine_tail=%zu " "pair_max_ulp=%u shared_max_ulp=%u affine_max_ulp=%u " "pair_max_abs=%g shared_max_abs=%g affine_max_abs=%g\n", ci, c->n_tok, c->n_head, c->head_dim, c->pos0, c->inverse ? 1 : 0, c->ext_factor, pair_stats.mismatch_count, elements, shared_stats.mismatch_count, elements, affine_stats.mismatch_count, elements, pair_prefix_mismatch, pair_tail_mismatch, shared_prefix_mismatch, shared_tail_mismatch, affine_prefix_mismatch, affine_tail_mismatch, pair_stats.max_ulp, shared_stats.max_ulp, affine_stats.max_ulp, pair_stats.max_abs, shared_stats.max_abs, affine_stats.max_abs); TEST_ASSERT(pair_stats.mismatch_count == 0); TEST_ASSERT(shared_stats.mismatch_count == 0); TEST_ASSERT(affine_stats.mismatch_count == 0); TEST_ASSERT(pair_prefix_mismatch == 0); TEST_ASSERT(pair_tail_mismatch == 0); TEST_ASSERT(shared_prefix_mismatch == 0); TEST_ASSERT(shared_tail_mismatch == 0); TEST_ASSERT(affine_prefix_mismatch == 0); TEST_ASSERT(affine_tail_mismatch == 0); total_pair_mismatch += pair_stats.mismatch_count; total_shared_mismatch += shared_stats.mismatch_count; total_affine_mismatch += affine_stats.mismatch_count; total_pair_prefix_mismatch += pair_prefix_mismatch; total_pair_tail_mismatch += pair_tail_mismatch; total_shared_prefix_mismatch += shared_prefix_mismatch; total_shared_tail_mismatch += shared_tail_mismatch; total_affine_prefix_mismatch += affine_prefix_mismatch; total_affine_tail_mismatch += affine_tail_mismatch; total_elements += elements; } free(affine_host); free(shared_host); free(pair_host); free(reference_host); free(input); ds4_gpu_tensor_free(affine_candidate); ds4_gpu_tensor_free(shared_candidate); ds4_gpu_tensor_free(pair_candidate); ds4_gpu_tensor_free(reference); } test_restore_env(disable_env, saved_disable); test_restore_env(shared_disable_env, saved_shared_disable); test_restore_env(affine_disable_env, saved_affine_disable); fprintf(stderr, "ds4-test: in-place RoPE total pair=%zu/%zu shared=%zu/%zu " "affine=%zu/%zu " "pair_prefix=%zu pair_tail=%zu " "shared_prefix=%zu shared_tail=%zu " "affine_prefix=%zu affine_tail=%zu\n", total_pair_mismatch, total_elements, total_shared_mismatch, total_elements, total_affine_mismatch, total_elements, total_pair_prefix_mismatch, total_pair_tail_mismatch, total_shared_prefix_mismatch, total_shared_tail_mismatch, total_affine_prefix_mismatch, total_affine_tail_mismatch); TEST_ASSERT(total_pair_mismatch == 0); TEST_ASSERT(total_shared_mismatch == 0); TEST_ASSERT(total_affine_mismatch == 0); TEST_ASSERT(total_pair_prefix_mismatch == 0); TEST_ASSERT(total_pair_tail_mismatch == 0); TEST_ASSERT(total_shared_prefix_mismatch == 0); TEST_ASSERT(total_shared_tail_mismatch == 0); TEST_ASSERT(total_affine_prefix_mismatch == 0); TEST_ASSERT(total_affine_tail_mismatch == 0); } static void test_metal_contiguous_f32_f16_roundtrip_exact(void) { typedef struct { uint32_t n; uint32_t src_offset; uint32_t dst_offset; } copy_case; static const copy_case cases[] = { { 1, 0, 0 }, { 3, 4, 2 }, { 4, 16, 8 }, { 5, 12, 6 }, { 17, 20, 10 }, { 65, 4, 2 }, }; const char *env_name = "DS4_METAL_DISABLE_CONTIG_F32_F16_COPY"; char *saved_env = test_save_env(env_name); size_t half_mismatch = 0; size_t half_guard_mismatch = 0; size_t roundtrip_mismatch = 0; size_t roundtrip_guard_mismatch = 0; size_t half_total = 0; size_t roundtrip_total = 0; for (size_t ci = 0; ci < sizeof(cases) / sizeof(cases[0]); ci++) { const uint32_t n = cases[ci].n; const uint64_t src_bytes = cases[ci].src_offset + (uint64_t)n * sizeof(float) + 16u; const uint64_t half_bytes = cases[ci].dst_offset + (uint64_t)n * sizeof(uint16_t) + 16u; const uint32_t raw_cap = 3; const uint32_t raw_row = 1; const uint64_t raw_bytes = (uint64_t)raw_cap * n * sizeof(float); ds4_gpu_tensor *src_base = ds4_gpu_tensor_alloc(src_bytes); ds4_gpu_tensor *src_view = src_base ? ds4_gpu_tensor_view(src_base, cases[ci].src_offset, (uint64_t)n * sizeof(float)) : NULL; ds4_gpu_tensor *half_ref = ds4_gpu_tensor_alloc(half_bytes); ds4_gpu_tensor *half_vec = ds4_gpu_tensor_alloc(half_bytes); ds4_gpu_tensor *raw_ref = ds4_gpu_tensor_alloc(raw_bytes); ds4_gpu_tensor *raw_vec = ds4_gpu_tensor_alloc(raw_bytes); TEST_ASSERT(src_base != NULL); TEST_ASSERT(src_view != NULL); TEST_ASSERT(half_ref != NULL); TEST_ASSERT(half_vec != NULL); TEST_ASSERT(raw_ref != NULL); TEST_ASSERT(raw_vec != NULL); uint8_t *src_host = malloc((size_t)src_bytes); uint16_t *half_init = malloc((size_t)half_bytes); uint16_t *half_ref_host = malloc((size_t)half_bytes); uint16_t *half_vec_host = malloc((size_t)half_bytes); uint32_t *raw_init = malloc((size_t)raw_bytes); uint32_t *raw_ref_host = malloc((size_t)raw_bytes); uint32_t *raw_vec_host = malloc((size_t)raw_bytes); TEST_ASSERT(src_host != NULL); TEST_ASSERT(half_init != NULL); TEST_ASSERT(half_ref_host != NULL); TEST_ASSERT(half_vec_host != NULL); TEST_ASSERT(raw_init != NULL); TEST_ASSERT(raw_ref_host != NULL); TEST_ASSERT(raw_vec_host != NULL); const bool allocated = src_base && src_view && half_ref && half_vec && raw_ref && raw_vec && src_host && half_init && half_ref_host && half_vec_host && raw_init && raw_ref_host && raw_vec_host; if (allocated) { memset(src_host, 0x6d, (size_t)src_bytes); test_fill_copy_f32_patterns(src_host + cases[ci].src_offset, n, (uint32_t)(ci * 7u)); const size_t half_words = (size_t)(half_bytes / sizeof(uint16_t)); for (size_t i = 0; i < half_words; i++) { half_init[i] = (uint16_t)(0xa55au ^ (uint16_t)(i * 73u)); } const size_t raw_words = (size_t)raw_cap * n; for (size_t i = 0; i < raw_words; i++) { raw_init[i] = 0x4a000000u + (uint32_t)i; } TEST_ASSERT(ds4_gpu_tensor_write(src_base, 0, src_host, src_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(half_ref, 0, half_init, half_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(half_vec, 0, half_init, half_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(raw_ref, 0, raw_init, raw_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(raw_vec, 0, raw_init, raw_bytes) != 0); TEST_ASSERT(setenv(env_name, "1", 1) == 0); TEST_ASSERT(ds4_gpu_tensor_copy_f32_to_f16( half_ref, cases[ci].dst_offset, src_base, cases[ci].src_offset, n) != 0); TEST_ASSERT(ds4_gpu_store_raw_kv_tensor( raw_ref, src_view, raw_cap, raw_row, n) != 0); TEST_ASSERT(setenv(env_name, "0", 1) == 0); TEST_ASSERT(ds4_gpu_tensor_copy_f32_to_f16( half_vec, cases[ci].dst_offset, src_base, cases[ci].src_offset, n) != 0); TEST_ASSERT(ds4_gpu_store_raw_kv_tensor( raw_vec, src_view, raw_cap, raw_row, n) != 0); TEST_ASSERT(ds4_gpu_tensor_read( half_ref, 0, half_ref_host, half_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( half_vec, 0, half_vec_host, half_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( raw_ref, 0, raw_ref_host, raw_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( raw_vec, 0, raw_vec_host, raw_bytes) != 0); const size_t half_first = cases[ci].dst_offset / sizeof(uint16_t); const size_t half_last = half_first + n; for (size_t i = 0; i < half_words; i++) { if (half_ref_host[i] == half_vec_host[i]) continue; if (i >= half_first && i < half_last) { half_mismatch++; } else { half_guard_mismatch++; } } const size_t raw_first = (size_t)raw_row * n; const size_t raw_last = raw_first + n; for (size_t i = 0; i < raw_words; i++) { if (raw_ref_host[i] == raw_vec_host[i]) continue; if (i >= raw_first && i < raw_last) { roundtrip_mismatch++; } else { roundtrip_guard_mismatch++; } } half_total += n; roundtrip_total += n; } free(raw_vec_host); free(raw_ref_host); free(raw_init); free(half_vec_host); free(half_ref_host); free(half_init); free(src_host); ds4_gpu_tensor_free(raw_vec); ds4_gpu_tensor_free(raw_ref); ds4_gpu_tensor_free(half_vec); ds4_gpu_tensor_free(half_ref); ds4_gpu_tensor_free(src_view); ds4_gpu_tensor_free(src_base); } test_restore_env(env_name, saved_env); fprintf(stderr, "ds4-test: contiguous conversion exactness " "f32_f16=%zu/%zu guard=%zu, f16_f32_roundtrip=%zu/%zu guard=%zu\n", half_mismatch, half_total, half_guard_mismatch, roundtrip_mismatch, roundtrip_total, roundtrip_guard_mismatch); TEST_ASSERT(half_mismatch == 0); TEST_ASSERT(half_guard_mismatch == 0); TEST_ASSERT(roundtrip_mismatch == 0); TEST_ASSERT(roundtrip_guard_mismatch == 0); } #endif #if defined(__APPLE__) static void test_metal_gathered_kv_stage_exact(void) { const uint32_t head_dim = 512; const uint32_t raw_cap = 7; const uint32_t n_raw = 5; const uint32_t n_comp = 3; const uint32_t raw_starts[] = {0, 2, 5, 6}; const uint64_t raw_bytes = (uint64_t)raw_cap * head_dim * sizeof(float); const uint64_t comp_bytes = (uint64_t)n_comp * head_dim * sizeof(uint16_t); const uint64_t payload_bytes = ((uint64_t)n_raw + n_comp) * head_dim * sizeof(uint16_t); const uint64_t raw_out_bytes = (uint64_t)n_raw * head_dim * sizeof(uint16_t); const uint64_t raw_view_offset = 4; const uint64_t comp_view_offset = 2; const uint64_t dst_view_offset = 6; const uint64_t raw_base_bytes = raw_view_offset + raw_bytes + 12; const uint64_t comp_base_bytes = comp_view_offset + comp_bytes + 14; const uint64_t dst_base_bytes = dst_view_offset + payload_bytes + 10; const char *envs[] = { "DS4_METAL_REQUIRE_GATHERED_KV_STAGE", "DS4_METAL_DISABLE_CONTIG_F32_F16_COPY", "DS4_METAL_DISABLE_CONTIG_F16_F16_COPY", }; char *saved[sizeof(envs)/sizeof(envs[0])]; for (size_t i = 0; i < sizeof(envs)/sizeof(envs[0]); i++) { saved[i] = test_save_env(envs[i]); } ds4_gpu_tensor *raw_base = ds4_gpu_tensor_alloc(raw_base_bytes); ds4_gpu_tensor *raw = raw_base ? ds4_gpu_tensor_view(raw_base, raw_view_offset, raw_bytes) : NULL; ds4_gpu_tensor *comp_base = ds4_gpu_tensor_alloc(comp_base_bytes); ds4_gpu_tensor *comp = comp_base ? ds4_gpu_tensor_view(comp_base, comp_view_offset, comp_bytes) : NULL; ds4_gpu_tensor *ref_base = ds4_gpu_tensor_alloc(dst_base_bytes); ds4_gpu_tensor *ref = ref_base ? ds4_gpu_tensor_view(ref_base, dst_view_offset, payload_bytes) : NULL; ds4_gpu_tensor *fused_base = ds4_gpu_tensor_alloc(dst_base_bytes); ds4_gpu_tensor *fused = fused_base ? ds4_gpu_tensor_view(fused_base, dst_view_offset, payload_bytes) : NULL; TEST_ASSERT(raw_base != NULL); TEST_ASSERT(raw != NULL); TEST_ASSERT(comp_base != NULL); TEST_ASSERT(comp != NULL); TEST_ASSERT(ref_base != NULL); TEST_ASSERT(ref != NULL); TEST_ASSERT(fused_base != NULL); TEST_ASSERT(fused != NULL); float *raw_host = malloc((size_t)raw_bytes); uint16_t *comp_host = malloc((size_t)comp_bytes); uint8_t *dst_init = malloc((size_t)dst_base_bytes); uint8_t *ref_host = malloc((size_t)dst_base_bytes); uint8_t *fused_host = malloc((size_t)dst_base_bytes); TEST_ASSERT(raw_host != NULL); TEST_ASSERT(comp_host != NULL); TEST_ASSERT(dst_init != NULL); TEST_ASSERT(ref_host != NULL); TEST_ASSERT(fused_host != NULL); static const uint16_t half_patterns[] = { 0x0000u, 0x8000u, 0x0001u, 0x03ffu, 0x0400u, 0x3555u, 0x3c00u, 0x3c01u, 0x7bffu, 0xfbffu, 0x7c00u, 0xfc00u, 0x7e00u, 0x7e01u, 0xfe55u, }; const bool allocated = raw_base && raw && comp_base && comp && ref_base && ref && fused_base && fused && raw_host && comp_host && dst_init && ref_host && fused_host; size_t raw_mismatch = 0; size_t comp_mismatch = 0; size_t guard_mismatch = 0; if (allocated) { for (uint32_t row = 0; row < raw_cap; row++) { test_fill_copy_f32_patterns( raw_host + (uint64_t)row * head_dim, head_dim, row * 17u + 3u); } for (uint64_t i = 0; i < (uint64_t)n_comp * head_dim; i++) { comp_host[i] = half_patterns[(i * 7u + (i >> 3u)) % (sizeof(half_patterns)/sizeof(half_patterns[0]))]; } for (uint64_t i = 0; i < dst_base_bytes; i++) { dst_init[i] = (uint8_t)(0xa5u ^ (uint8_t)(i * 37u)); } TEST_ASSERT(ds4_gpu_tensor_write( raw, 0, raw_host, raw_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( comp, 0, comp_host, comp_bytes) != 0); for (size_t ci = 0; ci < sizeof(raw_starts)/sizeof(raw_starts[0]); ci++) { TEST_ASSERT(ds4_gpu_tensor_write( ref_base, 0, dst_init, dst_base_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( fused_base, 0, dst_init, dst_base_bytes) != 0); TEST_ASSERT(unsetenv(envs[0]) == 0); TEST_ASSERT(unsetenv(envs[1]) == 0); TEST_ASSERT(unsetenv(envs[2]) == 0); ds4_gpu_set_quality(true); TEST_ASSERT(ds4_gpu_flash_kv_stage_f16_tensor( ref, raw, raw_cap, raw_starts[ci], n_raw, comp, 1, n_comp, head_dim) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(setenv(envs[0], "1", 1) == 0); TEST_ASSERT(ds4_gpu_flash_kv_stage_f16_tensor( fused, raw, raw_cap, raw_starts[ci], n_raw, comp, 1, n_comp, head_dim) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_base, 0, ref_host, dst_base_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( fused_base, 0, fused_host, dst_base_bytes) != 0); for (uint64_t i = 0; i < dst_base_bytes; i++) { if (i < dst_view_offset || i >= dst_view_offset + payload_bytes) { if (ref_host[i] != dst_init[i]) guard_mismatch++; if (fused_host[i] != dst_init[i]) guard_mismatch++; } else if (ref_host[i] == fused_host[i]) { continue; } else if (i < dst_view_offset + raw_out_bytes) { raw_mismatch++; } else { comp_mismatch++; } } } /* Component-copy diagnostics and quality mode prevent strict * selection of the gathered kernel. */ TEST_ASSERT(setenv(envs[0], "1", 1) == 0); TEST_ASSERT(setenv(envs[1], "1", 1) == 0); TEST_ASSERT(ds4_gpu_flash_kv_stage_f16_tensor( fused, raw, raw_cap, 5, n_raw, comp, 1, n_comp, head_dim) == 0); TEST_ASSERT(unsetenv(envs[1]) == 0); TEST_ASSERT(setenv(envs[2], "1", 1) == 0); TEST_ASSERT(ds4_gpu_flash_kv_stage_f16_tensor( fused, raw, raw_cap, 5, n_raw, comp, 1, n_comp, head_dim) == 0); TEST_ASSERT(unsetenv(envs[2]) == 0); ds4_gpu_set_quality(true); TEST_ASSERT(ds4_gpu_flash_kv_stage_f16_tensor( fused, raw, raw_cap, 5, n_raw, comp, 1, n_comp, head_dim) == 0); ds4_gpu_set_quality(false); } for (size_t i = 0; i < sizeof(envs)/sizeof(envs[0]); i++) { test_restore_env(envs[i], saved[i]); } fprintf(stderr, "ds4-test: gathered KV staging exact cases=%zu " "raw_bytes=%zu comp_bytes=%zu guard_bytes=%zu\n", sizeof(raw_starts)/sizeof(raw_starts[0]), raw_mismatch, comp_mismatch, guard_mismatch); TEST_ASSERT(raw_mismatch == 0); TEST_ASSERT(comp_mismatch == 0); TEST_ASSERT(guard_mismatch == 0); free(fused_host); free(ref_host); free(dst_init); free(comp_host); free(raw_host); ds4_gpu_tensor_free(fused); ds4_gpu_tensor_free(fused_base); ds4_gpu_tensor_free(ref); ds4_gpu_tensor_free(ref_base); ds4_gpu_tensor_free(comp); ds4_gpu_tensor_free(comp_base); ds4_gpu_tensor_free(raw); ds4_gpu_tensor_free(raw_base); } static void test_metal_contiguous_compressed_f16_attention_exact(void) { const uint32_t head_dim = 512; const uint32_t n_head = 2; const uint32_t raw_cap = 7; const uint32_t n_raw = 5; const uint32_t raw_start = 5; const uint32_t n_comp = 3; const uint64_t raw_bytes = (uint64_t)raw_cap * head_dim * sizeof(float); const uint64_t comp_bytes = (uint64_t)n_comp * head_dim * sizeof(uint16_t); const uint64_t q_bytes = (uint64_t)n_head * head_dim * sizeof(float); const uint64_t page = (uint64_t)getpagesize(); const char *env_name = "DS4_METAL_DISABLE_CONTIG_F16_F16_COPY"; static const uint16_t half_patterns[] = { 0x0000u, 0x8000u, 0x0001u, 0x03ffu, 0x0400u, 0x1001u, 0x3555u, 0x3c00u, 0x3c01u, 0x4000u, 0xbc00u, 0xc000u, 0x7bffu, 0xfbffu, }; ds4_gpu_tensor *raw = ds4_gpu_tensor_alloc(raw_bytes); ds4_gpu_tensor *comp_base = ds4_gpu_tensor_alloc(comp_bytes + 18u); ds4_gpu_tensor *comp = comp_base ? ds4_gpu_tensor_view(comp_base, 2u, comp_bytes) : NULL; ds4_gpu_tensor *q = ds4_gpu_tensor_alloc(q_bytes); ds4_gpu_tensor *heads_blit = ds4_gpu_tensor_alloc(q_bytes); ds4_gpu_tensor *heads_compute = ds4_gpu_tensor_alloc(q_bytes); TEST_ASSERT(raw != NULL); TEST_ASSERT(comp_base != NULL); TEST_ASSERT(comp != NULL); TEST_ASSERT(q != NULL); TEST_ASSERT(heads_blit != NULL); TEST_ASSERT(heads_compute != NULL); float *raw_host = malloc((size_t)raw_bytes); uint16_t *comp_host = malloc((size_t)comp_bytes); float *q_host = malloc((size_t)q_bytes); float *blit_host = malloc((size_t)q_bytes); float *compute_host = malloc((size_t)q_bytes); TEST_ASSERT(raw_host != NULL); TEST_ASSERT(comp_host != NULL); TEST_ASSERT(q_host != NULL); TEST_ASSERT(blit_host != NULL); TEST_ASSERT(compute_host != NULL); void *model_raw = NULL; TEST_ASSERT(posix_memalign(&model_raw, (size_t)page, (size_t)page) == 0); const bool allocated = raw && comp_base && comp && q && heads_blit && heads_compute && raw_host && comp_host && q_host && blit_host && compute_host && model_raw; char *saved_env = test_save_env(env_name); test_float_compare_stats stats = {0}; if (allocated) { memset(model_raw, 0, (size_t)page); float *sinks = model_raw; sinks[0] = -0.375f; sinks[1] = 0.1875f; for (uint64_t i = 0; i < (uint64_t)raw_cap * head_dim; i++) { const int value = (int)((i * 19u + (i ^ (i >> 5u)) * 7u) % 193u) - 96; raw_host[i] = (float)value / 128.0f; } for (uint64_t i = 0; i < (uint64_t)n_comp * head_dim; i++) { comp_host[i] = half_patterns[(i * 5u + (i >> 4u)) % (sizeof(half_patterns) / sizeof(half_patterns[0]))]; } for (uint32_t i = 0; i < n_head * head_dim; i++) { const