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sync : ggml (conv 1d + 2d updates, UB fixes) (#3468)
* sync : ggml (conv 1d + 2d updates) ggml-ci * ggml : fix UB in q5_0 and q5_1 quantize code ggml.c:1033:39: runtime error: left shift of 1 by 31 places cannot be represented in type 'int' SUMMARY: UndefinedBehaviorSanitizer: undefined-behavior ggml.c:1081:39: runtime error: left shift of 1 by 31 places cannot be represented in type 'int' SUMMARY: UndefinedBehaviorSanitizer: undefined-behavior ggml-ci * tests : fix UB in test-quantize-perf
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13
ggml.h
13
ggml.h
@ -401,10 +401,14 @@ extern "C" {
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GGML_OP_CLAMP,
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GGML_OP_CONV_1D,
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GGML_OP_CONV_2D,
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GGML_OP_CONV_TRANSPOSE_1D,
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GGML_OP_CONV_TRANSPOSE_2D,
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GGML_OP_POOL_1D,
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GGML_OP_POOL_2D,
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GGML_OP_CONV_1D_STAGE_0, // internal
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GGML_OP_CONV_1D_STAGE_1, // internal
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GGML_OP_UPSCALE, // nearest interpolate
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GGML_OP_FLASH_ATTN,
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@ -1386,6 +1390,14 @@ extern "C" {
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int s,
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int d);
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GGML_API struct ggml_tensor * ggml_conv_transpose_1d(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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struct ggml_tensor * b,
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int s0,
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int p0,
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int d0);
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GGML_API struct ggml_tensor * ggml_conv_2d(
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struct ggml_context * ctx,
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struct ggml_tensor * a,
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@ -1759,6 +1771,7 @@ extern "C" {
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GGML_OPT_NO_CONTEXT,
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GGML_OPT_INVALID_WOLFE,
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GGML_OPT_FAIL,
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GGML_OPT_CANCEL,
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GGML_LINESEARCH_FAIL = -128,
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GGML_LINESEARCH_MINIMUM_STEP,
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@ -69,7 +69,6 @@ inline static int32_t vaddvq_s32(int32x4_t v) {
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// 2-6 bit quantization in super-blocks
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//
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//
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// ===================== Helper functions
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//
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@ -348,7 +347,6 @@ void quantize_row_q2_K_reference(const float * restrict x, block_q2_K * restrict
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const float q4scale = 15.f;
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for (int i = 0; i < nb; i++) {
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float max_scale = 0; // as we are deducting the min, scales are always positive
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float max_min = 0;
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for (int j = 0; j < QK_K/16; ++j) {
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@ -208,26 +208,6 @@ static struct ggml_tensor * get_random_tensor_i32(
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return result;
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}
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static void print_elements(const char* label, const struct ggml_tensor * t) {
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if (!t) {
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printf("%s: %s = null\n", __func__, label);
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return;
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}
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const int nelements = ggml_nelements(t);
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printf("%s: %s = [", __func__, label);
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for (int k = 0; k < nelements; ++k) {
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if (k > 0) { printf(", "); }
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printf("%.5f", ggml_get_f32_1d(t, k));
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}
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printf("] shape: [");
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for (int k = 0; k < t->n_dims; ++k) {
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if (k > 0) { printf(", "); }
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printf("%d", (int)t->ne[k]);
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}
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printf("]\n");
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}
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static bool check_gradient(
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const char * op_name,
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struct ggml_context * ctx0,
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@ -40,27 +40,6 @@ static float frand(void) {
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return (float)rand()/(float)RAND_MAX;
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}
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static int irand(int n) {
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return rand()%n;
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}
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static void get_random_dims(int64_t * dims, int ndims) {
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dims[0] = dims[1] = dims[2] = dims[3] = 1;
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for (int i = 0; i < ndims; i++) {
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dims[i] = 1 + irand(4);
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}
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}
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static void get_random_dims_minmax(int64_t * dims, int ndims, int min, int max) {
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dims[0] = dims[1] = dims[2] = dims[3] = 1;
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for (int i = 0; i < ndims; i++) {
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dims[i] = min + irand(max-min);
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}
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}
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static struct ggml_tensor * get_random_tensor(
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struct ggml_context * ctx0, int ndims, int64_t ne[], float fmin, float fmax
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) {
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@ -106,14 +85,6 @@ static struct ggml_tensor * get_random_tensor(
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return result;
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}
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static float get_element(const struct ggml_tensor * t, int idx) {