int value = (int)((i * 37u + (i ^ (i >> 3u)) * 11u) % 251u) - 125; q_host[i] = (float)value / 96.0f; } TEST_ASSERT(ds4_gpu_tensor_write(raw, 0, raw_host, raw_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(comp, 0, comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(q, 0, q_host, q_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(model_raw, page) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(setenv(env_name, "1", 1) == 0); TEST_ASSERT(ds4_gpu_attention_decode_heads_tensor( heads_blit, model_raw, page, 0, q, raw, n_raw, raw_cap, raw_start, comp, 1, n_comp, NULL, 0, n_head, head_dim) != 0); TEST_ASSERT(setenv(env_name, "0", 1) == 0); TEST_ASSERT(ds4_gpu_attention_decode_heads_tensor( heads_compute, model_raw, page, 0, q, raw, n_raw, raw_cap, raw_start, comp, 1, n_comp, NULL, 0, n_head, head_dim) != 0); TEST_ASSERT(ds4_gpu_tensor_read( heads_blit, 0, blit_host, q_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( heads_compute, 0, compute_host, q_bytes) != 0); stats = test_compare_float_bits( blit_host, compute_host, (size_t)n_head * head_dim); } test_restore_env(env_name, saved_env); fprintf(stderr, "ds4-test: contiguous compressed-F16 staging exactness " "mismatches=%zu/%u max_ulp=%u max_abs=%g\n", stats.mismatch_count, n_head * head_dim, stats.max_ulp, stats.max_abs); TEST_ASSERT(stats.mismatch_count == 0); free(model_raw); free(compute_host); free(blit_host); free(q_host); free(comp_host); free(raw_host); ds4_gpu_tensor_free(heads_compute); ds4_gpu_tensor_free(heads_blit); ds4_gpu_tensor_free(q); ds4_gpu_tensor_free(comp); ds4_gpu_tensor_free(comp_base); ds4_gpu_tensor_free(raw); } static void test_metal_persistent_zero_attention_mask_exact_case( uint32_t raw_cap, uint32_t n_raw, uint32_t raw_start, uint32_t n_comp, uint32_t seed) { const uint32_t head_dim = 512; const uint32_t n_head = 2; const uint64_t raw_bytes = (uint64_t)raw_cap * head_dim * sizeof(float); const uint64_t comp_bytes = (uint64_t)n_comp * head_dim * sizeof(uint16_t); const uint64_t q_bytes = (uint64_t)n_head * head_dim * sizeof(float); const uint64_t mask_bytes = (uint64_t)n_comp * sizeof(float); const uint64_t page = (uint64_t)getpagesize(); ds4_gpu_tensor *raw = ds4_gpu_tensor_alloc(raw_bytes); ds4_gpu_tensor *comp = ds4_gpu_tensor_alloc(comp_bytes); ds4_gpu_tensor *q = ds4_gpu_tensor_alloc(q_bytes); ds4_gpu_tensor *comp_mask = ds4_gpu_tensor_alloc(mask_bytes); ds4_gpu_tensor *legacy = ds4_gpu_tensor_alloc(q_bytes); ds4_gpu_tensor *persistent = ds4_gpu_tensor_alloc(q_bytes); ds4_gpu_tensor *masked = ds4_gpu_tensor_alloc(q_bytes); ds4_gpu_tensor *pad_legacy = ds4_gpu_tensor_alloc(q_bytes); ds4_gpu_tensor *after_mask = ds4_gpu_tensor_alloc(q_bytes); TEST_ASSERT(raw != NULL); TEST_ASSERT(comp != NULL); TEST_ASSERT(q != NULL); TEST_ASSERT(comp_mask != NULL); TEST_ASSERT(legacy != NULL); TEST_ASSERT(persistent != NULL); TEST_ASSERT(masked != NULL); TEST_ASSERT(pad_legacy != NULL); TEST_ASSERT(after_mask != NULL); float *raw_host = malloc((size_t)raw_bytes); uint16_t *comp_host = malloc((size_t)comp_bytes); float *q_host = malloc((size_t)q_bytes); float *mask_host = malloc((size_t)mask_bytes); float *legacy_host = malloc((size_t)q_bytes); float *persistent_host = malloc((size_t)q_bytes); float *masked_host = malloc((size_t)q_bytes); float *pad_legacy_host = malloc((size_t)q_bytes); float *after_mask_host = malloc((size_t)q_bytes); TEST_ASSERT(raw_host != NULL); TEST_ASSERT(comp_host != NULL); TEST_ASSERT(q_host != NULL); TEST_ASSERT(mask_host != NULL); TEST_ASSERT(legacy_host != NULL); TEST_ASSERT(persistent_host != NULL); TEST_ASSERT(masked_host != NULL); TEST_ASSERT(pad_legacy_host != NULL); TEST_ASSERT(after_mask_host != NULL); void *model_raw = NULL; TEST_ASSERT(posix_memalign(&model_raw, (size_t)page, (size_t)page) == 0); const bool allocated = raw && comp && q && comp_mask && legacy && persistent && masked && pad_legacy && after_mask && raw_host && comp_host && q_host && mask_host && legacy_host && persistent_host && masked_host && pad_legacy_host && after_mask_host && model_raw; const char *disable_env = "DS4_METAL_DISABLE_PERSISTENT_ZERO_ATTN_MASK"; const char *pad_disable_env = "DS4_METAL_DISABLE_GATHERED_KV_PAD_FUSION"; const char *shared_pad_disable_env = "DS4_METAL_DISABLE_SHARED_KV_PAD"; char *saved_disable = test_save_env(disable_env); char *saved_pad_disable = test_save_env(pad_disable_env); char *saved_shared_pad_disable = test_save_env(shared_pad_disable_env); test_float_compare_stats persistent_stats = {0}; test_float_compare_stats masked_stats = {0}; test_float_compare_stats pad_stats = {0}; test_float_compare_stats after_mask_stats = {0}; if (allocated) { memset(model_raw, 0, (size_t)page); float *sinks = model_raw; sinks[0] = -0.3125f; sinks[1] = 0.21875f; for (uint64_t i = 0; i < (uint64_t)raw_cap * head_dim; i++) { const int value = (int)((i * 17u + (i ^ (i >> 5u)) * 11u + seed * 13u) % 211u) - 105; raw_host[i] = (float)value / 128.0f; } for (uint64_t i = 0; i < (uint64_t)n_comp * head_dim; i++) { const int value = (int)((i * 23u + (i ^ (i >> 4u)) * 7u + seed * 19u) % 193u) - 96; comp_host[i] = test_float_to_f16((float)value / 112.0f); } for (uint32_t i = 0; i < n_head * head_dim; i++) { const int value = (int)((i * 31u + (i ^ (i >> 3u)) * 5u + seed * 29u) % 227u) - 113; q_host[i] = (float)value / 104.0f; } for (uint32_t i = 0; i < n_comp; i++) { mask_host[i] = i == 0 ? -8.0f : -(float)(i + 1u) / 8.0f; } TEST_ASSERT(ds4_gpu_tensor_write(raw, 0, raw_host, raw_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(comp, 0, comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(q, 0, q_host, q_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( comp_mask, 0, mask_host, mask_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(model_raw, page) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(setenv(disable_env, "1", 1) == 0); TEST_ASSERT(ds4_gpu_attention_decode_heads_tensor( legacy, model_raw, page, 0, q, raw, n_raw, raw_cap, raw_start, comp, 1, n_comp, NULL, 0, n_head, head_dim) != 0); unsetenv(disable_env); unsetenv(pad_disable_env); unsetenv(shared_pad_disable_env); TEST_ASSERT(ds4_gpu_attention_decode_heads_tensor( persistent, model_raw, page, 0, q, raw, n_raw, raw_cap, raw_start, comp, 1, n_comp, NULL, 0, n_head, head_dim) != 0); TEST_ASSERT(ds4_gpu_attention_decode_heads_tensor( masked, model_raw, page, 0, q, raw, n_raw, raw_cap, raw_start, comp, 1, n_comp, comp_mask, 1, n_head, head_dim) != 0); TEST_ASSERT(setenv(pad_disable_env, "1", 1) == 0); TEST_ASSERT(setenv(shared_pad_disable_env, "1", 1) == 0); TEST_ASSERT(ds4_gpu_attention_decode_heads_tensor( pad_legacy, model_raw, page, 0, q, raw, n_raw, raw_cap, raw_start, comp, 1, n_comp, comp_mask, 1, n_head, head_dim) != 0); unsetenv(pad_disable_env); unsetenv(shared_pad_disable_env); TEST_ASSERT(ds4_gpu_attention_decode_heads_tensor( after_mask, model_raw, page, 0, q, raw, n_raw, raw_cap, raw_start, comp, 1, n_comp, NULL, 0, n_head, head_dim) != 0); TEST_ASSERT(ds4_gpu_tensor_read( legacy, 0, legacy_host, q_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( persistent, 0, persistent_host, q_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( masked, 0, masked_host, q_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( pad_legacy, 0, pad_legacy_host, q_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( after_mask, 0, after_mask_host, q_bytes) != 0); persistent_stats = test_compare_float_bits( legacy_host, persistent_host, (size_t)n_head * head_dim); masked_stats = test_compare_float_bits( legacy_host, masked_host, (size_t)n_head * head_dim); pad_stats = test_compare_float_bits( pad_legacy_host, masked_host, (size_t)n_head * head_dim); after_mask_stats = test_compare_float_bits( legacy_host, after_mask_host, (size_t)n_head * head_dim); } test_restore_env(disable_env, saved_disable); test_restore_env(pad_disable_env, saved_pad_disable); test_restore_env(shared_pad_disable_env, saved_shared_pad_disable); fprintf(stderr, "ds4-test: persistent zero attention mask exact keys=%u " "candidate=%zu/%u max_ulp=%u masked_diff=%zu/%u " "pad_fusion=%zu/%u max_ulp=%u " "after_mask=%zu/%u max_ulp=%u\n", n_raw + n_comp, persistent_stats.mismatch_count, n_head * head_dim, persistent_stats.max_ulp, masked_stats.mismatch_count, n_head * head_dim, pad_stats.mismatch_count, n_head * head_dim, pad_stats.max_ulp, after_mask_stats.mismatch_count, n_head * head_dim, after_mask_stats.max_ulp); TEST_ASSERT(persistent_stats.mismatch_count == 0); TEST_ASSERT(masked_stats.mismatch_count != 0); TEST_ASSERT(pad_stats.mismatch_count == 0); TEST_ASSERT(after_mask_stats.mismatch_count == 0); free(model_raw); free(after_mask_host); free(pad_legacy_host); free(masked_host); free(persistent_host); free(legacy_host); free(mask_host); free(q_host); free(comp_host); free(raw_host); ds4_gpu_tensor_free(after_mask); ds4_gpu_tensor_free(pad_legacy); ds4_gpu_tensor_free(masked); ds4_gpu_tensor_free(persistent); ds4_gpu_tensor_free(legacy); ds4_gpu_tensor_free(comp_mask); ds4_gpu_tensor_free(q); ds4_gpu_tensor_free(comp); ds4_gpu_tensor_free(raw); } static void test_metal_persistent_zero_attention_mask_exact(void) { test_metal_persistent_zero_attention_mask_exact_case(7, 5, 5, 3, 11); test_metal_persistent_zero_attention_mask_exact_case(37, 29, 35, 3, 23); } typedef enum { TEST_METAL_PREFILL_MASK_CACHE_RAW = 1, TEST_METAL_PREFILL_MASK_CACHE_RATIO4 = 2, TEST_METAL_PREFILL_MASK_CACHE_RATIO128 = 3, } test_metal_prefill_mask_cache_kind; typedef struct { uint32_t n_tokens; uint32_t n_comp; uint32_t window; uint32_t ratio; } test_metal_prefill_mask_cache_shape; static int test_metal_zero_prefix_prefill_mask_cache_call( test_metal_prefill_mask_cache_kind kind, ds4_gpu_tensor *heads, const void *model_map, uint64_t model_size, const ds4_gpu_tensor *q, const ds4_gpu_tensor *raw, const ds4_gpu_tensor *comp, const ds4_gpu_tensor *comp_mask, const test_metal_prefill_mask_cache_shape *shape, bool masked, uint32_t n_head, uint32_t head_dim) { if (kind == TEST_METAL_PREFILL_MASK_CACHE_RAW) { if (masked) return 0; return ds4_gpu_attention_prefill_raw_heads_tensor( heads, model_map, model_size, 0, q, raw, shape->n_tokens, shape->window, n_head, head_dim); } if (masked) { return ds4_gpu_attention_prefill_masked_mixed_heads_tensor( heads, model_map, model_size, 0, q, raw, comp, 1, comp_mask, shape->n_tokens, shape->n_comp, shape->window, shape->ratio, n_head, head_dim); } return ds4_gpu_attention_prefill_static_mixed_heads_tensor( heads, model_map, model_size, 0, q, raw, comp, 1, shape->n_tokens, shape->n_comp, shape->window, shape->ratio, n_head, head_dim); } static bool test_metal_zero_prefix_prefill_mask_cache_run( test_metal_prefill_mask_cache_kind kind, ds4_gpu_tensor *heads, const void *model_map, uint64_t model_size, const ds4_gpu_tensor *q, const ds4_gpu_tensor *raw, const ds4_gpu_tensor *comp, const ds4_gpu_tensor *comp_mask, const test_metal_prefill_mask_cache_shape *shape, bool masked, uint32_t n_head, uint32_t head_dim, float *host) { const uint64_t bytes = (uint64_t)shape->n_tokens * n_head * head_dim * sizeof(float); const int call_ok = test_metal_zero_prefix_prefill_mask_cache_call( kind, heads, model_map, model_size, q, raw, comp, comp_mask, shape, masked, n_head, head_dim); TEST_ASSERT(call_ok != 0); if (!call_ok) return false; const int read_ok = ds4_gpu_tensor_read(heads, 0, host, bytes); TEST_ASSERT(read_ok != 0); return read_ok != 0; } static void test_metal_zero_prefix_prefill_mask_cache_compare( const float *expected, const float *actual, size_t count, size_t *total_mismatches, uint32_t *max_ulp) { const test_float_compare_stats stats = test_compare_float_bits(expected, actual, count); *total_mismatches += stats.mismatch_count; if (stats.max_ulp > *max_ulp) *max_ulp = stats.max_ulp; } static void test_metal_zero_prefix_prefill_mask_cache_exact_kind( test_metal_prefill_mask_cache_kind kind, uint32_t seed) { const uint32_t head_dim = 512; const uint32_t n_head = 1; const uint32_t max_tokens = 129; const uint32_t max_comp = 32; const uint64_t raw_count = (uint64_t)max_tokens * head_dim; const uint64_t comp_count = (uint64_t)max_comp * head_dim; const uint64_t q_count = (uint64_t)max_tokens * n_head * head_dim; const uint64_t mask_count = (uint64_t)max_tokens * max_comp; const uint64_t raw_bytes = raw_count * sizeof(float); const uint64_t comp_bytes = comp_count * sizeof(uint16_t); const uint64_t q_bytes = q_count * sizeof(float); const uint64_t mask_bytes = mask_count * sizeof(float); const uint64_t page = (uint64_t)getpagesize(); const test_metal_prefill_mask_cache_shape shape_a = { .n_tokens = 128, .n_comp = kind == TEST_METAL_PREFILL_MASK_CACHE_RAW ? 0u : (kind == TEST_METAL_PREFILL_MASK_CACHE_RATIO4 ? 32u : 1u), .window = 128, .ratio = kind == TEST_METAL_PREFILL_MASK_CACHE_RATIO4 ? 4u : (kind == TEST_METAL_PREFILL_MASK_CACHE_RATIO128 ? 128u : 0u), }; const test_metal_prefill_mask_cache_shape shape_b = { .n_tokens = 129, .n_comp = kind == TEST_METAL_PREFILL_MASK_CACHE_RAW ? 0u : (kind == TEST_METAL_PREFILL_MASK_CACHE_RATIO4 ? 31u : 2u), .window = 63, .ratio = shape_a.ratio, }; const size_t count_a = (size_t)shape_a.n_tokens * n_head * head_dim; const size_t count_b = (size_t)shape_b.n_tokens * n_head * head_dim; ds4_gpu_tensor *raw = ds4_gpu_tensor_alloc(raw_bytes); ds4_gpu_tensor *comp = ds4_gpu_tensor_alloc(comp_bytes); ds4_gpu_tensor *q = ds4_gpu_tensor_alloc(q_bytes); ds4_gpu_tensor *comp_mask = ds4_gpu_tensor_alloc(mask_bytes); ds4_gpu_tensor *heads = ds4_gpu_tensor_alloc(q_bytes); float *raw_host = malloc((size_t)raw_bytes); uint16_t *comp_host = malloc((size_t)comp_bytes); float *q_host = calloc((size_t)q_count, sizeof(float)); float *mask_host = malloc((size_t)mask_bytes); float *ref_a = malloc((size_t)q_bytes); float *ref_b = malloc((size_t)q_bytes); float *actual = malloc((size_t)q_bytes); float *masked_actual = malloc((size_t)q_bytes); void *model_raw = NULL; TEST_ASSERT(posix_memalign(&model_raw, (size_t)page, (size_t)page) == 0); TEST_ASSERT(raw != NULL); TEST_ASSERT(comp != NULL); TEST_ASSERT(q != NULL); TEST_ASSERT(comp_mask != NULL); TEST_ASSERT(heads != NULL); TEST_ASSERT(raw_host != NULL); TEST_ASSERT(comp_host != NULL); TEST_ASSERT(q_host != NULL); TEST_ASSERT(mask_host != NULL); TEST_ASSERT(ref_a != NULL); TEST_ASSERT(ref_b != NULL); TEST_ASSERT(actual != NULL); TEST_ASSERT(masked_actual != NULL); TEST_ASSERT(model_raw != NULL); const char *disable_env = "DS4_METAL_DISABLE_ZERO_PREFIX_PREFILL_MASK_CACHE"; char *saved_disable = test_save_env(disable_env); size_t total_mismatches = 0; uint32_t max_ulp = 0; size_t key_difference = 0; size_t masked_difference = 0; const bool allocated = raw && comp && q && comp_mask && heads && raw_host && comp_host && q_host && mask_host && ref_a && ref_b && actual && masked_actual && model_raw; if (allocated) { memset(model_raw, 0, (size_t)page); ((float *)model_raw)[0] = -1.0f; for (uint32_t row = 0; row < max_tokens; row++) { for (uint32_t col = 0; col < head_dim; col++) { const int value = (int)((row * 37u + col * 17u + (col ^ (col >> 3u)) * 5u + seed * 13u) % 257u) - 128; raw_host[(uint64_t)row * head_dim + col] = (float)value / 256.0f; } } for (uint32_t row = 0; row < max_comp; row++) { for (uint32_t col = 0; col < head_dim; col++) { const int value = (int)((row * 29u + col * 11u + (col ^ (col >> 4u)) * 7u + seed * 19u) % 193u) - 96; comp_host[(uint64_t)row * head_dim + col] = test_float_to_f16(0.375f + (float)value / 384.0f); } } for (uint64_t i = 0; i < mask_count; i++) { mask_host[i] = -65504.0f; } if (shape_a.n_comp != 0) { for (uint32_t row = 0; row < shape_a.n_tokens; row++) { const uint32_t visible = (row + 1u) / shape_a.ratio; for (uint32_t col = 0; col < shape_a.n_comp; col++) { if (col < visible) { mask_host[(uint64_t)row * shape_a.n_comp + col] = (col & 1u) != 0u ? -2.0f : -65504.0f; } } } } TEST_ASSERT(ds4_gpu_tensor_write(raw, 0, raw_host, raw_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(comp, 0, comp_host, comp_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(q, 0, q_host, q_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( comp_mask, 0, mask_host, mask_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(model_raw, page) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(setenv(disable_env, "1", 1) == 0); const bool have_ref_a = test_metal_zero_prefix_prefill_mask_cache_run( kind, heads, model_raw, page, q, raw, comp, comp_mask, &shape_a, false, n_head, head_dim, ref_a); const bool have_ref_b = test_metal_zero_prefix_prefill_mask_cache_run( kind, heads, model_raw, page, q, raw, comp, comp_mask, &shape_b, false, n_head, head_dim, ref_b); if (have_ref_a && have_ref_b) { const test_float_compare_stats key_stats = test_compare_float_bits(ref_a, ref_b, count_a); key_difference = key_stats.mismatch_count; TEST_ASSERT(key_difference != 0); } TEST_ASSERT(unsetenv(disable_env) == 0); if (test_metal_zero_prefix_prefill_mask_cache_run( kind, heads, model_raw, page, q, raw, comp, comp_mask, &shape_a, false, n_head, head_dim, actual) && have_ref_a) { test_metal_zero_prefix_prefill_mask_cache_compare( ref_a, actual, count_a, &total_mismatches, &max_ulp); } if (test_metal_zero_prefix_prefill_mask_cache_run( kind, heads, model_raw, page, q, raw, comp, comp_mask, &shape_a, false, n_head, head_dim, actual) && have_ref_a) { test_metal_zero_prefix_prefill_mask_cache_compare( ref_a, actual, count_a, &total_mismatches, &max_ulp); } if (kind != TEST_METAL_PREFILL_MASK_CACHE_RAW) { if (test_metal_zero_prefix_prefill_mask_cache_run( kind, heads, model_raw, page, q, raw, comp, comp_mask, &shape_a, true, n_head, head_dim, masked_actual) && have_ref_a) { const test_float_compare_stats masked_stats = test_compare_float_bits(ref_a, masked_actual, count_a); masked_difference = masked_stats.mismatch_count; TEST_ASSERT(masked_difference != 0); } if (test_metal_zero_prefix_prefill_mask_cache_run( kind, heads, model_raw, page, q, raw, comp, comp_mask, &shape_a, false, n_head, head_dim, actual) && have_ref_a) { test_metal_zero_prefix_prefill_mask_cache_compare( ref_a, actual, count_a, &total_mismatches, &max_ulp); } } if (test_metal_zero_prefix_prefill_mask_cache_run( kind, heads, model_raw, page, q, raw, comp, comp_mask, &shape_b, false, n_head, head_dim, actual) && have_ref_b) { test_metal_zero_prefix_prefill_mask_cache_compare( ref_b, actual, count_b, &total_mismatches, &max_ulp); } if (test_metal_zero_prefix_prefill_mask_cache_run( kind, heads, model_raw, page, q, raw, comp, comp_mask, &shape_a, false, n_head, head_dim, actual) && have_ref_a) { test_metal_zero_prefix_prefill_mask_cache_compare( ref_a, actual, count_a, &total_mismatches, &max_ulp); } } test_restore_env(disable_env, saved_disable); const char *kind_name = kind == TEST_METAL_PREFILL_MASK_CACHE_RAW ? "raw" : (kind == TEST_METAL_PREFILL_MASK_CACHE_RATIO4 ? "ratio4" : "ratio128"); fprintf(stderr, "ds4-test: zero-prefix prefill mask cache %s exact " "mismatches=%zu max_ulp=%u key_diff=%zu masked_diff=%zu\n", kind_name, total_mismatches, max_ulp, key_difference, masked_difference); TEST_ASSERT(total_mismatches == 0); TEST_ASSERT(max_ulp == 0); free(model_raw); free(masked_actual); free(actual); free(ref_b); free(ref_a); free(mask_host); free(q_host); free(comp_host); free(raw_host); ds4_gpu_tensor_free(heads); ds4_gpu_tensor_free(comp_mask); ds4_gpu_tensor_free(q); ds4_gpu_tensor_free(comp); ds4_gpu_tensor_free(raw); } static void test_metal_zero_prefix_prefill_mask_cache_exact(void) { test_metal_zero_prefix_prefill_mask_cache_exact_kind( TEST_METAL_PREFILL_MASK_CACHE_RAW, 41); test_metal_zero_prefix_prefill_mask_cache_exact_kind( TEST_METAL_PREFILL_MASK_CACHE_RATIO4, 43); test_metal_zero_prefix_prefill_mask_cache_exact_kind( TEST_METAL_PREFILL_MASK_CACHE_RATIO128, 47); } #endif #if defined(__APPLE__) static void test_metal_hc_split_weighted_sum_norm_batch_exact(void) { /* Compare the batched HC+RMSNorm fusion against the exact two-dispatch * sequence used by the reference path at DS4's production dimensions. */ const uint32_t n_embd = 7168; const uint32_t n_hc = 4; const uint32_t n_rows = 3; const uint32_t sinkhorn_iters = 20; const float hc_eps = 1.0e-6f; const float norm_eps = 1.0e-6f; const uint64_t mix_hc = 2ull * n_hc + (uint64_t)n_hc * n_hc; const uint64_t page = (uint64_t)getpagesize(); const uint64_t scale_offset = 0; const uint64_t base_offset = test_round_up_u64(3u * sizeof(float), page); const uint64_t norm_weight_offset = test_round_up_u64(base_offset + mix_hc * sizeof(float), page); const uint64_t model_alloc = test_round_up_u64( norm_weight_offset + (uint64_t)n_embd * sizeof(float), page); const uint64_t mix_bytes = (uint64_t)n_rows * mix_hc * sizeof(float); const uint64_t residual_bytes = (uint64_t)n_rows * n_hc * n_embd * sizeof(float); const uint64_t out_bytes = (uint64_t)n_rows * n_embd * sizeof(float); void *model_raw = NULL; TEST_ASSERT(posix_memalign(&model_raw, (size_t)page, (size_t)model_alloc) == 0); if (!model_raw) return; memset(model_raw, 0, (size_t)model_alloc); float *scale = (float *)((uint8_t *)model_raw + scale_offset); float *base = (float *)((uint8_t *)model_raw + base_offset); float *norm_weight = (float *)((uint8_t *)model_raw + norm_weight_offset); scale[0] = 0.625f; scale[1] = -0.75f; scale[2] = 0.4375f; for (uint32_t i = 0; i < mix_hc; i++) { const int value = (int)((i * 17u + 5u) % 29u) - 14; base[i] = (float)value / 16.0f; } for (uint32_t i = 0; i < n_embd; i++) { norm_weight[i] = 0.5f + (float)((i * 13u + 7u) % 31u) / 32.0f; } ds4_gpu_tensor *mix = ds4_gpu_tensor_alloc(mix_bytes); ds4_gpu_tensor *residual = ds4_gpu_tensor_alloc(residual_bytes); ds4_gpu_tensor *ref_split = ds4_gpu_tensor_alloc(mix_bytes); ds4_gpu_tensor *fused_split = ds4_gpu_tensor_alloc(mix_bytes); ds4_gpu_tensor *ref_out = ds4_gpu_tensor_alloc(out_bytes); ds4_gpu_tensor *fused_out = ds4_gpu_tensor_alloc(out_bytes); ds4_gpu_tensor *ref_norm = ds4_gpu_tensor_alloc(out_bytes); ds4_gpu_tensor *fused_norm = ds4_gpu_tensor_alloc(out_bytes); TEST_ASSERT(mix != NULL); TEST_ASSERT(residual != NULL); TEST_ASSERT(ref_split != NULL); TEST_ASSERT(fused_split != NULL); TEST_ASSERT(ref_out != NULL); TEST_ASSERT(fused_out != NULL); TEST_ASSERT(ref_norm != NULL); TEST_ASSERT(fused_norm != NULL); if (!mix || !residual || !ref_split || !fused_split || !ref_out || !fused_out || !ref_norm || !fused_norm) { ds4_gpu_tensor_free(mix); ds4_gpu_tensor_free(residual); ds4_gpu_tensor_free(ref_split); ds4_gpu_tensor_free(fused_split); ds4_gpu_tensor_free(ref_out); ds4_gpu_tensor_free(fused_out); ds4_gpu_tensor_free(ref_norm); ds4_gpu_tensor_free(fused_norm); free(model_raw); return; } float *mix_host = malloc((size_t)mix_bytes); float *residual_host = malloc((size_t)residual_bytes); float *ref_split_host = malloc((size_t)mix_bytes); float *fused_split_host = malloc((size_t)mix_bytes); float *ref_out_host = malloc((size_t)out_bytes); float *fused_out_host = malloc((size_t)out_bytes); float *ref_norm_host = malloc((size_t)out_bytes); float *fused_norm_host = malloc((size_t)out_bytes); TEST_ASSERT(mix_host != NULL); TEST_ASSERT(residual_host != NULL); TEST_ASSERT(ref_split_host != NULL); TEST_ASSERT(fused_split_host != NULL); TEST_ASSERT(ref_out_host != NULL); TEST_ASSERT(fused_out_host != NULL); TEST_ASSERT(ref_norm_host != NULL); TEST_ASSERT(fused_norm_host != NULL); if (!mix_host || !residual_host || !ref_split_host || !fused_split_host || !ref_out_host || !fused_out_host || !ref_norm_host || !fused_norm_host) { free(mix_host); free(residual_host); free(ref_split_host); free(fused_split_host); free(ref_out_host); free(fused_out_host); free(ref_norm_host); free(fused_norm_host); ds4_gpu_tensor_free(mix); ds4_gpu_tensor_free(residual); ds4_gpu_tensor_free(ref_split); ds4_gpu_tensor_free(fused_split); ds4_gpu_tensor_free(ref_out); ds4_gpu_tensor_free(fused_out); ds4_gpu_tensor_free(ref_norm); ds4_gpu_tensor_free(fused_norm); free(model_raw); return; } for (uint32_t row = 0; row < n_rows; row++) { for (uint32_t i = 0; i < mix_hc; i++) { const int value = (int)(((row + 1u) * 19u + i * 11u + (i ^ row) * 3u) % 47u) - 23; mix_host[(uint64_t)row * mix_hc + i] = (float)value / 9.0f; } for (uint32_t hc = 0; hc < n_hc; hc++) { for (uint32_t d = 0; d < n_embd; d++) { const uint32_t key = d * 37u + hc * 173u + row * 997u + ((d >> 3u) ^ (d * 7u)); const int value = (int)(key % 2047u) - 1023; residual_host[((uint64_t)row * n_hc + hc) * n_embd + d] = (float)value / 512.0f; } } } TEST_ASSERT(ds4_gpu_tensor_write(mix, 0, mix_host, mix_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write(residual, 0, residual_host, residual_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(model_raw, model_alloc) != 0); TEST_ASSERT(ds4_gpu_hc_split_weighted_sum_tensor( ref_out, ref_split, mix, residual, model_raw, model_alloc, scale_offset, base_offset, n_embd, n_hc, sinkhorn_iters, hc_eps) != 0); TEST_ASSERT(ds4_gpu_rms_norm_weight_rows_tensor( ref_norm, ref_out, model_raw, model_alloc, norm_weight_offset, n_embd, n_rows, norm_eps) != 0); TEST_ASSERT(ds4_gpu_hc_split_weighted_sum_norm_tensor( fused_out, fused_norm, fused_split, mix, residual, model_raw, model_alloc, scale_offset, base_offset, norm_weight_offset, n_embd, n_hc, sinkhorn_iters, hc_eps, norm_eps) != 0); TEST_ASSERT(ds4_gpu_tensor_read(ref_split, 0, ref_split_host, mix_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read(fused_split, 0, fused_split_host, mix_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read(ref_out, 0, ref_out_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read(fused_out, 0, fused_out_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read(ref_norm, 0, ref_norm_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read(fused_norm, 0, fused_norm_host, out_bytes) != 0); const test_float_compare_stats split_stats = test_compare_float_bits( ref_split_host, fused_split_host, (size_t)(n_rows * mix_hc)); const test_float_compare_stats out_stats = test_compare_float_bits( ref_out_host, fused_out_host, (size_t)n_rows * n_embd); const test_float_compare_stats norm_stats = test_compare_float_bits( ref_norm_host, fused_norm_host, (size_t)n_rows * n_embd); fprintf(stderr, "ds4-test: batch HC+RMSNorm exactness rows=%u " "split=%zu/%llu max_ulp=%u max_abs=%g, " "collapse=%zu/%llu max_ulp=%u max_abs=%g, " "norm=%zu/%llu max_ulp=%u max_abs=%g\n", n_rows, split_stats.mismatch_count, (unsigned long long)(n_rows * mix_hc), split_stats.max_ulp, split_stats.max_abs, out_stats.mismatch_count, (unsigned long long)((uint64_t)n_rows * n_embd), out_stats.max_ulp, out_stats.max_abs, norm_stats.mismatch_count, (unsigned long long)((uint64_t)n_rows * n_embd), norm_stats.max_ulp, norm_stats.max_abs); TEST_ASSERT(split_stats.mismatch_count == 0); TEST_ASSERT(out_stats.mismatch_count == 0); TEST_ASSERT(norm_stats.mismatch_count == 0); free(mix_host); free(residual_host); free(ref_split_host); free(fused_split_host); free(ref_out_host); free(fused_out_host); free(ref_norm_host); free(fused_norm_host); ds4_gpu_tensor_free(mix); ds4_gpu_tensor_free(residual); ds4_gpu_tensor_free(ref_split); ds4_gpu_tensor_free(fused_split); ds4_gpu_tensor_free(ref_out); ds4_gpu_tensor_free(fused_out); ds4_gpu_tensor_free(ref_norm); ds4_gpu_tensor_free(fused_norm); free(model_raw); } static void test_metal_output_hc_weights4_exact(void) { const uint32_t n_hc = 4; const float eps = 1.0e-6f; const uint64_t page = (uint64_t)getpagesize(); const uint64_t scale_offset = 0; const uint64_t base_offset = page; const uint64_t model_alloc = 2u * page; const uint64_t bytes = n_hc * sizeof(float); const char *require_env = "DS4_METAL_REQUIRE_OUTPUT_HC_WEIGHTS4"; char *saved_require = test_save_env(require_env); void *model_raw = NULL; TEST_ASSERT(posix_memalign( &model_raw, (size_t)page, (size_t)model_alloc) == 0); ds4_gpu_tensor *pre = ds4_gpu_tensor_alloc(bytes); ds4_gpu_tensor *reference = ds4_gpu_tensor_alloc(bytes); ds4_gpu_tensor *candidate = ds4_gpu_tensor_alloc(bytes); TEST_ASSERT(model_raw != NULL); TEST_ASSERT(pre != NULL); TEST_ASSERT(reference != NULL); TEST_ASSERT(candidate != NULL); size_t total_mismatch = 0; uint32_t max_ulp = 0; const bool allocated = model_raw && pre && reference && candidate; if (allocated) { memset(model_raw, 0, (size_t)model_alloc); float *scale = (float *)((uint8_t *)model_raw + scale_offset); float *base = (float *)((uint8_t *)model_raw + base_offset); for (uint32_t ci = 0; ci < 4; ci++) { float pre_host[4]; float ref_host[4]; float candidate_host[4]; for (uint32_t i = 0; i < 4; i++) { pre_host[i] = ((float)((int)(ci * 17u + i * 11u) - 23)) / 8.0f; base[i] = ((float)((int)(ci * 13u + i * 7u) - 19)) / 16.0f; } scale[0] = 0.62500012f + (float)ci * 0.125f; if (ci == 1) { /* The first lane distinguishes the required two-rounding * sequence from an illegally contracted multiply-add. */ const uint32_t pre_bits = 0x4620a541u; const uint32_t scale_bits = 0x462483bau; const uint32_t base_bits = 0xccce790eu; memcpy(&pre_host[0], &pre_bits, sizeof(pre_bits)); memcpy(&scale[0], &scale_bits, sizeof(scale_bits)); memcpy(&base[0], &base_bits, sizeof(base_bits)); } else if (ci == 2) { const uint32_t pre_bits[4] = { 0x00000000u, 0x80000000u, 0x00000001u, 0x80000001u, }; const uint32_t base_bits[4] = { 0x80000000u, 0x00000000u, 0x00800000u, 0x80800000u, }; for (uint32_t i = 0; i < 4; i++) { memcpy(&pre_host[i], &pre_bits[i], sizeof(uint32_t)); memcpy(&base[i], &base_bits[i], sizeof(uint32_t)); } scale[0] = -1.00000012f; } else if (ci == 3) { pre_host[0] = 100.0f; pre_host[1] = -100.0f; pre_host[2] = 88.0f; pre_host[3] = -88.0f; scale[0] = 1.0f; for (uint32_t i = 0; i < 4; i++) base[i] = 0.0f; } memset(ref_host, 0xa5, sizeof(ref_host)); memset(candidate_host, 0xa5, sizeof(candidate_host)); TEST_ASSERT(ds4_gpu_tensor_write(pre, 0, pre_host, bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( reference, 0, ref_host, bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( candidate, 0, candidate_host, bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(model_raw, model_alloc) != 0); TEST_ASSERT(unsetenv(require_env) == 0); ds4_gpu_test_set_flags(0); ds4_gpu_set_quality(true); TEST_ASSERT(ds4_gpu_output_hc_weights_tensor( reference, pre, model_raw, model_alloc, scale_offset, base_offset, n_hc, eps) != 0); ds4_gpu_set_quality(false); ds4_gpu_test_set_flags(DS4_GPU_TEST_OUTPUT_HC_WEIGHTS4); TEST_ASSERT(setenv(require_env, "1", 1) == 0); TEST_ASSERT(ds4_gpu_output_hc_weights_tensor( candidate, pre, model_raw, model_alloc, scale_offset, base_offset, n_hc, eps) != 0); TEST_ASSERT(ds4_gpu_tensor_read( reference, 0, ref_host, bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( candidate, 0, candidate_host, bytes) != 0); const test_float_compare_stats stats = test_compare_float_bits(ref_host, candidate_host, n_hc); fprintf(stderr, "ds4-test: output HC weights4 exact case=%u " "mismatch=%zu/%u max_ulp=%u max_abs=%g\n", ci, stats.mismatch_count, n_hc, stats.max_ulp, stats.max_abs); TEST_ASSERT(stats.mismatch_count == 0); total_mismatch += stats.mismatch_count; if (stats.max_ulp > max_ulp) max_ulp = stats.max_ulp; } /* Quality mode prevents strict selection of the fast path. */ TEST_ASSERT(setenv(require_env, "1", 1) == 0); ds4_gpu_set_quality(true); TEST_ASSERT(ds4_gpu_output_hc_weights_tensor( candidate, pre, model_raw, model_alloc, scale_offset, base_offset, n_hc, eps) == 0); ds4_gpu_set_quality(false); ds4_gpu_test_set_flags(0); } test_restore_env(require_env, saved_require); fprintf(stderr, "ds4-test: output HC weights4 total mismatch=%zu/16 max_ulp=%u\n", total_mismatch, max_ulp); TEST_ASSERT(total_mismatch == 0); TEST_ASSERT(max_ulp == 0); ds4_gpu_tensor_free(candidate); ds4_gpu_tensor_free(reference); ds4_gpu_tensor_free(pre); free(model_raw); } static void test_metal_hc_rms_scale_project_f16_exact_shape( uint32_t in_dim, uint32_t seed) { const uint32_t out_dim = 24; /* One full 32-row matmul tile plus a tail row covers both load paths. */ const uint32_t n_rows = 33; const float eps = 1.0e-6f; const uint64_t page = (uint64_t)getpagesize(); const uint64_t weight_offset = page; const uint64_t weight_bytes = (uint64_t)in_dim * out_dim * sizeof(uint16_t); const uint64_t model_alloc = test_round_up_u64( weight_offset + weight_bytes, page); const uint64_t x_count = (uint64_t)in_dim * n_rows; const uint64_t out_count = (uint64_t)out_dim * n_rows; const uint64_t x_bytes = x_count * sizeof(float); const uint64_t out_bytes = out_count * sizeof(float); const uint64_t scale_bytes = (uint64_t)n_rows * sizeof(float); void *model_raw = NULL; TEST_ASSERT(posix_memalign( &model_raw, (size_t)page, (size_t)model_alloc) == 0); ds4_gpu_tensor *x = ds4_gpu_tensor_alloc(x_bytes); ds4_gpu_tensor *ref_norm = ds4_gpu_tensor_alloc(x_bytes); ds4_gpu_tensor *ref_out = ds4_gpu_tensor_alloc(out_bytes); ds4_gpu_tensor *scaled_out = ds4_gpu_tensor_alloc(out_bytes); /* Deliberately too small for the full-RMS fallback. */ ds4_gpu_tensor *scale_scratch = ds4_gpu_tensor_alloc(scale_bytes); float *x_host = malloc((size_t)x_bytes); float *ref_norm_host = malloc((size_t)x_bytes); float *ref_out_host = malloc((size_t)out_bytes); float *scaled_out_host = malloc((size_t)out_bytes); float *scale_host = malloc((size_t)scale_bytes); float *expected_scale = malloc((size_t)scale_bytes); TEST_ASSERT(model_raw != NULL); TEST_ASSERT(x != NULL); TEST_ASSERT(ref_norm != NULL); TEST_ASSERT(ref_out != NULL); TEST_ASSERT(scaled_out != NULL); TEST_ASSERT(scale_scratch != NULL); TEST_ASSERT(x_host != NULL); TEST_ASSERT(ref_norm_host != NULL); TEST_ASSERT(ref_out_host != NULL); TEST_ASSERT(scaled_out_host != NULL); TEST_ASSERT(scale_host != NULL); TEST_ASSERT(expected_scale != NULL); const bool allocated = model_raw && x && ref_norm && ref_out && scaled_out && scale_scratch && x_host && ref_norm_host && ref_out_host && scaled_out_host && scale_host && expected_scale; test_float_compare_stats scale_stats = {0}; test_float_compare_stats out_stats = {0}; if (allocated) { memset(model_raw, 0, (size_t)model_alloc); uint16_t *weights = (uint16_t *)((uint8_t *)model_raw + weight_offset); for (uint32_t o = 0; o < out_dim; o++) { for (uint32_t i = 0; i < in_dim; i++) { const uint32_t key = i * 37u + o * 1009u + seed * 53u + ((i >> 4u) ^ (o * 17u)); uint16_t bits; if (key % 257u == 0u) { bits = (key & 1u) ? 