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return ((float *)t->data)[idx];
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}
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static void set_element(struct ggml_tensor * t, int idx, float value) {
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((float *)t->data)[idx] = value;
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}
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int main(void) {
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struct ggml_init_params params = {
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/* .mem_size = */ 1024*1024*1024,
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@ -76,22 +76,21 @@ static void * align_with_offset(void * ptr, int offset) {
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return (char *) std::align(MAX_ALIGNMENT, MAX_ALIGNMENT, ptr, dummy_size) + offset;
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}
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static void benchmark_function(size_t size, size_t q_size, int64_t iterations, const std::function<size_t(void)> & function) {
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static void benchmark_function(size_t size, size_t q_size, int64_t iterations, const std::function<float(void)> & func) {
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int64_t min_time_us = INT64_MAX;
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int64_t total_time_us = 0;
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int64_t min_time_cycles = INT64_MAX;
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int64_t total_time_cycles = 0;
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for (int i = 0; i < WARMUP; i++) {
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function();
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func();
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}
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for (int i = 0; i < iterations; i++) {
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const int64_t start_time = ggml_time_us();
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const int64_t start_cycles = cpu_cycles();
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function();
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func();
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const int64_t end_cycles = cpu_cycles();
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const int64_t end_time = ggml_time_us();
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@ -245,9 +244,9 @@ int main(int argc, char * argv[]) {
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std::vector<uint8_t> test_data1_v(largest*4 + MAX_ALIGNMENT*2);
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std::vector<uint8_t> test_data2_v(largest*4 + MAX_ALIGNMENT*2);
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std::vector<uint8_t> test_q1_v(largest*4 + MAX_ALIGNMENT*2);
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std::vector<uint8_t> test_q2_v(largest*4 + MAX_ALIGNMENT*2);
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std::vector<uint8_t> test_out_v(largest*4 + MAX_ALIGNMENT*2);
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std::vector<uint8_t> test_q1_v (largest*4 + MAX_ALIGNMENT*2);
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std::vector<uint8_t> test_q2_v (largest*4 + MAX_ALIGNMENT*2);
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std::vector<uint8_t> test_out_v (largest*4 + MAX_ALIGNMENT*2);
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float * test_data1 = (float *) align_with_offset(test_data1_v.data(), params.alignment_offset);
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float * test_data2 = (float *) align_with_offset(test_data2_v.data(), params.alignment_offset);
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@ -283,7 +282,7 @@ int main(int argc, char * argv[]) {
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printf(" quantize_row_q_reference\n");
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for (size_t size : params.test_sizes) {
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printf(" %zu values (%.2f MB)\n", size, 4*size/(float)(1024*1024));
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auto quantize_fn = [&](void ) {
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auto quantize_fn = [&](void) -> float {
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qfns.from_float_reference(test_data1, test_q1, size);
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return test_q1[0];
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};
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@ -297,7 +296,7 @@ int main(int argc, char * argv[]) {
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printf(" quantize_row_q\n");
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for (size_t size : params.test_sizes) {
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printf(" %zu values (%.2f MB)\n", size, 4*size/(float)(1024*1024));
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auto quantize_fn = [&](void ) {
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auto quantize_fn = [&](void) -> float {
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qfns.from_float(test_data1, test_q1, size);
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return test_q1[0];
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};
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@ -312,7 +311,7 @@ int main(int argc, char * argv[]) {
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qfns.from_float(test_data1, test_q1, largest);
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for (size_t size : params.test_sizes) {
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printf(" %zu values (%.2f MB)\n", size, 4*size/(float)(1024*1024));
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auto quantize_fn = [&](void ) {
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auto quantize_fn = [&](void) -> float {
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qfns.to_float(test_q1, test_out, size);
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return test_out[0];
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};
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@ -326,7 +325,7 @@ int main(int argc, char * argv[]) {
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printf(" quantize_row_q_dot\n");
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for (size_t size : params.test_sizes) {
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printf(" %zu values (%.2f MB)\n", size, 4*size/(float)(1024*1024));
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auto quantize_fn = [&](void ) {
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auto quantize_fn = [&](void) -> float {
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auto vdot = ggml_internal_get_type_traits(qfns.vec_dot_type);
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vdot.from_float(test_data1, test_q1, size);
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return test_q1[0];
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@ -343,7 +342,7 @@ int main(int argc, char * argv[]) {
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qfns.from_float(test_data2, test_q2, largest);
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for (size_t size : params.test_sizes) {
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printf(" %zu values (%.2f MB)\n", size, 4*size/(float)(1024*1024));
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auto quantize_fn = [&](void ) {
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auto quantize_fn = [&](void) -> float {
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float result;
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qfns.vec_dot(size, &result, test_q1, test_q2);
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return result;
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