0x8000u : 0x0000u; } else if (key % 263u == 0u) { bits = (key & 1u) ? 0x8001u : 0x0001u; } else if (key % 269u == 0u) { bits = (key & 1u) ? 0x8400u : 0x0400u; } else { const int value = (int)(key % 127u) - 63; bits = test_float_to_f16((float)value / 128.0f); } weights[(uint64_t)o * in_dim + i] = bits; } } static const uint32_t rounding_bits[] = { 0x3f800fffu, 0x3f801000u, 0x3f801001u, 0x3f802fffu, 0x3f803000u, 0x3f803001u, 0xbf800fffu, 0xbf801000u, 0xbf801001u, 0x3eaaaaabu, 0xbeaaaaabu, }; static const int sentinel_exp[] = { -2, -10, 0, -4, -6, -1 }; for (uint32_t row = 0; row < n_rows; row++) { for (uint32_t i = 0; i < in_dim; i++) { const uint32_t key = i * 131u + row * 977u + seed * 71u + ((i >> 3u) ^ (row * 29u)); const float sign = (key & 1u) ? -1.0f : 1.0f; float value; switch (row % 6u) { case 0: value = (float)((int)(key % 4093u) - 2046) / 512.0f; break; case 1: value = sign * ldexpf( (float)(1u + (key & 7u)) / 8.0f, -19); break; case 2: value = i % 257u == row % 257u ? sign * (16.0f + (float)(key & 7u)) : sign * (float)(1u + (key & 31u)) / 8192.0f; break; case 3: { const uint32_t bits = rounding_bits[ key % (sizeof(rounding_bits) / sizeof(rounding_bits[0]))]; memcpy(&value, &bits, sizeof(value)); break; } case 4: if ((key & 7u) == 0u) { const uint32_t bits = (key & 8u) ? 0x80000000u : 0u; memcpy(&value, &bits, sizeof(value)); } else { value = sign * ldexpf( 1.0f + (float)(key & 3u) * 0.25f, (int)((key >> 4u) % 14u) - 10); } break; default: value = sign * (float)(1u + (key % 251u)) / 256.0f; break; } x_host[(uint64_t)row * in_dim + i] = value; } x_host[(uint64_t)row * in_dim] = ldexpf(1.0f, sentinel_exp[row % 6u]); } for (uint64_t i = 0; i < out_count; i++) { const uint32_t bits = 0x7fc01000u + (uint32_t)(i & 0xfffu); memcpy(scaled_out_host + i, &bits, sizeof(bits)); } for (uint32_t row = 0; row < n_rows; row++) { const uint32_t bits = 0x7fc02000u + row; memcpy(scale_host + row, &bits, sizeof(bits)); } TEST_ASSERT(ds4_gpu_tensor_write(x, 0, x_host, x_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( scaled_out, 0, scaled_out_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_write( scale_scratch, 0, scale_host, scale_bytes) != 0); TEST_ASSERT(ds4_gpu_set_model_map(model_raw, model_alloc) != 0); ds4_gpu_set_quality(false); int ref_begun = ds4_gpu_begin_commands(); int ref_ok = ref_begun; if (ref_ok) ref_ok = ds4_gpu_rms_norm_plain_rows_tensor( ref_norm, x, in_dim, n_rows, eps); if (ref_ok) ref_ok = ds4_gpu_matmul_f16_tensor( ref_out, model_raw, model_alloc, weight_offset, in_dim, out_dim, ref_norm, n_rows); const int ref_end = ref_begun ? ds4_gpu_end_commands() : 0; TEST_ASSERT(ref_ok != 0); TEST_ASSERT(ref_end != 0); int scaled_begun = ds4_gpu_begin_commands(); int scaled_ok = scaled_begun; if (scaled_ok) scaled_ok = ds4_gpu_hc_rms_scale_project_f16_tensor( scaled_out, scale_scratch, model_raw, model_alloc, weight_offset, in_dim, out_dim, x, n_rows, eps); const int scaled_end = scaled_begun ? ds4_gpu_end_commands() : 0; TEST_ASSERT(scaled_ok != 0); TEST_ASSERT(scaled_end != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_norm, 0, ref_norm_host, x_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_out, 0, ref_out_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( scaled_out, 0, scaled_out_host, out_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( scale_scratch, 0, scale_host, scale_bytes) != 0); for (uint32_t row = 0; row < n_rows; row++) { expected_scale[row] = ldexpf( ref_norm_host[(uint64_t)row * in_dim], -sentinel_exp[row % 6u]); TEST_ASSERT(isfinite(expected_scale[row])); TEST_ASSERT(isfinite(scale_host[row])); } scale_stats = test_compare_float_bits( expected_scale, scale_host, n_rows); out_stats = test_compare_float_bits( ref_out_host, scaled_out_host, (size_t)out_count); } fprintf(stderr, "ds4-test: HC RMS scale F16 projection exact K=%u rows=%u " "scale=%zu/%u max_ulp=%u projection=%zu/%llu max_ulp=%u\n", in_dim, n_rows, scale_stats.mismatch_count, n_rows, scale_stats.max_ulp, out_stats.mismatch_count, (unsigned long long)out_count, out_stats.max_ulp); TEST_ASSERT(scale_stats.mismatch_count == 0); TEST_ASSERT(scale_stats.max_ulp == 0); TEST_ASSERT(out_stats.mismatch_count == 0); TEST_ASSERT(out_stats.max_ulp == 0); free(expected_scale); free(scale_host); free(scaled_out_host); free(ref_out_host); free(ref_norm_host); free(x_host); ds4_gpu_tensor_free(scale_scratch); ds4_gpu_tensor_free(scaled_out); ds4_gpu_tensor_free(ref_out); ds4_gpu_tensor_free(ref_norm); ds4_gpu_tensor_free(x); free(model_raw); } static void test_metal_hc_rms_scale_project_f16_exact(void) { const char *disable_env = "DS4_METAL_DISABLE_HC_RMS_SCALE_PROJ"; char *saved_disable = test_save_env(disable_env); TEST_ASSERT(unsetenv(disable_env) == 0); ds4_gpu_test_set_flags(DS4_GPU_TEST_HC_RMS_SCALE_PROJ); test_metal_hc_rms_scale_project_f16_exact_shape(16384u, 59u); test_metal_hc_rms_scale_project_f16_exact_shape(28672u, 61u); ds4_gpu_test_set_flags(0); test_restore_env(disable_env, saved_disable); } static void test_metal_router_simd_finalize_exact(void) { typedef struct { const char *name; bool has_bias; uint32_t pattern; } router_case; static const router_case cases[] = { { "unique", false, 0 }, { "bias", true, 0 }, { "top6-ties", false, 1 }, { "signed-zero-extremes", false, 2 }, { "clamp-underflow", false, 3 }, { "sum-rounding", true, 4 }, }; const uint32_t n_expert = 256; const uint32_t n_used = 6; const uint32_t modes = 4; const uint64_t probs_bytes = (uint64_t)n_expert * sizeof(float); const uint64_t selected_bytes = (uint64_t)n_used * sizeof(int32_t); const uint64_t weights_bytes = (uint64_t)n_used * sizeof(float); const uint64_t page = (uint64_t)getpagesize(); const char *disable_env = "DS4_METAL_DISABLE_PRE_M5_ROUTER_SIMD_FINALIZE"; const char *weights_disable_env = "DS4_METAL_DISABLE_PRE_M5_ROUTER_SIMD_WEIGHTS_FUSION"; const char *transform_finalize_disable_env = "DS4_METAL_DISABLE_PRE_M5_ROUTER_TRANSFORM_FINALIZE_FUSION"; const char *select_disable_env = "DS4_METAL_DISABLE_ROUTER_SELECT_FUSION"; void *model_raw = NULL; TEST_ASSERT(posix_memalign(&model_raw, (size_t)page, (size_t)page) == 0); ds4_gpu_tensor *logits = ds4_gpu_tensor_alloc(probs_bytes); ds4_gpu_tensor *ref_selected = ds4_gpu_tensor_alloc(selected_bytes); ds4_gpu_tensor *simd_selected = ds4_gpu_tensor_alloc(selected_bytes); ds4_gpu_tensor *ref_weights = ds4_gpu_tensor_alloc(weights_bytes); ds4_gpu_tensor *simd_weights = ds4_gpu_tensor_alloc(weights_bytes); ds4_gpu_tensor *ref_probs = ds4_gpu_tensor_alloc(probs_bytes); ds4_gpu_tensor *simd_probs = ds4_gpu_tensor_alloc(probs_bytes); float *logits_host = malloc((size_t)probs_bytes); float *ref_probs_host = malloc((size_t)probs_bytes); float *simd_probs_host = malloc((size_t)probs_bytes); int32_t ref_selected_host[6]; int32_t simd_selected_host[6]; int32_t unique_selected_host[6]; float ref_weights_host[6]; float simd_weights_host[6]; TEST_ASSERT(model_raw != NULL); TEST_ASSERT(logits != NULL); TEST_ASSERT(ref_selected != NULL); TEST_ASSERT(simd_selected != NULL); TEST_ASSERT(ref_weights != NULL); TEST_ASSERT(simd_weights != NULL); TEST_ASSERT(ref_probs != NULL); TEST_ASSERT(simd_probs != NULL); TEST_ASSERT(logits_host != NULL); TEST_ASSERT(ref_probs_host != NULL); TEST_ASSERT(simd_probs_host != NULL); char *saved_disable = test_save_env(disable_env); char *saved_weights_disable = test_save_env(weights_disable_env); char *saved_transform_finalize_disable = test_save_env(transform_finalize_disable_env); char *saved_select_disable = test_save_env(select_disable_env); size_t total_selected_mismatch = 0; size_t total_weights_mismatch = 0; size_t total_probs_mismatch = 0; const bool allocated = model_raw && logits && ref_selected && simd_selected && ref_weights && simd_weights && ref_probs && simd_probs && logits_host && ref_probs_host && simd_probs_host; if (allocated) { memset(model_raw, 0, (size_t)page); float *bias = model_raw; for (uint32_t i = 0; i < n_used; i++) { bias[200u + i] = 16.0f - (float)i; } TEST_ASSERT(ds4_gpu_set_model_map(model_raw, page) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(setenv(transform_finalize_disable_env, "1", 1) == 0); TEST_ASSERT(unsetenv(select_disable_env) == 0); for (size_t ci = 0; ci < sizeof(cases) / sizeof(cases[0]); ci++) { const router_case *c = &cases[ci]; for (uint32_t i = 0; i < n_expert; i++) { const int value = (int)((i * 47u + (i ^ (i >> 3u)) * 13u) % 257u) - 128; logits_host[i] = (float)value / 32.0f; } if (c->pattern == 1) { static const uint32_t tied[] = { 7u, 19u, 43u, 71u, 103u, 149u, 211u, 239u, }; for (uint32_t i = 0; i < n_expert; i++) { logits_host[i] = -7.0f - (float)(i % 17u) / 64.0f; } for (size_t i = 0; i < sizeof(tied) / sizeof(tied[0]); i++) { logits_host[tied[i]] = 1.0f; } } else if (c->pattern == 2) { for (uint32_t i = 0; i < n_expert; i++) { const uint32_t zero_bits = (i & 1u) ? 0x80000000u : 0u; memcpy(&logits_host[i], &zero_bits, sizeof(zero_bits)); } logits_host[3] = 80.0f; logits_host[17] = 40.0f; logits_host[61] = 20.0f; logits_host[127] = -20.0f; logits_host[193] = -40.0f; logits_host[251] = -80.0f; } else if (c->pattern == 3) { for (uint32_t i = 0; i < n_expert; i++) { logits_host[i] = -30.0f - (float)(i % 11u); } } else if (c->pattern == 4) { static const float rounding_logits[6] = { -0.6356699467f, -0.8182631135f, -2.7906901836f, -3.4414808750f, -3.4991359711f, -3.1251864433f, }; for (uint32_t i = 0; i < n_expert; i++) { logits_host[i] = -20.0f; } for (uint32_t i = 0; i < n_used; i++) { logits_host[200u + i] = rounding_logits[i]; } } TEST_ASSERT(ds4_gpu_tensor_write( logits, 0, logits_host, probs_bytes) != 0); TEST_ASSERT(setenv(disable_env, "1", 1) == 0); TEST_ASSERT(ds4_gpu_router_select_tensor( ref_selected, ref_weights, ref_probs, model_raw, page, 0, 0, 1, 0, n_expert, n_used, 1.5f, 1, 0, c->has_bias, false, logits) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_selected, 0, ref_selected_host, selected_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_weights, 0, ref_weights_host, weights_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_probs, 0, ref_probs_host, probs_bytes) != 0); if (ci == 0) { memcpy(unique_selected_host, ref_selected_host, sizeof(unique_selected_host)); } else if (c->has_bias) { TEST_ASSERT(memcmp(unique_selected_host, ref_selected_host, sizeof(unique_selected_host)) != 0); } TEST_ASSERT(unsetenv(disable_env) == 0); for (uint32_t mode = 0; mode < modes; mode++) { const bool fused_weights = mode != 0; const bool fused_transform = mode >= 2; if (fused_weights) { TEST_ASSERT(unsetenv(weights_disable_env) == 0); } else { TEST_ASSERT(setenv(weights_disable_env, "1", 1) == 0); } if (fused_transform) { TEST_ASSERT(unsetenv(transform_finalize_disable_env) == 0); } else { TEST_ASSERT(setenv( transform_finalize_disable_env, "1", 1) == 0); } for (uint32_t i = 0; i < n_expert; i++) { const uint32_t poison_bits = 0x7fc00001u + i; memcpy(&simd_probs_host[i], &poison_bits, sizeof(poison_bits)); } TEST_ASSERT(ds4_gpu_tensor_write( simd_probs, 0, simd_probs_host, probs_bytes) != 0); TEST_ASSERT(ds4_gpu_router_select_tensor( simd_selected, simd_weights, simd_probs, model_raw, page, 0, 0, 1, 0, n_expert, n_used, 1.5f, 1, 0, c->has_bias, false, logits) != 0); TEST_ASSERT(ds4_gpu_tensor_read( simd_selected, 0, simd_selected_host, selected_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( simd_weights, 0, simd_weights_host, weights_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( simd_probs, 0, simd_probs_host, probs_bytes) != 0); size_t selected_mismatch = 0; for (uint32_t i = 0; i < n_used; i++) { if (ref_selected_host[i] != simd_selected_host[i]) { selected_mismatch++; } } const test_float_compare_stats weights_stats = test_compare_float_bits( ref_weights_host, simd_weights_host, n_used); const test_float_compare_stats probs_stats = test_compare_float_bits( ref_probs_host, simd_probs_host, n_expert); fprintf(stderr, "ds4-test: router SIMD finalize exactness " "case=%s mode=%s rep=%u selected=%zu/%u weights=%zu/%u " "probs=%zu/%u max_weight_ulp=%u max_prob_ulp=%u\n", c->name, fused_transform ? "fused-transform" : fused_weights ? "fused-weights" : "split-weights", fused_transform ? mode - 2u : 0u, selected_mismatch, n_used, weights_stats.mismatch_count, n_used, probs_stats.mismatch_count, n_expert, weights_stats.max_ulp, probs_stats.max_ulp); TEST_ASSERT(selected_mismatch == 0); TEST_ASSERT(weights_stats.mismatch_count == 0); TEST_ASSERT(probs_stats.mismatch_count == 0); total_selected_mismatch += selected_mismatch; total_weights_mismatch += weights_stats.mismatch_count; total_probs_mismatch += probs_stats.mismatch_count; } } } test_restore_env(disable_env, saved_disable); test_restore_env(weights_disable_env, saved_weights_disable); test_restore_env(transform_finalize_disable_env, saved_transform_finalize_disable); test_restore_env(select_disable_env, saved_select_disable); fprintf(stderr, "ds4-test: router SIMD finalize total selected=%zu/%zu " "weights=%zu/%zu probs=%zu/%zu\n", total_selected_mismatch, (sizeof(cases) / sizeof(cases[0])) * modes * (size_t)n_used, total_weights_mismatch, (sizeof(cases) / sizeof(cases[0])) * modes * (size_t)n_used, total_probs_mismatch, (sizeof(cases) / sizeof(cases[0])) * modes * (size_t)n_expert); TEST_ASSERT(total_selected_mismatch == 0); TEST_ASSERT(total_weights_mismatch == 0); TEST_ASSERT(total_probs_mismatch == 0); free(simd_probs_host); free(ref_probs_host); free(logits_host); ds4_gpu_tensor_free(simd_probs); ds4_gpu_tensor_free(ref_probs); ds4_gpu_tensor_free(simd_weights); ds4_gpu_tensor_free(ref_weights); ds4_gpu_tensor_free(simd_selected); ds4_gpu_tensor_free(ref_selected); ds4_gpu_tensor_free(logits); free(model_raw); } static void test_metal_router_weights_batch_exact(void) { typedef struct { const char *name; uint32_t n_tokens; bool has_bias; bool hash_mode; uint32_t pattern; } router_batch_case; static const router_batch_case cases[] = { { "rows2-unique", 2, false, false, 0 }, { "rows17-bias-ties", 17, true, false, 1 }, { "rows129-hash-duplicates", 129, false, true, 2 }, { "rows2048-typical", 2048, false, false, 0 }, { "rows3-clamp-underflow", 3, false, false, 3 }, }; const uint32_t n_expert = 256; const uint32_t n_used = 6; const uint32_t max_tokens = 2048; const uint32_t hash_rows = 64; const uint32_t repeats = 2; const uint64_t logits_bytes = (uint64_t)max_tokens * n_expert * sizeof(float); const uint64_t selected_bytes = (uint64_t)max_tokens * n_used * sizeof(int32_t); const uint64_t weights_bytes = (uint64_t)max_tokens * n_used * sizeof(float); const uint64_t tokens_bytes = (uint64_t)max_tokens * sizeof(int32_t); const uint64_t page = (uint64_t)getpagesize(); const uint64_t bias_offset = 0; const uint64_t hash_offset = 2048; const char *disable_env = "DS4_METAL_DISABLE_ROUTER_WEIGHTS_BATCH_FUSION"; const char *select_disable_env = "DS4_METAL_DISABLE_ROUTER_SELECT_FUSION"; void *model_raw = NULL; TEST_ASSERT(posix_memalign(&model_raw, (size_t)page, (size_t)page) == 0); ds4_gpu_tensor *logits = ds4_gpu_tensor_alloc(logits_bytes); ds4_gpu_tensor *tokens = ds4_gpu_tensor_alloc(tokens_bytes); ds4_gpu_tensor *ref_selected = ds4_gpu_tensor_alloc(selected_bytes); ds4_gpu_tensor *batch_selected = ds4_gpu_tensor_alloc(selected_bytes); ds4_gpu_tensor *ref_weights = ds4_gpu_tensor_alloc(weights_bytes); ds4_gpu_tensor *batch_weights = ds4_gpu_tensor_alloc(weights_bytes); ds4_gpu_tensor *ref_probs = ds4_gpu_tensor_alloc(logits_bytes); ds4_gpu_tensor *batch_probs = ds4_gpu_tensor_alloc(logits_bytes); float *logits_host = malloc((size_t)logits_bytes); int32_t *tokens_host = malloc((size_t)tokens_bytes); int32_t *ref_selected_host = malloc((size_t)selected_bytes); int32_t *batch_selected_host = malloc((size_t)selected_bytes); float *ref_weights_host = malloc((size_t)weights_bytes); float *batch_weights_host = malloc((size_t)weights_bytes); float *ref_probs_host = malloc((size_t)logits_bytes); float *batch_probs_host = malloc((size_t)logits_bytes); TEST_ASSERT(model_raw != NULL); TEST_ASSERT(logits != NULL); TEST_ASSERT(tokens != NULL); TEST_ASSERT(ref_selected != NULL); TEST_ASSERT(batch_selected != NULL); TEST_ASSERT(ref_weights != NULL); TEST_ASSERT(batch_weights != NULL); TEST_ASSERT(ref_probs != NULL); TEST_ASSERT(batch_probs != NULL); TEST_ASSERT(logits_host != NULL); TEST_ASSERT(tokens_host != NULL); TEST_ASSERT(ref_selected_host != NULL); TEST_ASSERT(batch_selected_host != NULL); TEST_ASSERT(ref_weights_host != NULL); TEST_ASSERT(batch_weights_host != NULL); TEST_ASSERT(ref_probs_host != NULL); TEST_ASSERT(batch_probs_host != NULL); char *saved_disable = test_save_env(disable_env); char *saved_select_disable = test_save_env(select_disable_env); size_t total_selected_mismatch = 0; size_t total_weights_mismatch = 0; size_t total_probs_mismatch = 0; const bool allocated = model_raw && logits && tokens && ref_selected && batch_selected && ref_weights && batch_weights && ref_probs && batch_probs && logits_host && tokens_host && ref_selected_host && batch_selected_host && ref_weights_host && batch_weights_host && ref_probs_host && batch_probs_host; if (allocated) { memset(model_raw, 0, (size_t)page); float *bias = (float *)((uint8_t *)model_raw + bias_offset); int32_t *hash = (int32_t *)((uint8_t *)model_raw + hash_offset); for (uint32_t i = 0; i < n_expert; i++) { bias[i] = (float)((int)((i * 29u) % 67u) - 33) / 16.0f; } for (uint32_t row = 0; row < hash_rows; row++) { const int32_t base = (int32_t)((row * 37u) % n_expert); hash[(uint64_t)row * n_used + 0u] = base; hash[(uint64_t)row * n_used + 1u] = base; hash[(uint64_t)row * n_used + 2u] = (base + 19) % (int32_t)n_expert; hash[(uint64_t)row * n_used + 3u] = (base + 43) % (int32_t)n_expert; hash[(uint64_t)row * n_used + 4u] = (base + 43) % (int32_t)n_expert; hash[(uint64_t)row * n_used + 5u] = (base + 101) % (int32_t)n_expert; } for (uint32_t row = 0; row < max_tokens; row++) { tokens_host[row] = (int32_t)((row * 13u + 7u) % hash_rows); } TEST_ASSERT(ds4_gpu_set_model_map(model_raw, page) != 0); ds4_gpu_set_quality(false); TEST_ASSERT(ds4_gpu_tensor_write( tokens, 0, tokens_host, tokens_bytes) != 0); TEST_ASSERT(unsetenv(select_disable_env) == 0); for (size_t ci = 0; ci < sizeof(cases) / sizeof(cases[0]); ci++) { const router_batch_case *c = &cases[ci]; const size_t prob_count = (size_t)c->n_tokens * n_expert; const size_t route_count = (size_t)c->n_tokens * n_used; const uint64_t case_probs_bytes = prob_count * sizeof(float); const uint64_t case_selected_bytes = route_count * sizeof(int32_t); const uint64_t case_weights_bytes = route_count * sizeof(float); for (uint32_t row = 0; row < c->n_tokens; row++) { for (uint32_t expert = 0; expert < n_expert; expert++) { const size_t index = (size_t)row * n_expert + expert; const int value = (int)((row * 131u + expert * 47u + (expert ^ (expert >> 3u)) * 13u) % 513u) - 256; logits_host[index] = (float)value / 64.0f; if (c->pattern == 1) { logits_host[index] = -7.0f - (float)((row + expert) % 17u) / 64.0f; } else if (c->pattern == 3) { logits_host[index] = -30.0f - (float)((row * 17u + expert * 29u) % 11u); } } if (c->pattern == 1) { static const uint32_t tied[] = { 7u, 19u, 43u, 71u, 103u, 149u, 211u, 239u, }; for (size_t i = 0; i < sizeof(tied) / sizeof(tied[0]); i++) { logits_host[(size_t)row * n_expert + tied[i]] = 1.0f; } } } TEST_ASSERT(ds4_gpu_tensor_write( logits, 0, logits_host, case_probs_bytes) != 0); TEST_ASSERT(setenv(disable_env, "1", 1) == 0); TEST_ASSERT(ds4_gpu_router_select_batch_tensor( ref_selected, ref_weights, ref_probs, model_raw, page, bias_offset, hash_offset, hash_rows, 1, 0, c->has_bias, c->hash_mode, logits, tokens, n_expert, n_used, 1.5f, c->n_tokens) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_selected, 0, ref_selected_host, case_selected_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_weights, 0, ref_weights_host, case_weights_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( ref_probs, 0, ref_probs_host, case_probs_bytes) != 0); if (c->hash_mode) { for (uint32_t row = 0; row < c->n_tokens; row++) { const uint32_t hash_row = (uint32_t)tokens_host[row]; for (uint32_t lane = 0; lane < n_used; lane++) { TEST_ASSERT( ref_selected_host[(size_t)row * n_used + lane] == hash[(uint64_t)hash_row * n_used + lane]); } } } if (c->pattern == 3) { for (uint32_t row = 0; row < c->n_tokens; row++) { float sum = 0.0f; for (uint32_t lane = 0; lane < n_used; lane++) { const int32_t expert = ref_selected_host[(size_t)row * n_used + lane]; sum += ref_probs_host[(size_t)row * n_expert + (uint32_t)expert]; } TEST_ASSERT(sum < 6.103515625e-5f); } } TEST_ASSERT(unsetenv(disable_env) == 0); for (uint32_t rep = 0; rep < repeats; rep++) { TEST_ASSERT(ds4_gpu_router_select_batch_tensor( batch_selected, batch_weights, batch_probs, model_raw, page, bias_offset, hash_offset, hash_rows, 1, 0, c->has_bias, c->hash_mode, logits, tokens, n_expert, n_used, 1.5f, c->n_tokens) != 0); TEST_ASSERT(ds4_gpu_tensor_read( batch_selected, 0, batch_selected_host, case_selected_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( batch_weights, 0, batch_weights_host, case_weights_bytes) != 0); TEST_ASSERT(ds4_gpu_tensor_read( batch_probs, 0, batch_probs_host, case_probs_bytes) != 0); size_t selected_mismatch = 0; for (size_t i = 0; i < route_count; i++) { if (ref_selected_host[i] != batch_selected_host[i]) { selected_mismatch++; } } const test_float_compare_stats weights_stats = test_compare_float_bits( ref_weights_host, batch_weights_host, route_count); const test_float_compare_stats probs_stats = test_compare_float_bits( ref_probs_host, batch_probs_host, prob_count); fprintf(stderr, "ds4-test: router batch weights exactness " "case=%s rep=%u selected=%zu/%zu weights=%zu/%zu " "probs=%zu/%zu max_weight_ulp=%u max_prob_ulp=%u\n", c->name, rep, selected_mismatch, route_count, weights_stats.mismatch_count, route_count, probs_stats.mismatch_count, prob_count, weights_stats.max_ulp, probs_stats.max_ulp); TEST_ASSERT(selected_mismatch == 0); TEST_ASSERT(weights_stats.mismatch_count == 0); TEST_ASSERT(probs_stats.mismatch_count == 0); total_selected_mismatch += selected_mismatch; total_weights_mismatch += weights_stats.mismatch_count; total_probs_mismatch += probs_stats.mismatch_count; } } } test_restore_env(disable_env, saved_disable); test_restore_env(select_disable_env, saved_select_disable); fprintf(stderr, "ds4-test: router batch weights total selected=%zu " "weights=%zu probs=%zu\n", total_selected_mismatch, total_weights_mismatch, total_probs_mismatch); TEST_ASSERT(total_selected_mismatch == 0); TEST_ASSERT(total_weights_mismatch == 0); TEST_ASSERT(total_probs_mismatch == 0); free(batch_probs_host); free(ref_probs_host); free(batch_weights_host); free(ref_weights_host); free(batch_selected_host); free(ref_selected_host); free(tokens_host); free(logits_host); ds4_gpu_tensor_free(batch_probs); ds4_gpu_tensor_free(ref_probs); ds4_gpu_tensor_free(batch_weights); ds4_gpu_tensor_free(ref_weights); ds4_gpu_tensor_free(batch_selected); ds4_gpu_tensor_free(ref_selected); ds4_gpu_tensor_free(tokens); ds4_gpu_tensor_free(logits); free(model_raw); } #endif static void test_metal_kernel_group(void) { test_metal_f16_matvec_fast_nr0_4(); test_metal_f16_prefill_matmul(); test_metal_q8_0_prefill_matmul(); test_metal_pack_slot_rows_f32(); test_metal_store_raw_kv_batch_wrap(); test_dspark_cache_window_crop(); test_metal_q8_0_decode_pair_exact(); #if defined(__APPLE__) test_metal_f16_compressor_pair_state_store_exact(); test_metal_compressor_ape_add_exact(); test_metal_compressor_ratio4_pack_exact(); test_metal_compressor_ratio4_replay_pack_exact(); test_metal_compressor_ratio4_direct_pool_exact(); test_metal_inplace_rope_pair_exact(); test_metal_contiguous_f32_f16_roundtrip_exact(); test_metal_gathered_kv_stage_exact(); test_metal_contiguous_compressed_f16_attention_exact(); test_metal_persistent_zero_attention_mask_exact(); test_metal_zero_prefix_prefill_mask_cache_exact(); test_metal_hc_split_weighted_sum_norm_batch_exact(); test_metal_output_hc_weights4_exact(); test_metal_hc_rms_scale_project_f16_exact(); test_metal_router_simd_finalize_exact(); test_metal_router_weights_batch_exact(); #endif } static void test_metal_short_prefill_ratio4(void) { ds4_engine *engine = test_get_engine(false); if (!engine) return; const int tokens[] = { ds4_token_user(engine), ds4_token_assistant(engine), ds4_token_eos(engine), }; for (size_t i = 0; i < sizeof(tokens) / sizeof(tokens[0]); i++) { TEST_ASSERT(tokens[i] >= 0); if (tokens[i] < 0) return; } for (size_t n = 1; n <= 3; n++) { ds4_tokens prompt = {0}; for (size_t i = 0; i < n; i++) { ds4_tokens_push(&prompt, tokens[i]); } TEST_ASSERT(prompt.len == (int)n); ds4_session *session = NULL; TEST_ASSERT(ds4_session_create(&session, engine, 2048) == 0); if (!session) { ds4_tokens_free(&prompt); return; } char err[160] = {0}; const int rc = ds4_session_sync(session, &prompt, err, sizeof(err)); if (rc != 0) { fprintf(stderr, "ds4-test: short prefill failed for %zu token(s): %s\n", n, err); } TEST_ASSERT(rc == 0); ds4_session_free(session); ds4_tokens_free(&prompt); } } static char *test_read_file(const char *path) { FILE *fp = fopen(path, "rb"); if (!fp) return NULL; if (fseek(fp, 0, SEEK_END) != 0) { fclose(fp); return NULL; } long len = ftell(fp); if (len < 0) { fclose(fp); return NULL; } rewind(fp); char *s = malloc((size_t)len + 1); if (!s) { fclose(fp); return NULL; } size_t nread = fread(s, 1, (size_t)len, fp); fclose(fp); if (nread != (size_t)len) { free(s); return NULL; } s[len] = '\0'; return s; } typedef struct { const char *name; int number; } test_long_fact; static const test_long_fact test_long_facts[] = { {"Bob", 34}, {"Alice", 52}, {"Clara", 71}, {"Diego", 93}, {"Elena", 16}, {"Felix", 88}, {"Greta", 47}, {"Hugo", 29}, {"Iris", 64}, {"Jonas", 12}, {"Kira", 81}, {"Leo", 39}, {"Marta", 76}, {"Nadia", 23}, {"Owen", 58}, {"Priya", 97}, }; static bool test_is_name_boundary(char c) { unsigned char uc = (unsigned char)c; return c == '\0' || !(isalnum(uc) || c == '_'); } static bool test_parse_assignment_value(const char *p, int *value) { while (*p == ' ' || *p == '\t') p++; if (*p != '=') return false; p++; while (*p == ' ' || *p == '\t') p++; if (!isdigit((unsigned char)*p)) return false; int v = 0; while (isdigit((unsigned char)*p)) { v = v * 10 + (*p - '0'); p++; } *value = v; return true; } static bool test_output_has_fact(const char *text, const test_long_fact *fact) { const size_t name_len = strlen(fact->name); const char *p = text; bool saw_wrong_assignment = false; int wrong_value = -1; while ((p = strstr(p, fact->name)) != NULL) { const bool before_ok = p == text || test_is_name_boundary(p[-1]); const bool after_ok = test_is_name_boundary(p[name_len]) || p[name_len] == ' ' || p[name_len] == '\t' || p[name_len] == '='; if (before_ok && after_ok) { int value = 0; if (test_parse_assignment_value(p + name_len, &value)) { if (value == fact->number) return true; saw_wrong_assignment = true; wrong_value = value; } } p += name_len; } if (saw_wrong_assignment) { fprintf(stderr, "ds4-test: long-context wrong assignment for %s: got %d expected %d\n", fact->name, wrong_value, fact->number); } else { fprintf(stderr, "ds4-test: long-context missing assignment for %s=%d\n", fact->name, fact->number); } return false; } static int test_hex_digit(char c) { if (c >= '0' && c <= '9') return c - '0'; if (c >= 'a' && c <= 'f') return 10 + c - 'a'; if (c >= 'A' && c <= 'F') return 10 + c - 'A'; return -1; } static bool test_hex_to_bytes(const char *hex, unsigned char *out, int cap, int *len) { int n = 0; while (*hex && !isspace((unsigned char)*hex)) { int hi = test_hex_digit(hex[0]); int lo = test_hex_digit(hex[1]); if (hi < 0 || lo < 0 || n >= cap) return false; out[n++] = (unsigned char)((hi << 4) | lo); hex += 2; } *len = n; return true; } static bool test_token_bytes_equal(ds4_engine *engine, int token, const unsigned char *want, int want_len) { size_t got_len = 0; char *got = ds4_token_text(engine, token, &got_len); bool eq = got && got_len == (size_t)want_len && memcmp(got, want, (size_t)want_len) == 0; free(got); return eq; } static void test_long_prefill_progress(void *ud, const char *event, int current, int total) { (void)ud; if (strcmp(event, "prefill_chunk")) return; if (current == 0 || current == total || current % 8192 == 0) { fprintf(stderr, "ds4-test: long-context prefill %d/%d\n", current, total); } } static void test_long_story_fact_recall(void) { const char *prompt_path = getenv("DS4_TEST_LONG_PROMPT"); if (!prompt_path || !prompt_path[0]) { prompt_path = "tests/long_context_story_prompt.txt"; } char *prompt_text = test_read_file(prompt_path); TEST_ASSERT(prompt_text != NULL); if (!prompt_text) return; ds4_engine *engine = test_get_engine(false); if (!engine) { free(prompt_text); return; } ds4_tokens prompt = {0}; ds4_tokenize_rendered_chat(engine, prompt_text, &prompt); TEST_ASSERT(prompt.len > 30000); ds4_session *session = NULL; TEST_ASSERT(ds4_session_create(&session, engine, 100000) == 0); if (!session) { ds4_tokens_free(&prompt); free(prompt_text); return; } char err[160]; ds4_session_set_progress(session, test_long_prefill_progress, NULL); TEST_ASSERT(ds4_session_sync(session, &prompt, err, sizeof(err)) == 0); ds4_session_set_progress(session, NULL, NULL); buf out = {0}; uint64_t rng = 12345; int generated = 0; bool decode_ok = true; for (; generated < 350; generated++) { int token = ds4_session_sample(session, 0.0f, 0, 1.0f, 0.0f, &rng); if (token == ds4_token_eos(engine)) break; size_t piece_len = 0; char *piece = ds4_token_text(engine, token, &piece_len); buf_append(&out, piece, piece_len); free(piece); if (ds4_session_eval(session, token, err, sizeof(err)) != 0) { decode_ok = false; break; } } const char *text = out.ptr ? out.ptr : ""; TEST_ASSERT(decode_ok); TEST_ASSERT(generated > 0); for (size_t i = 0; i < sizeof(test_long_facts) / sizeof(test_long_facts[0]); i++) { TEST_ASSERT(test_output_has_fact(text, &test_long_facts[i])); } buf_free(&out); ds4_session_free(session); ds4_tokens_free(&prompt); free(prompt_text); } #define TEST_VEC_MAX_STEPS 16 #define TEST_VEC_MAX_TOP 32 #define TEST_VEC_MAX_TOKEN_BYTES 128 typedef struct { unsigned char bytes[TEST_VEC_MAX_TOKEN_BYTES]; int len; float logprob; } test_vec_top; typedef struct { unsigned char selected[TEST_VEC_MAX_TOKEN_BYTES]; int selected_len; int ntop; test_vec_top top[TEST_VEC_MAX_TOP]; } test_vec_step; typedef struct { char id[96]; char prompt_path[512]; int ctx; int nsteps; test_vec_step steps[TEST_VEC_MAX_STEPS]; } test_vec_case; static char *test_trim_line(char *line) { while (*line && isspace((unsigned char)*line)) line++; size_t n = strlen(line); while (n && isspace((unsigned char)line[n - 1])) line[--n] = '\0'; return line; } static bool test_read_vector_case(FILE *fp, test_vec_case *vc) { char line[2048]; memset(vc, 0, sizeof(*vc)); while (fgets(line, sizeof(line), fp)) { char *p = test_trim_line(line); if (!p[0] || p[0] == '#') continue; if (sscanf(p, "case %95s %d %d %511s", vc->id, &vc->ctx, &vc->nsteps, vc->prompt_path) == 4) { TEST_ASSERT(vc->nsteps > 0 && vc->nsteps <= TEST_VEC_MAX_STEPS); return true; } TEST_ASSERT(!"unexpected line before vector case"); } return false; } static bool test_fill_vector_case(FILE *fp, test_vec_case *vc) { char line[2048]; int step_index = -1; int top_index = 0; while (fgets(line, sizeof(line), fp)) { char *p = test_trim_line(line); if (!p[0] || p[0] == '#') continue; if (!strcmp(p, "end")) return true; if (!strncmp(p, "step ", 5)) { char hex[TEST_VEC_MAX_TOKEN_BYTES * 2 + 2]; int ntop = 0; if (sscanf(p, "step %d %257s %d", &step_index, hex, &ntop) != 3) { TEST_ASSERT(!"bad vector step line"); return false; } TEST_ASSERT(step_index >= 0 && step_index < vc->nsteps); TEST_ASSERT(ntop >= 0 && ntop <= TEST_VEC_MAX_TOP); vc->steps[step_index].ntop = ntop; TEST_ASSERT(test_hex_to_bytes(hex, vc->steps[step_index].selected, TEST_VEC_MAX_TOKEN_BYTES, &vc->steps[step_index].selected_len)); top_index = 0; continue; } if (!strncmp(p, "top ", 4)) { char hex[TEST_VEC_MAX_TOKEN_BYTES * 2 + 2]; float lp = 0.0f; TEST_ASSERT(step_index >= 0 && step_index < vc->nsteps); TEST_ASSERT(top_index < vc->steps[step_index].ntop); if (sscanf(p, "top %257s %f", hex, &lp) != 2) { TEST_ASSERT(!"bad vector top line"); return false; } test_vec_top *top = &vc->steps[step_index].top[top_index++]; top->logprob = lp; TEST_ASSERT(test_hex_to_bytes(hex, top->bytes, TEST_VEC_MAX_TOKEN_BYTES, &top->len)); continue; } TEST_ASSERT(!"unexpected vector line"); return false; } TEST_ASSERT(!"unterminated vector case"); return false; } static void test_logprob_vector_case(ds4_engine *engine, const test_vec_case *vc) { char *prompt_text = test_read_file(vc->prompt_path); TEST_ASSERT(prompt_text != NULL); if (!prompt_text) return; ds4_tokens prompt = {0}; ds4_encode_chat_prompt(engine, "", prompt_text, DS4_THINK_NONE, &prompt); free(prompt_text); ds4_session *session = NULL; TEST_ASSERT(ds4_session_create(&session, engine, vc->ctx) == 0); if (!session) { ds4_tokens_free(&prompt); return; } char err[160]; if (ds4_session_sync(session, &prompt, err, sizeof(err)) != 0) { fprintf(stderr, "ds4-test: vector %s prefill failed: %s\n", vc->id, err); TEST_ASSERT(false); ds4_session_free(session); ds4_tokens_free(&prompt); return; } ds4_token_score scores[20]; for (int i = 0; i < vc->nsteps; i++) { const test_vec_step *step = &vc->steps[i]; int nscore = ds4_session_top_logprobs(session, scores, 20); int token = ds4_session_argmax(session); if (!test_token_bytes_equal(engine, token, step->selected, step->selected_len)) { fprintf(stderr, "ds4-test: vector %s step %d selected token mismatch\n", vc->id, i); TEST_ASSERT(false); } for (int t = 0; t < step->ntop; t++) { bool found = false; float local_lp = 0.0f; for (int j = 0; j < nscore; j++) { if (scores[j].id < 0) continue; if (test_token_bytes_equal(engine, scores[j].id, step->top[t].bytes, step->top[t].len)) { found = true; local_lp = scores[j].logprob; break; } } if (!found) { fprintf(stderr, "ds4-test: vector %s step %d official top token missing locally\n", vc->id, i); TEST_ASSERT(false); } else if (fabsf(local_lp - step->top[t].logprob) > 4.0f) { fprintf(stderr, "ds4-test: vector %s step %d logprob delta too high: local=%g official=%g\n", vc->id, i, local_lp, step->top[t].logprob); TEST_ASSERT(false); } } if (i + 1 < vc->nsteps) { if (ds4_session_eval(session, token, err, sizeof(err)) != 0) { fprintf(stderr, "ds4-test: vector %s step %d eval failed: %s\n", vc->id, i, err); TEST_ASSERT(false); break; } } } ds4_session_free(session); ds4_tokens_free(&prompt); } static bool test_logprob_vector_case_disabled(const char *path, const test_vec_case *vc) { /* * This one long-context vector currently matches the public DeepSeek API less * after adding the official Hadamard+FP4 indexer path. The public official * implementation and the API appear to disagree here; the official graph has * slightly lower local perplexity on the A/B check we ran, so DS4 keeps that * implementation and only excludes this brittle API fixture for now. */ return !strcmp(path, "tests/test-vectors/flash-pre-0731/official.vec") && !strcmp(vc->id, "long_memory_archive"); } static void test_official_logprob_vectors_run(const char *case_filter) { const char *path = getenv("DS4_TEST_VECTOR_FILE"); if (!path || !path[0]) { path = "tests/test-vectors/flash-0731/official.vec"; } FILE *fp = fopen(path, "rb"); TEST_ASSERT(fp != NULL); if (!fp) return; char *saved_prefill_chunk = test_save_env("DS4_METAL_PREFILL_CHUNK"); char *saved_disable_metal4 = test_save_env("DS4_METAL_DISABLE_METAL4"); test_streaming_prefill_env saved_canonical_streaming_prefill = test_force_canonical_streaming_prefill(); setenv("DS4_METAL_PREFILL_CHUNK", "2048", 1); if (getenv("DS4_TEST_LOGPROB_AUTO_METAL") == NULL) { setenv("DS4_METAL_DISABLE_METAL4", "1", 1); } else { unsetenv("DS4_METAL_DISABLE_METAL4"); } ds4_engine *engine = test_open_engine(false); if (!engine) { test_restore_canonical_streaming_prefill(saved_canonical_streaming_prefill); test_restore_env("DS4_METAL_DISABLE_METAL4", saved_disable_metal4); test_restore_env("DS4_METAL_PREFILL_CHUNK", saved_prefill_chunk); fclose(fp); return; } test_vec_case vc; int ran = 0; while (test_read_vector_case(fp, &vc)) { if (!test_fill_vector_case(fp, &vc)) break; if (case_filter && case_filter[0] && strcmp(vc.id, case_filter)) { continue; } if (test_logprob_vector_case_disabled(path, &vc)) { fprintf(stderr, "ds4-test: vector %s skipped (API/official graph mismatch)\n", vc.id); continue; } fprintf(stderr, "ds4-test: vector %s\n", vc.id); test_logprob_vector_case(engine, &vc); ran++; } TEST_ASSERT(!case_filter || !case_filter[0] || ran == 1); ds4_engine_close(engine); test_restore_canonical_streaming_prefill(saved_canonical_streaming_prefill); test_restore_env("DS4_METAL_DISABLE_METAL4", saved_disable_metal4); test_restore_env("DS4_METAL_PREFILL_CHUNK", saved_prefill_chunk); fclose(fp); } static void test_official_logprob_vectors(void) { test_official_logprob_vectors_run(NULL); } static void test_metal_ssd_streaming_cache_pressure(void) { #ifndef __APPLE__ fprintf(stderr, "ds4-test: Metal SSD streaming cache-pressure repro skipped " "(Metal-only)\n"); #else /* * Regression repro for GitHub issue #384. * * The bug needs the Metal SSD-streaming decode layer-batch path and a small * routed-expert cache. Under pressure, a cache entry referenced by an * already-encoded-but-not-yet-executed layer can be reused for a later * layer in the same command buffer, producing deterministic wrong logits. */ char *saved_streaming = test_save_env("DS4_TEST_SSD_STREAMING"); char *saved_cache_gb = test_save_env("DS4_TEST_SSD_STREAMING_CACHE_GB"); char *saved_cache_experts = test_save_env("DS4_TEST_SSD_STREAMING_CACHE_EXPERTS"); char *saved_disable_layer_batch = test_save_env("DS4_METAL_DISABLE_STREAMING_LAYER_BATCH"); char *saved_disable_static_decode = test_save_env("DS4_METAL_DISABLE_STREAMING_STATIC_DECODE_MAP"); char *saved_one_stage = test_save_env("DS4_METAL_MOE_ONE_STAGE_PROFILE"); setenv("DS4_TEST_SSD_STREAMING", "1", 1); setenv("DS4_TEST_SSD_STREAMING_CACHE_GB", "16", 1); unsetenv("DS4_TEST_SSD_STREAMING_CACHE_EXPERTS"); unsetenv("DS4_METAL_DISABLE_STREAMING_LAYER_BATCH"); unsetenv("DS4_METAL_DISABLE_STREAMING_STATIC_DECODE_MAP"); unsetenv("DS4_METAL_MOE_ONE_STAGE_PROFILE"); fprintf(stderr, "ds4-test: Metal SSD streaming cache-pressure repro " "(16GiB cache, layer-batched decode, short_code_completion)\n"); test_official_logprob_vectors_run("short_code_completion"); test_restore_env("DS4_METAL_MOE_ONE_STAGE_PROFILE", saved_one_stage); test_restore_env("DS4_METAL_DISABLE_STREAMING_STATIC_DECODE_MAP", saved_disable_static_decode); test_restore_env("DS4_METAL_DISABLE_STREAMING_LAYER_BATCH", saved_disable_layer_batch); test_restore_env("DS4_TEST_SSD_STREAMING_CACHE_EXPERTS", saved_cache_experts); test_restore_env("DS4_TEST_SSD_STREAMING_CACHE_GB", saved_cache_gb); test_restore_env("DS4_TEST_SSD_STREAMING", saved_streaming); #endif } static void test_logits_topk(const float *logits, int n, int *out, int k); static bool test_topk_contains(const int *top, int k, int id); #define TEST_LOCAL_GOLDEN_MAX_TOP 128 typedef struct { int id; float logit; } test_local_golden_top; typedef struct { char id[96]; char mode[16]; char prompt_path[512]; int ctx; int frontier; int ntop; test_local_golden_top top[TEST_LOCAL_GOLDEN_MAX_TOP]; } test_local_golden_case; static bool test_read_local_golden_case(FILE *fp, test_local_golden_case *tc) { char line[2048]; memset(tc, 0, sizeof(*tc)); while (fgets(line, sizeof(line), fp)) { char *p = test_trim_line(line); if (!p[0] || p[0] == '#') continue; if (sscanf(p, "case %95s %15s %d %d %511s %d", tc->id, tc->mode, &tc->ctx, &tc->frontier, tc->prompt_path, &tc->ntop) == 6) { TEST_ASSERT(tc->ctx > tc->frontier); TEST_ASSERT(tc->frontier > 0); TEST_ASSERT(tc->ntop > 0 && tc->ntop <= TEST_LOCAL_GOLDEN_MAX_TOP); return true; } TEST_ASSERT(!"unexpected line before local golden case"); return false; } return false; } static bool test_fill_local_golden_case(FILE *fp, test_local_golden_case *tc) { char line[2048]; int seen = 0; while (fgets(line, sizeof(line), fp)) { char *p = test_trim_line(line); if (!p[0] || p[0] == '#') continue; if (!strcmp(p, "end")) { TEST_ASSERT(seen == tc->ntop); return seen == tc->ntop; } int rank = -1; int id = -1; float logit = 0.0f; if (sscanf(p, "top %d %d %f", &rank, &id, &logit) != 3) { TEST_ASSERT(!"bad local golden top line"); return false; } TEST_ASSERT(rank == seen); TEST_ASSERT(seen < tc->ntop); if (seen >= tc->ntop) return false; tc->top[seen].id = id; tc->top[seen].logit = logit; seen++; } TEST_ASSERT(!"unterminated local golden case"); return false; } static int test_local_golden_overlap(const test_local_golden_case *tc, const int *cand_top, int n) { int overlap = 0; if (n > tc->ntop) n = tc->ntop; for (int i = 0; i < n; i++) { if (test_topk_contains(cand_top, n, tc->top[i].id)) overlap++; } return overlap; } static float test_local_golden_max_abs(const test_local_golden_case *tc, const float *cand_logits, int n) { float max_abs = 0.0f; if (n > tc->ntop) n = tc->ntop; for (int i = 0; i < n; i++) { const int id = tc->top[i].id; if (id < 0) continue; const float abs_delta = fabsf(cand_logits[id] - tc->top[i].logit); if (abs_delta > max_abs) max_abs = abs_delta; } return max_abs; } static void test_local_golden_case_run(ds4_engine *engine, const test_local_golden_case *tc) { char *prompt_text = test_read_file(tc->prompt_path); TEST_ASSERT(prompt_text != NULL); if (!prompt_text) return; ds4_tokens prompt = {0}; if (!strcmp(tc->mode, "text")) { ds4_tokenize_text(engine, prompt_text, &prompt); } else if (!strcmp(tc->mode, "rendered")) { ds4_tokenize_rendered_chat(engine, prompt_text, &prompt); } else if (!strcmp(tc->mode, "chat")) { ds4_encode_chat_prompt(engine, "", prompt_text, DS4_THINK_NONE, &prompt); } else { TEST_ASSERT(!"unknown local golden prompt mode"); } free(prompt_text); TEST_ASSERT(prompt.len >= tc->frontier); if (prompt.len < tc->frontier) { ds4_tokens_free(&prompt); return; } ds4_tokens prefix = { .v = prompt.v, .len = tc->frontier, .cap = tc->frontier, }; ds4_session *session = NULL; TEST_ASSERT(ds4_session_create(&session, engine, tc->ctx) == 0); if (!session) { ds4_tokens_free(&prompt); return; } char err[160]; TEST_ASSERT(ds4_session_sync(session, &prefix, err, sizeof(err)) == 0); const int vocab = ds4_engine_vocab_size(engine); float *cand_logits = malloc((size_t)vocab * sizeof(cand_logits[0])); TEST_ASSERT(cand_logits != NULL); if (cand_logits && ds4_session_copy_logits(session, cand_logits, vocab) == vocab) { int cand_top[TEST_LOCAL_GOLDEN_MAX_TOP]; const int ntop = tc->ntop < TEST_LOCAL_GOLDEN_MAX_TOP ? tc->ntop : TEST_LOCAL_GOLDEN_MAX_TOP; test_logits_topk(cand_logits, vocab, cand_top, ntop); const int top5_overlap = test_local_golden_overlap(tc, cand_top, 5); const int top20_overlap = test_local_golden_overlap(tc, cand_top, 20); const int top64_overlap = test_local_golden_overlap(tc, cand_top, 64); const float top20_max_abs = test_local_golden_max_abs(tc, cand_logits, 20); fprintf(stderr, "ds4-test: local golden %s top1 ref=%d cand=%d " "top5_overlap=%d/5 top20_overlap=%d/20 top64_overlap=%d/64 " "top20_max_abs=%g\n", tc->id, tc->top[0].id, cand_top[0], top5_overlap, top20_overlap, top64_overlap, top20_max_abs); /* * This is intentionally tolerant: it is meant to catch substantial * backend drift (wrong tiling, skipped work, bad dispatch), not tiny * floating-point differences from otherwise sane kernel changes. */ TEST_ASSERT(cand_top[0] == tc->top[0].id); TEST_ASSERT(top5_overlap >= 4); TEST_ASSERT(top20_overlap >= 15); TEST_ASSERT(top64_overlap >= 40); TEST_ASSERT(top20_max_abs <= 8.0f); } else { TEST_ASSERT(false); } free(cand_logits); ds4_session_free(session); ds4_tokens_free(&prompt); } static void test_local_golden_vectors(void) { const char *path = getenv("DS4_TEST_LOCAL_GOLDEN_FILE"); if (!path || !path[0]) { path = "tests/test-vectors/flash-0731/local-golden.vec"; } FILE *fp = fopen(path, "rb"); TEST_ASSERT(fp != NULL); if (!fp) return; char *saved_prefill_chunk = test_save_env("DS4_METAL_PREFILL_CHUNK"); char *saved_disable_metal4 = test_save_env("DS4_METAL_DISABLE_METAL4"); char *saved_moe_tile_max = test_save_env("DS4_METAL_MOE_TILE_MAX"); test_streaming_prefill_env saved_canonical_streaming_prefill = test_force_canonical_streaming_prefill(); setenv("DS4_METAL_PREFILL_CHUNK", "4096", 1); setenv("DS4_METAL_DISABLE_METAL4", "1", 1); unsetenv("DS4_METAL_MOE_TILE_MAX"); ds4_engine *engine = test_open_engine(false); if (!engine) { test_restore_canonical_streaming_prefill(saved_canonical_streaming_prefill); test_restore_env("DS4_METAL_MOE_TILE_MAX", saved_moe_tile_max); test_restore_env("DS4_METAL_DISABLE_METAL4", saved_disable_metal4); test_restore_env("DS4_METAL_PREFILL_CHUNK", saved_prefill_chunk); fclose(fp); return; } test_local_golden_case tc; while (test_read_local_golden_case(fp, &tc)) { if (!test_fill_local_golden_case(fp, &tc)) break; test_local_golden_case_run(engine, &tc); } ds4_engine_close(engine); test_restore_canonical_streaming_prefill(saved_canonical_streaming_prefill); test_restore_env("DS4_METAL_MOE_TILE_MAX", saved_moe_tile_max); test_restore_env("DS4_METAL_DISABLE_METAL4", saved_disable_metal4); test_restore_env("DS4_METAL_PREFILL_CHUNK", saved_prefill_chunk); fclose(fp); } #define TEST_MPP_EQ_MAX_CASES 8 #define TEST_MPP_EQ_TOPK 20 #define TEST_MPP_EQ_TOP5 5 #define TEST_MPP_EQ_DELTAS 5 typedef struct { char id[96]; int ctx; int vocab_size; int gen_steps; ds4_tokens prompt; float *ref_logits; int ref_gen[TEST_VEC_MAX_STEPS]; int ref_gen_len; } test_mpp_eq_case; typedef struct { int ref_top1; int cand_top1; int overlap; int top5_overlap; int max_rank_delta; int nonfinite; float rms; float max_abs; float top20_max_abs; bool same_top1; bool pass; } test_mpp_eq_result; typedef struct { const char *label; int cases; int capture_failures; int logits_failures; int greedy_failures; int top1_mismatches; int min_overlap; int min_top5_overlap; int worst_rank_delta; float worst_rms; float worst_max_abs; float worst_top20_max_abs; } test_mpp_eq_summary; static void test_mpp_eq_case_free(test_mpp_eq_case *tc) { if (!tc) return; ds4_tokens_free(&tc->prompt); free(tc->ref_logits); memset(tc, 0, sizeof(*tc)); } static void test_logits_topk(const float *logits, int n, int *out, int k) { for (int i = 0; i < k; i++) out[i] = -1; for (int id = 0; id < n; id++) { const float v = logits[id]; if (!isfinite(v)) continue; for (int j = 0; j < k; j++) { if (out[j] < 0 || v > logits[out[j]]) { for (int l = k - 1; l > j; l--) out[l] = out[l - 1]; out[j] = id; break; } } } } static bool test_topk_contains(const int *top, int k, int id) { for (int i = 0; i < k; i++) { if (top[i] == id) return true; } return false; } static int test_topk_rank(const int *top, int k, int id) { for (int i = 0; i < k; i++) { if (top[i] == id) return i; } return -1; } static void test_note_delta(int *ids, float *ref_vals, float *cand_vals, float *abs_vals, int id, float ref, float cand) { const float abs_delta = fabsf(cand - ref); for (int i = 0; i < TEST_MPP_EQ_DELTAS; i++) { if (ids[i] < 0 || abs_delta > abs_vals[i]) { for (int j = TEST_MPP_EQ_DELTAS - 1; j > i; j--) { ids[j] = ids[j - 1]; ref_vals[j] = ref_vals[j - 1]; cand_vals[j] = cand_vals[j - 1]; abs_vals[j] = abs_vals[j - 1]; } ids[i] = id; ref_vals[i] = ref; cand_vals[i] = cand; abs_vals[i] = abs_delta; return; } } } static float test_top_union_max_abs(const float *ref, const float *cand, const int *ref_top, const int *cand_top, int k) { float max_abs = 0.0f; for (int i = 0; i < k; i++) { if (ref_top[i] >= 0) { const float d = fabsf(cand[ref_top[i]] - ref[ref_top[i]]); if (d > max_abs) max_abs = d; } if (cand_top[i] >= 0 && !test_topk_contains(ref_top, k, cand_top[i])) { const float d = fabsf(cand[cand_top[i]] - ref[cand_top[i]]); if (d > max_abs) max_abs = d; } } return max_abs; } /* * Metal4/TensorOps equivalence is a smoke test, not a demand for bitwise local * logits. Tensor kernels change precision and reduction order, so the useful * invariant here is: no NaNs, same first greedy token, and same short greedy * continuation. Larger logit drift is still printed so it can be compared with * official API-vector and long-context recall gates. */ static test_mpp_eq_result test_compare_mpp_logits(const test_mpp_eq_case *tc, const float *cand_logits, bool assert_thresholds) { int ref_top[TEST_MPP_EQ_TOPK]; int cand_top[TEST_MPP_EQ_TOPK]; test_logits_topk(tc->ref_logits, tc->vocab_size, ref_top, TEST_MPP_EQ_TOPK); test_logits_topk(cand_logits, tc->vocab_size, cand_top, TEST_MPP_EQ_TOPK); int overlap = 0; int top5_overlap = 0; int max_rank_delta = 0; for (int i = 0; i < TEST_MPP_EQ_TOPK; i++) { const int cand_rank = test_topk_rank(cand_top, TEST_MPP_EQ_TOPK, ref_top[i]); if (ref_top[i] >= 0 && cand_rank >= 0) { overlap++; const int rank_delta = abs(cand_rank - i); if (rank_delta > max_rank_delta) max_rank_delta = rank_delta; } if (i < TEST_MPP_EQ_TOP5 && ref_top[i] >= 0 && test_topk_contains(cand_top, TEST_MPP_EQ_TOP5, ref_top[i])) { top5_overlap++; } } double sumsq = 0.0; float max_abs = 0.0f; int nonfinite = 0; int delta_ids[TEST_MPP_EQ_DELTAS]; float delta_ref[TEST_MPP_EQ_DELTAS]; float delta_cand[TEST_MPP_EQ_DELTAS]; float delta_abs[TEST_MPP_EQ_DELTAS]; for (int i = 0; i < TEST_MPP_EQ_DELTAS; i++) { delta_ids[i] = -1; delta_ref[i] = 0.0f; delta_cand[i] = 0.0f; delta_abs[i] = 0.0f; } for (int i = 0; i < tc->vocab_size; i++) { if (!isfinite(tc->ref_logits[i]) || !isfinite(cand_logits[i])) { nonfinite++; continue; } const float delta = cand_logits[i] - tc->ref_logits[i]; const float abs_delta = fabsf(delta); if (abs_delta > max_abs) max_abs = abs_delta; sumsq += (double)delta * (double)delta; test_note_delta(delta_ids, delta_ref, delta_cand, delta_abs, (int)i, tc->ref_logits[i], cand_logits[i]); } const float rms = (float)sqrt(sumsq / (double)tc->vocab_size); const float top_abs = test_top_union_max_abs(tc->ref_logits, cand_logits, ref_top, cand_top, TEST_MPP_EQ_TOPK); const bool same_top1 = ref_top[0] >= 0 && ref_top[0] == cand_top[0]; test_mpp_eq_result result = { .ref_top1 = ref_top[0], .cand_top1 = cand_top[0], .overlap = overlap, .top5_overlap = top5_overlap, .max_rank_delta = max_rank_delta, .nonfinite = nonfinite, .rms = rms, .max_abs = max_abs, .top20_max_abs = top_abs, .same_top1 = same_top1, .pass = nonfinite == 0 && same_top1, }; fprintf(stderr, "ds4-test: Tensor equivalence %s top1 ref=%d cand=%d top5_overlap=%d/%d overlap=%d/%d max_rank_delta=%d rms=%g max_abs=%g top20_max_abs=%g\n", tc->id, ref_top[0], cand_top[0], top5_overlap, TEST_MPP_EQ_TOP5, overlap, TEST_MPP_EQ_TOPK, max_rank_delta, rms, max_abs, top_abs); fprintf(stderr, "ds4-test: Tensor equivalence %s largest deltas:", tc->id); for (int i = 0; i < TEST_MPP_EQ_DELTAS && delta_ids[i] >= 0; i++) { fprintf(stderr, " id=%d ref=%g cand=%g abs=%g", delta_ids[i], delta_ref[i], delta_cand[i], delta_abs[i]); } fputc('\n', stderr); if (assert_thresholds) { TEST_ASSERT(nonfinite == 0); TEST_ASSERT(same_top1); } return result; } static bool test_mpp_capture(ds4_engine *engine, const test_mpp_eq_case *tc, float *logits, int *gen, int *gen_len) { ds4_session *session = NULL; TEST_ASSERT(ds4_session_create(&session, engine, tc->ctx) == 0); if (!session) return false; char err[160]; bool ok = ds4_session_sync(session, &tc->prompt, err, sizeof(err)) == 0; TEST_ASSERT(ok); if (ok) { ok = ds4_session_copy_logits(session, logits, tc->vocab_size) == tc->vocab_size; TEST_ASSERT(ok); } int n = 0; while (ok && n < tc->gen_steps) { const int token = ds4_session_argmax(session); gen[n++] = token; if (n < tc->gen_steps && ds4_session_eval(session, token, err, sizeof(err)) != 0) { ok = false; TEST_ASSERT(false); } } *gen_len = n; ds4_session_free(session); return ok; } static bool test_mpp_capture_logits_only(ds4_engine *engine, const test_mpp_eq_case *tc, float *logits) { ds4_session *session = NULL; TEST_ASSERT(ds4_session_create(&session, engine, tc->ctx) == 0); if (!session) return false; char err[160]; bool ok = ds4_session_sync(session, &tc->prompt, err, sizeof(err)) == 0; TEST_ASSERT(ok); if (ok) { ok = ds4_session_copy_logits(session, logits, tc->vocab_size) == tc->vocab_size; TEST_ASSERT(ok); } ds4_session_free(session); return ok; } static bool test_mpp_eq_case_selected(const char *id) { const char *filter = getenv("DS4_TEST_MPP_EQ_CASE"); if (!filter || !filter[0]) return true; char buf[256]; snprintf(buf, sizeof(buf), "%s", filter); for (char *tok = strtok(buf, ","); tok; tok = strtok(NULL, ",")) { tok = test_trim_line(tok); if (tok[0] && strstr(id, tok)) return true; } return false; } static int test_load_mpp_cases(ds4_engine *engine, test_mpp_eq_case *cases, int cap) { const char *path = getenv("DS4_TEST_VECTOR_FILE"); if (!path || !path[0]) { path = "tests/test-vectors/flash-0731/official.vec"; } FILE *fp = fopen(path, "rb"); TEST_ASSERT(fp != NULL); if (!fp) return 0; int ncase = 0; test_vec_case vc; while (ncase < cap && test_read_vector_case(fp, &vc)) { if (!test_fill_vector_case(fp, &vc)) break; if (!test_mpp_eq_case_selected(vc.id)) continue; char *prompt_text = test_read_file(vc.prompt_path); TEST_ASSERT(prompt_text != NULL); if (!prompt_text) continue; test_mpp_eq_case *tc = &cases[ncase++]; snprintf(tc->id, sizeof(tc->id), "%s", vc.id); tc->ctx = vc.ctx; tc->vocab_size = ds4_engine_vocab_size(engine); tc->gen_steps = vc.nsteps < TEST_VEC_MAX_STEPS ? vc.nsteps : TEST_VEC_MAX_STEPS; ds4_encode_chat_prompt(engine, "", prompt_text, DS4_THINK_NONE, &tc->prompt); free(prompt_text); TEST_ASSERT(tc->prompt.len > 0); } fclose(fp); return ncase; } static void test_mpp_summary_init(test_mpp_eq_summary *summary, const char *label) { memset(summary, 0, sizeof(*summary)); summary->label = label; summary->min_overlap = TEST_MPP_EQ_TOPK; summary->min_top5_overlap = TEST_MPP_EQ_TOP5; } static void test_mpp_summary_note_logits(test_mpp_eq_summary *summary, const test_mpp_eq_result *result) { if (!result->pass) summary->logits_failures++; if (!result->same_top1) summary->top1_mismatches++; if (result->overlap < summary->min_overlap) summary->min_overlap = result->overlap; if (result->top5_overlap < summary->min_top5_overlap) { summary->min_top5_overlap = result->top5_overlap; } if (result->max_rank_delta > summary->worst_rank_delta) { summary->worst_rank_delta = result->max_rank_delta; } if (result->rms > summary->worst_rms) summary->worst_rms = result->rms; if (result->max_abs > summary->worst_max_abs) summary->worst_max_abs = result->max_abs; if (result->top20_max_abs > summary->worst_top20_max_abs) { summary->worst_top20_max_abs = result->top20_max_abs; } } static void test_mpp_summary_print(const test_mpp_eq_summary *summary) { fprintf(stderr, "ds4-test: Tensor summary route=%s cases=%d capture_fail=%d logits_fail=%d greedy_fail=%d top1_mismatch=%d min_top5_overlap=%d/%d min_overlap=%d/%d worst_rank_delta=%d worst_rms=%g worst_max_abs=%g worst_top20_max_abs=%g\n", summary->label, summary->cases, summary->capture_failures, summary->logits_failures, summary->greedy_failures, summary->top1_mismatches, summary->min_top5_overlap, TEST_MPP_EQ_TOP5, summary->min_overlap, TEST_MPP_EQ_TOPK, summary->worst_rank_delta, summary->worst_rms, summary->worst_max_abs, summary->worst_top20_max_abs); } static void test_run_mpp_candidate(const char *label, test_mpp_eq_case *cases, int ncase) { fprintf(stderr, "ds4-test: Tensor equivalence candidate route=%s\n", label); test_mpp_eq_summary summary; test_mpp_summary_init(&summary, label); ds4_engine *cand_engine = test_open_engine(false); if (cand_engine) { const int vocab_size = ncase > 0 ? cases[0].vocab_size : 0; float *cand_logits = malloc((size_t)vocab_size * sizeof(cand_logits[0])); TEST_ASSERT(cand_logits != NULL); if (cand_logits) { for (int i = 0; i < ncase; i++) { test_mpp_eq_case *tc = &cases[i]; if (!tc->ref_logits) continue; int cand_gen[TEST_VEC_MAX_STEPS] = {0}; int cand_gen_len = 0; if (!test_mpp_capture(cand_engine, tc, cand_logits, cand_gen, &cand_gen_len)) { summary.capture_failures++; continue; } summary.cases++; test_mpp_eq_result result = test_compare_mpp_logits(tc, cand_logits, true); test_mpp_summary_note_logits(&summary, &result); TEST_ASSERT(cand_gen_len == tc->ref_gen_len); if (cand_gen_len != tc->ref_gen_len) summary.greedy_failures++; for (int j = 0; j < tc->ref_gen_len && j < cand_gen_len; j++) { if (cand_gen[j] != tc->ref_gen[j]) { fprintf(stderr, "ds4-test: Tensor equivalence %s greedy token mismatch step=%d ref=%d cand=%d\n", tc->id, j, tc->ref_gen[j], cand_gen[j]); summary.greedy_failures++; } TEST_ASSERT(cand_gen[j] == tc->ref_gen[j]); } } free(cand_logits); } ds4_engine_close(cand_engine); } test_mpp_summary_print(&summary); } static void test_metal_mpp_equivalence(void) { test_close_engines(); test_mpp_eq_case cases[TEST_MPP_EQ_MAX_CASES]; memset(cases, 0, sizeof(cases)); char *saved_disable_metal4 = test_save_env("DS4_METAL_DISABLE_METAL4"); setenv("DS4_METAL_DISABLE_METAL4", "1", 1); ds4_engine *ref_engine = test_open_engine(false); if (!ref_engine) { test_restore_env("DS4_METAL_DISABLE_METAL4", saved_disable_metal4); return; } const int ncase = test_load_mpp_cases(ref_engine, cases, TEST_MPP_EQ_MAX_CASES); TEST_ASSERT(ncase > 0); for (int i = 0; i < ncase; i++) { test_mpp_eq_case *tc = &cases[i]; tc->ref_logits = malloc((size_t)tc->vocab_size * sizeof(tc->ref_logits[0])); TEST_ASSERT(tc->ref_logits != NULL); if (!tc->ref_logits) continue; TEST_ASSERT(test_mpp_capture(ref_engine, tc, tc->ref_logits, tc->ref_gen, &tc->ref_gen_len)); } ds4_engine_close(ref_engine); test_restore_env("DS4_METAL_DISABLE_METAL4", saved_disable_metal4); test_run_mpp_candidate("auto", cases, ncase); for (int i = 0; i < ncase; i++) test_mpp_eq_case_free(&cases[i]); } static void test_streaming_decode_prefill_correctness(void) { test_close_engines(); if (!test_env_bool("DS4_TEST_SSD_STREAMING")) { fprintf(stderr, "ds4-test: streaming decode-prefill correctness skipped " "(set DS4_TEST_SSD_STREAMING=1 to enable)\n"); return; } test_mpp_eq_case cases[TEST_MPP_EQ_MAX_CASES]; memset(cases, 0, sizeof(cases)); test_streaming_prefill_env saved_canonical_streaming_prefill = test_force_canonical_streaming_prefill(); ds4_engine *ref_engine = test_open_engine(false); if (!ref_engine) { test_restore_canonical_streaming_prefill(saved_canonical_streaming_prefill); return; } const int ncase = test_load_mpp_cases(ref_engine, cases, TEST_MPP_EQ_MAX_CASES); TEST_ASSERT(ncase > 0); for (int i = 0; i < ncase; i++) { test_mpp_eq_case *tc = &cases[i]; tc->ref_logits = malloc((size_t)tc->vocab_size * sizeof(tc->ref_logits[0])); TEST_ASSERT(tc->ref_logits != NULL); if (!tc->ref_logits) continue; TEST_ASSERT(test_mpp_capture(ref_engine, tc, tc->ref_logits, tc->ref_gen, &tc->ref_gen_len)); } ds4_engine_close(ref_engine); unsetenv("DS4_METAL_DISABLE_STREAMING_COLD_DECODE_PREFILL"); unsetenv("DS4_METAL_DISABLE_STREAMING_PREFILL_BATCH_SELECTED_ADDR"); ds4_engine *cand_engine = test_open_engine(false); if (cand_engine) { for (int i = 0; i < ncase; i++) { test_mpp_eq_case *tc = &cases[i]; if (!tc->ref_logits) continue; float *cand_cold = malloc((size_t)tc->vocab_size * sizeof(cand_cold[0])); float *cand_warm_a = malloc((size_t)tc->vocab_size * sizeof(cand_warm_a[0])); float *cand_warm_b = malloc((size_t)tc->vocab_size * sizeof(cand_warm_b[0])); TEST_ASSERT(cand_cold != NULL); TEST_ASSERT(cand_warm_a != NULL); TEST_ASSERT(cand_warm_b != NULL); if (!cand_cold || !cand_warm_a || !cand_warm_b) { free(cand_cold); free(cand_warm_a); free(cand_warm_b); continue; } TEST_ASSERT(test_mpp_capture_logits_only(cand_engine, tc, cand_cold)); TEST_ASSERT(test_mpp_capture_logits_only(cand_engine, tc, cand_warm_a)); TEST_ASSERT(test_mpp_capture_logits_only(cand_engine, tc, cand_warm_b)); test_mpp_eq_result result = test_compare_mpp_logits(tc, cand_cold, false); TEST_ASSERT(result.nonfinite == 0); TEST_ASSERT(result.top5_overlap >= 2); TEST_ASSERT(result.overlap >= 10); TEST_ASSERT(result.rms <= 4.0f); TEST_ASSERT(result.top20_max_abs <= 12.0f); int cold_warm_neq = 0; int warm_repeat_neq = 0; int repeat_nonfinite = 0; float cold_warm_max_abs = 0.0f; float warm_repeat_max_abs = 0.0f; for (int j = 0; j < tc->vocab_size; j++) { if (!isfinite(cand_cold[j]) || !isfinite(cand_warm_a[j]) || !isfinite(cand_warm_b[j])) { repeat_nonfinite++; continue; } const float cold_warm_d = fabsf(cand_cold[j] - cand_warm_a[j]); if (cold_warm_d != 0.0f) cold_warm_neq++; if (cold_warm_d > cold_warm_max_abs) cold_warm_max_abs = cold_warm_d; const float warm_repeat_d = fabsf(cand_warm_a[j] - cand_warm_b[j]); if (warm_repeat_d != 0.0f) warm_repeat_neq++; if (warm_repeat_d > warm_repeat_max_abs) { warm_repeat_max_abs = warm_repeat_d; } } TEST_ASSERT(repeat_nonfinite == 0); TEST_ASSERT(cold_warm_neq == 0); TEST_ASSERT(warm_repeat_neq == 0); fprintf(stderr, "ds4-test: streaming decode-prefill %s cold_warm_neq=%d " "cold_warm_max_abs=%g warm_repeat_neq=%d " "warm_repeat_max_abs=%g top1 canonical=%d decode=%d\n", tc->id, cold_warm_neq, cold_warm_max_abs, warm_repeat_neq, warm_repeat_max_abs, result.ref_top1, result.cand_top1); free(cand_cold); free(cand_warm_a); free(cand_warm_b); } ds4_engine_close(cand_engine); } test_restore_canonical_streaming_prefill(saved_canonical_streaming_prefill); for (int i = 0; i < ncase; i++) test_mpp_eq_case_free(&cases[i]); } #define TEST_LIST_FILES_USER_PROMPT \ "Use the list_files tool to list the current directory exactly once, " \ "then report the listed files and stop." #define TEST_LIST_FILES_TOOL_JSON \ "{\"type\":\"function\",\"function\":{" \ "\"name\":\"list_files\"," \ "\"description\":\"List files in a directory.\"," \ "\"parameters\":{\"type\":\"object\",\"properties\":{" \ "\"path\":{\"type\":\"string\",\"description\":\"Directory path to list.\"}" \ "},\"required\":[\"path\"]}" \ "}}" #define TEST_LIST_FILES_RESULT "[\"README.md\",\"Makefile\",\"ds4.c\",\"metal\"]" static const char *test_tool_call_request_json(void) { return "{" "\"model\":\"deepseek-v4-flash\"," "\"messages\":[{\"role\":\"user\",\"content\":\"" TEST_LIST_FILES_USER_PROMPT "\"}]," "\"tools\":[" TEST_LIST_FILES_TOOL_JSON "]," "\"tool_choice\":\"auto\"," "\"think\":false," "\"temperature\":0," "\"max_tokens\":256," "\"stream\":false" "}"; } static char *test_tool_result_request_json(const char *assistant_content, const tool_call *call) { if (!call || !call->id || !call->id[0]) return NULL; buf b = {0}; buf_puts(&b, "{\"model\":\"deepseek-v4-flash\",\"messages\":[" "{\"role\":\"user\",\"content\":"); json_escape(&b, TEST_LIST_FILES_USER_PROMPT); buf_puts(&b, "},{\"role\":\"assistant\",\"content\":"); json_escape(&b, assistant_content ? assistant_content : ""); buf_puts(&b, ",\"tool_calls\":[{\"id\":"); json_escape(&b, call->id); buf_puts(&b, ",\"type\":\"function\",\"function\":{\"name\":"); json_escape(&b, call->name ? call->name : ""); buf_puts(&b, ",\"arguments\":"); json_escape(&b, call->arguments ? call->arguments : "{}"); buf_puts(&b, "}}]},{\"role\":\"tool\",\"tool_call_id\":"); json_escape(&b, call->id); buf_puts(&b, ",\"content\":"); json_escape(&b, TEST_LIST_FILES_RESULT); buf_puts(&b, "}],\"tools\":[" TEST_LIST_FILES_TOOL_JSON "]," "\"tool_choice\":\"auto\",\"think\":false," "\"temperature\":0,\"max_tokens\":256,\"stream\":false}"); return buf_take(&b); } /* A complete tool call inside unclosed reasoning is recovered directly. The * detector must wait for the complete block, and the parser must keep only the * preceding prose in reasoning_content. */ static void test_think_tool_recovery(void) { const char *generated = "The user wants a directory listing.\n\n" DS4_TOOL_CALLS_START "\n" DS4_INVOKE_START " name=\"list_files\">\n" DS4_PARAM_START " name=\"path\" string=\"true\">." DS4_PARAM_END "\n" DS4_INVOKE_END "\n" DS4_TOOL_CALLS_END; buf text = {0}; size_t scan_from = 0; bool complete = false; for (size_t i = 0; generated[i]; i++) { buf_append(&text, generated + i, 1); complete = complete_tool_call_inside_thinking(text.ptr, text.len, &scan_from); TEST_ASSERT(complete == (generated[i + 1] == '\0')); } TEST_ASSERT(complete); char *content = NULL; char *reasoning = NULL; tool_calls calls = {0}; bool parsed = parse_generated_message_ex(text.ptr, true, &content, &reasoning, &calls); TEST_ASSERT(parsed); TEST_ASSERT(calls.len > 0 && !strcmp(calls.v[0].name, "list_files")); TEST_ASSERT(calls.v[0].arguments && strstr(calls.v[0].arguments, "\"path\": \".\"")); TEST_ASSERT(content && content[0] == '\0'); TEST_ASSERT(reasoning && !strcmp(reasoning, "The user wants a directory listing.")); fprintf(stderr, "ds4-test: think-tool-recovery complete=%d calls=%d name=%s\n", complete ? 1 : 0, calls.len, calls.len ? calls.v[0].name : "-"); free(content); free(reasoning); tool_calls_free(&calls); buf_free(&text); } typedef struct { char *raw; char *content; char *reasoning; tool_calls calls; const char *finish; } test_chat_turn; static void test_chat_turn_free(test_chat_turn *turn) { if (!turn) return; free(turn->raw); free(turn->content); free(turn->reasoning); tool_calls_free(&turn->calls); memset(turn, 0, sizeof(*turn)); } /* Run the same greedy stop/tool-marker/response parse path needed by the server, * while keeping one session alive so the next request genuinely continues from * this sampled turn. */ static bool test_generate_chat_turn(ds4_engine *engine, ds4_session *session, const request *r, test_chat_turn *turn) { memset(turn, 0, sizeof(*turn)); char err[160] = {0}; if (ds4_session_sync(session, &r->prompt, err, sizeof(err)) != 0) { fprintf(stderr, "ds4-test: tool-call sync failed: %s\n", err); turn->finish = "error"; return false; } buf text = {0}; uint64_t rng = 123; const char *finish = "length"; bool saw_tool_start = false; bool saw_tool_end = false; bool decode_ok = true; for (int i = 0; i < r->max_tokens; i++) { int token = ds4_session_sample(session, r->temperature, r->top_k, r->top_p, r->min_p, &rng); if (ds4_token_is_stop_for_think_mode(engine, token, r->think_mode)) { finish = "stop"; break; } if (ds4_session_eval(session, token, err, sizeof(err)) != 0) { finish = "error"; decode_ok = false; break; } size_t piece_len = 0; char *piece = ds4_token_text(engine, token, &piece_len); buf_append(&text, piece, piece_len); free(piece); if (r->has_tools) { observe_tool_markers(text.ptr ? text.ptr : "", &saw_tool_start, &saw_tool_end, NULL); if (saw_tool_end) { finish = "tool_calls"; break; } } } turn->raw = buf_take(&text); turn->finish = finish; if (!decode_ok) { fprintf(stderr, "ds4-test: tool-call decode failed: %s\n", err); return false; } bool recovered = false; bool parsed = parse_generated_message_for_response_for_syntax( r->model_syntax, turn->raw ? turn->raw : "", r->has_tools, saw_tool_start, ds4_think_mode_enabled(r->think_mode), &turn->finish, err, sizeof(err), &turn->content, &turn->reasoning, &turn->calls, &recovered); if (turn->calls.len > 0) turn->finish = "tool_calls"; if (!parsed) { fprintf(stderr, "ds4-test: generated message parse failed: %s recovered=%d raw=%s\n", err, recovered ? 1 : 0, turn->raw ? turn->raw : ""); } return parsed; } static void test_tool_call_quality_one(bool quality) { ds4_engine *engine = test_get_engine(quality); if (!engine) return; server s = {0}; s.engine = engine; pthread_mutex_init(&s.tool_mu, NULL); request first_request = {0}; request second_request = {0}; ds4_session *session = NULL; test_chat_turn first = {0}; test_chat_turn second = {0}; char *second_body = NULL; char err[160] = {0}; bool request_ok = parse_chat_request(engine, &s, test_tool_call_request_json(), 512, 32768, &first_request, err, sizeof(err)); TEST_ASSERT(request_ok); if (!request_ok) goto done; bool session_ok = ds4_session_create(&session, engine, 32768) == 0; TEST_ASSERT(session_ok); if (!session_ok) goto done; bool first_ok = test_generate_chat_turn(engine, session, &first_request, &first); TEST_ASSERT(first_ok); TEST_ASSERT(first.finish && !strcmp(first.finish, "tool_calls")); TEST_ASSERT(first.calls.len == 1); TEST_ASSERT(first.calls.len == 1 && first.calls.v[0].name && !strcmp(first.calls.v[0].name, "list_files")); TEST_ASSERT(first.calls.raw_tool_text && first.calls.raw_tool_text[0]); if (!first_ok || first.calls.len != 1 || !first.calls.v[0].name || strcmp(first.calls.v[0].name, "list_files") || !first.calls.raw_tool_text || !first.calls.raw_tool_text[0]) { goto done; } /* Use the real response-side id assignment and exact sampled-DSML memory. * The same id is serialized on both the assistant call and tool result. */ assign_tool_call_ids(&s, &first.calls, API_OPENAI); TEST_ASSERT(first.calls.v[0].id && first.calls.v[0].id[0]); if (!first.calls.v[0].id || !first.calls.v[0].id[0]) goto done; tool_memory_remember(&s, &first.calls); second_body = test_tool_result_request_json(first.content, &first.calls.v[0]); TEST_ASSERT(second_body != NULL); if (!second_body) goto done; err[0] = '\0'; request_ok = parse_chat_request(engine, &s, second_body, 512, 32768, &second_request, err, sizeof(err)); TEST_ASSERT(request_ok); if (!request_ok) goto done; TEST_ASSERT(second_request.tool_replay.mem == 1); TEST_ASSERT(second_request.tool_replay.disk == 0); TEST_ASSERT(second_request.tool_replay.canonical == 0); TEST_ASSERT(second_request.tool_replay.missing_ids == 0); bool second_ok = test_generate_chat_turn(engine, session, &second_request, &second); TEST_ASSERT(second_ok); TEST_ASSERT(second.finish && !strcmp(second.finish, "stop")); TEST_ASSERT(second.calls.len == 0); TEST_ASSERT(second.content && second.content[0]); fprintf(stderr, "ds4-test: post-tool-result turn1 finish_reason=%s tool_calls=%d " "turn2 finish_reason=%s tool_calls=%d replay_mem=%d\n", first.finish ? first.finish : "-", first.calls.len, second.finish ? second.finish : "-", second.calls.len, second_request.tool_replay.mem); done: free(second_body); test_chat_turn_free(&second); test_chat_turn_free(&first); ds4_session_free(session); request_free(&second_request); request_free(&first_request); tool_memory_free(&s.tool_mem); pthread_mutex_destroy(&s.tool_mu); } static void test_tool_call_quality(void) { fprintf(stderr, "ds4-test: tool-call quality fast path\n"); test_tool_call_quality_one(false); test_close_engine(false); fprintf(stderr, "ds4-test: tool-call quality exact path\n"); test_tool_call_quality_one(true); test_close_engine(true); } /* Greedy speculative decode: capture committed tokens and the largest accepted * chunk, so the caller can confirm the multi-row verify path actually ran. */ static bool test_mtp_capture_speculative(ds4_engine *engine, const ds4_tokens *prompt, int max_tokens, int *out, int *out_len, int *max_chunk) { *out_len = 0; *max_chunk = 0; ds4_session *session = NULL; TEST_ASSERT(ds4_session_create(&session, engine, 32768) == 0); if (!session) return false; char err[160]; bool ok = ds4_session_sync(session, prompt, err, sizeof(err)) == 0; TEST_ASSERT(ok); const int eos = ds4_token_eos(engine); int n = 0; bool stop = false; while (ok && !stop && n < max_tokens) { const int token = ds4_session_argmax(session); if (token == eos) break; int toks[17]; /* base token + draft depth, which the engine clamps to 16 */ const int ntok = ds4_session_eval_speculative_argmax( session, token, max_tokens - n, eos, toks, (int)(sizeof(toks) / sizeof(toks[0])), err, sizeof(err)); if (ntok < 0) { ok = false; TEST_ASSERT(false); break; } if (ntok > *max_chunk) *max_chunk = ntok; for (int j = 0; j < ntok; j++) { if (toks[j] == eos) { stop = true; break; } out[n++] = toks[j]; if (n >= max_tokens) { stop = true; break; } } } *out_len = n; ds4_session_free(session); return ok; } /* Replay toks[] through plain decode and return the largest gap between a * position's argmax logit and the committed token's logit. Correct speculation * commits (near-)argmax tokens (gap ~0); a mis-committed token gives a big gap. */ static bool test_mtp_worst_argmax_gap(ds4_engine *engine, const ds4_tokens *prompt, const int *toks, int n, float *worst_gap, int *worst_at) { *worst_gap = 0.0f; *worst_at = -1; ds4_session *session = NULL; TEST_ASSERT(ds4_session_create(&session, engine, 32768) == 0); if (!session) return false; char err[160]; bool ok = ds4_session_sync(session, prompt, err, sizeof(err)) == 0; TEST_ASSERT(ok); for (int i = 0; ok && i < n; i++) { ds4_token_score best, cur; ok = ds4_session_top_logprobs(session, &best, 1) >= 1 && ds4_session_token_logprob(session, toks[i], &cur) == 1; TEST_ASSERT(ok); if (!ok) break; const float gap = best.logit - cur.logit; if (gap > *worst_gap) { *worst_gap = gap; *worst_at = i; } if (ds4_session_eval(session, toks[i], err, sizeof(err)) != 0) { ok = false; TEST_ASSERT(false); break; } } ds4_session_free(session); return ok; } /* Verbatim-copy task: keeps the model confident (a mis-committed token shows as * a large argmax gap) and draft acceptance high (so the multi-row verify path is * exercised across the generation). */ static const char *test_mtp_copy_prompt(void) { return "Reproduce the following C code EXACTLY, character for character, " "inside a single code block and output nothing else:\n\n" "```c\n" "static uint32_t clamp_u32(uint32_t v, uint32_t lo, uint32_t hi) {\n" " if (v < lo) return lo;\n" " if (v > hi) return hi;\n" " return v;\n" "}\n" "\n" "static uint32_t ring_advance(uint32_t pos, uint32_t cap) {\n" " uint32_t next = pos + 1u;\n" " return next >= cap ? 0u : next;\n" "}\n" "\n" "static int scratch_init(scratch *s, uint32_t ctx_size) {\n" " if (ctx_size == 0u) ctx_size = 1u;\n" " s->ctx_size = ctx_size;\n" " s->comp_cap = ctx_size / 4u + 2u;\n" " s->rows = clamp_u32(s->comp_cap, 1u, 4096u);\n" " s->head = 0u;\n" " return s->rows > 0u ? 0 : -1;\n" "}\n" "```\n"; } #define TEST_MTP_MAXGEN 256 #define TEST_DSPARK_MAXGEN 128 static ds4_engine *test_open_dspark_engine(const char *support_path) { ds4_engine *engine = NULL; ds4_engine_options opt = { .model_path = test_model_path(), #ifdef __APPLE__ .backend = DS4_BACKEND_METAL, #else .backend = DS4_BACKEND_CUDA, #endif .quality = false, .ssd_streaming = test_env_bool("DS4_TEST_SSD_STREAMING"), .ssd_streaming_cold = test_env_bool("DS4_TEST_SSD_STREAMING_COLD"), .ssd_streaming_cache_experts = test_env_u32("DS4_TEST_SSD_STREAMING_CACHE_EXPERTS"), .ssd_streaming_cache_bytes = test_env_gib("DS4_TEST_SSD_STREAMING_CACHE_GB"), .ssd_streaming_preload_experts = test_env_u32("DS4_TEST_SSD_STREAMING_PRELOAD_EXPERTS"), .mtp_path = support_path, .mtp_draft_tokens = 0, .dspark = true, .dspark_confidence_threshold = 0.9f, .dspark_confidence_threshold_set = true, }; const int rc = ds4_engine_open(&engine, &opt); TEST_ASSERT(rc == 0); return rc == 0 ? engine : NULL; } /* Regression for the swapped top-k arguments in metal_graph_verify_suffix_tops * at draft depth > 2. Replays the committed speculative tokens through plain * decode and requires each to be a (near-)argmax: that is the verify invariant, * and unlike comparing token streams it tolerates the near-greedy tie * divergences. Needs an MTP head, so it self-skips without DS4_TEST_MTP. */ static void test_mtp_verify_depth(void) { ds4_engine *engine = test_get_engine(false); if (!engine || !ds4_engine_has_mtp(engine)) { fprintf(stderr, "ds4-test: mtp-verify-depth skipped (set DS4_TEST_MTP to an MTP GGUF)\n"); return; } TEST_ASSERT(ds4_engine_mtp_draft_tokens(engine) > 2); ds4_tokens prompt = {0}; ds4_chat_begin(engine, &prompt); ds4_chat_append_message(engine, &prompt, "user", test_mtp_copy_prompt()); ds4_chat_append_assistant_prefix(engine, &prompt, DS4_THINK_NONE); TEST_ASSERT(prompt.len > 0); int *spec = malloc((size_t)TEST_MTP_MAXGEN * sizeof(*spec)); TEST_ASSERT(spec != NULL); if (spec && prompt.len > 0) { int nspec = 0, max_chunk = 0; const bool ok_spec = test_mtp_capture_speculative(engine, &prompt, TEST_MTP_MAXGEN, spec, &nspec, &max_chunk); TEST_ASSERT(ok_spec); TEST_ASSERT(max_chunk > 1); /* multi-token chunks committed: the multi-row path ran */ TEST_ASSERT(nspec > 128); /* enough output to surface the bug, incl. a spurious-EOS truncation */ float worst_gap = 0.0f; int worst_at = -1; const bool ok_check = test_mtp_worst_argmax_gap(engine, &prompt, spec, nspec, &worst_gap, &worst_at); TEST_ASSERT(ok_check); fprintf(stderr, "ds4-test: mtp-verify-depth nspec=%d max_chunk=%d worst_argmax_gap=%.3f at=%d\n", nspec, max_chunk, worst_gap, worst_at); TEST_ASSERT(worst_gap <= 2.0f); /* correct: ~0; bug: ~21 on the reference model */ } free(spec); ds4_tokens_free(&prompt); } /* Same invariant as the MTP depth smoke, but for the DSpark support model. This * is separate from the fixture because it teacher-forces every committed token * through normal decode and directly checks that DSpark never commits a token * that was not near the target argmax. */ static void test_dspark_verify_depth(void) { const char *support = getenv("DS4_TEST_DSPARK"); if (!support || !support[0]) { fprintf(stderr, "ds4-test: dspark-verify-depth skipped (set DS4_TEST_DSPARK to a DSpark support GGUF)\n"); return; } char *saved_scheduler = test_save_env("DS4_DSPARK_SCHEDULER"); setenv("DS4_DSPARK_SCHEDULER", "0", 1); ds4_engine *engine = test_open_dspark_engine(support); ds4_tokens prompt = {0}; int *spec = NULL; if (engine) { const int draft_depth = ds4_engine_mtp_draft_tokens(engine); TEST_ASSERT(draft_depth > 2); ds4_chat_begin(engine, &prompt); ds4_chat_append_message(engine, &prompt, "user", test_mtp_copy_prompt()); ds4_chat_append_assistant_prefix(engine, &prompt, DS4_THINK_NONE); TEST_ASSERT(prompt.len > 0); spec = malloc((size_t)TEST_DSPARK_MAXGEN * sizeof(*spec)); TEST_ASSERT(spec != NULL); if (draft_depth > 2 && spec && prompt.len > 0) { int nspec = 0, max_chunk = 0; const bool ok_spec = test_mtp_capture_speculative(engine, &prompt, TEST_DSPARK_MAXGEN, spec, &nspec, &max_chunk); TEST_ASSERT(ok_spec); TEST_ASSERT(max_chunk > 1); TEST_ASSERT(nspec > 64); float worst_gap = 0.0f; int worst_at = -1; const bool ok_check = test_mtp_worst_argmax_gap(engine, &prompt, spec, nspec, &worst_gap, &worst_at); TEST_ASSERT(ok_check); fprintf(stderr, "ds4-test: dspark-verify-depth nspec=%d max_chunk=%d draft_depth=%d worst_argmax_gap=%.3f at=%d\n", nspec, max_chunk, draft_depth, worst_gap, worst_at); TEST_ASSERT(worst_gap <= 2.0f); } } free(spec); ds4_tokens_free(&prompt); ds4_engine_close(engine); test_restore_env("DS4_DSPARK_SCHEDULER", saved_scheduler); } #endif static void test_server_unit_group(void) { ds4_server_unit_tests_run(); } typedef void (*test_fn)(void); typedef struct { const char *flag; const char *name; const char *desc; test_fn fn; } ds4_test_entry; static const ds4_test_entry test_entries[] = { #ifndef DS4_NO_GPU {"--long-context", "long-context", "long-context story fact-recall regression", test_long_story_fact_recall}, {"--tool-call-quality", "tool-call-quality", "model tool call and post-result stop regression", test_tool_call_quality}, {"--think-tool-recovery", "think-tool-recovery", "recover a complete tool call emitted inside unclosed reasoning", test_think_tool_recovery}, {"--logprob-vectors", "logprob-vectors", "official API top-logprob vector comparison on the standard Metal path", test_official_logprob_vectors}, {"--metal-ssd-streaming-cache-pressure", "metal-ssd-streaming-cache-pressure", "Metal SSD-streaming layer-batched decode cache-pressure repro for issue #384", test_metal_ssd_streaming_cache_pressure}, {"--local-golden-vectors", "local-golden-vectors", "local top-k/logit drift regression for long Metal prefill", test_local_golden_vectors}, {"--metal-short-prefill", "metal-short-prefill", "Metal ratio-4 short prefill regression", test_metal_short_prefill_ratio4}, {"--metal-kernels", "metal-kernels", "isolated Metal kernel numeric regressions", test_metal_kernel_group}, {"--metal-tensor-equivalence", "metal-tensor-equivalence", "fast/quality Metal prompt-logit and greedy equivalence", test_metal_mpp_equivalence}, {"--streaming-decode-prefill-correctness", "streaming-decode-prefill-correctness", "streaming decode-style cold prefill drift and repeatability", test_streaming_decode_prefill_correctness}, {"--mtp-verify-depth", "mtp-verify-depth", "MTP speculative verify commits autoregressive-identical tokens at draft depth > 2", test_mtp_verify_depth}, {"--dspark-verify-depth", "dspark-verify-depth", "DSpark speculative verify commits autoregressive-identical tokens at draft depth > 2", test_dspark_verify_depth}, #endif {"--server", "server", "server parser/rendering/cache unit tests", test_server_unit_group}, }; static void test_print_help(const char *prog) { printf("Usage: %s [--all | TEST...]\n\n", prog); puts("Tests:"); puts(" --all"); puts(" Run every test. This is the default, ordered from slower to faster."); for (size_t i = 0; i < sizeof(test_entries) / sizeof(test_entries[0]); i++) { printf(" %-20s %s\n", test_entries[i].flag, test_entries[i].desc); } puts(" --list"); puts(" Print test names only."); #ifndef DS4_NO_GPU puts(" --metal-mpp-equivalence"); puts(" Compatibility alias for --metal-tensor-equivalence."); #endif puts(" -h, --help"); puts(" Show this help."); puts("\nEnvironment:"); puts(" DS4_TEST_MODEL=FILE Model path. Default: ds4flash.gguf"); puts(" DS4_TEST_BACKEND=cpu Run model tests on CPU instead of Metal/CUDA."); puts(" DS4_TEST_SSD_STREAMING=1 Run model tests through Metal SSD streaming."); puts(" DS4_TEST_SSD_STREAMING_CACHE_GB=N Streaming routed expert cache in GiB."); puts(" DS4_TEST_SSD_STREAMING_CACHE_EXPERTS=N Streaming routed expert cache count."); puts(" DS4_TEST_SSD_STREAMING_COLD=1 Skip streaming hot expert preload."); puts(" DS4_METAL_DISABLE_STREAMING_COLD_DECODE_PREFILL=1 Force canonical streamed cold prefill."); puts(" DS4_TEST_LONG_PROMPT=FILE Rendered long-context story fact prompt."); puts(" DS4_TEST_VECTOR_FILE=FILE Official fixture. Default: flash-0731/official.vec."); puts(" DS4_TEST_LOCAL_GOLDEN_FILE=FILE Local fixture. Default: flash-0731/local-golden.vec."); puts(" DS4_TEST_MPP_EQ_CASE=NAME Run only Tensor equivalence cases whose id contains NAME."); puts(" DS4_TEST_MTP=FILE Legacy MTP support GGUF for --mtp-verify-depth."); puts(" DS4_TEST_DSPARK=FILE DSpark support GGUF for --dspark-verify-depth."); } static const ds4_test_entry *test_find_entry(const char *arg) { #ifndef DS4_NO_GPU if (!strcmp(arg, "--metal-mpp-equivalence")) { arg = "--metal-tensor-equivalence"; } #endif for (size_t i = 0; i < sizeof(test_entries) / sizeof(test_entries[0]); i++) { if (!strcmp(arg, test_entries[i].flag)) return &test_entries[i]; } return NULL; } static void test_run_entry(const ds4_test_entry *entry) { int before = test_failures; fprintf(stderr, "%s:\n", entry->name); entry->fn(); fprintf(stderr, "%s: ", entry->name); ds4_log(stderr, test_failures == before ? DS4_LOG_OK : DS4_LOG_ERROR, "%s", test_failures == before ? "OK" : "ERR"); fputc('\n', stderr); } int main(int argc, char **argv) { bool run_all = argc == 1; bool selected[sizeof(test_entries) / sizeof(test_entries[0])] = {0}; for (int i = 1; i < argc; i++) { if (!strcmp(argv[i], "--all")) { run_all = true; } else if (!strcmp(argv[i], "--list")) { for (size_t j = 0; j < sizeof(test_entries) / sizeof(test_entries[0]); j++) { puts(test_entries[j].flag); } return 0; } else if (!strcmp(argv[i], "-h") || !strcmp(argv[i], "--help")) { test_print_help(argv[0]); return 0; } else { const ds4_test_entry *entry = test_find_entry(argv[i]); if (!entry) { fprintf(stderr, "ds4-test: unknown test switch: %s\n", argv[i]); test_print_help(argv[0]); return 2; } selected[(size_t)(entry - test_entries)] = true; } } if (run_all) { for (size_t i = 0; i < sizeof(test_entries) / sizeof(test_entries[0]); i++) { test_run_entry(&test_entries[i]); } } else { for (size_t i = 0; i < sizeof(test_entries) / sizeof(test_entries[0]); i++) { if (selected[i]) test_run_entry(&test_entries[i]); } } #ifndef DS4_NO_GPU test_close_engines(); #endif if (test_failures) { fprintf(stderr, "ds4 tests: %d failure(s)\n", test_failures); return 1; } puts("ds4 tests: ok"); return 0; }