mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2026-09-11 04:56:56 +02:00
tests : drop SYCL special-casing in test-backend-ops.cpp (#28688)
This commit is contained in:
+15
-124
@@ -462,17 +462,9 @@ static std::string var_to_str(ggml_scale_mode mode) {
|
||||
#define VARS_TO_STR16(a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p) VAR_TO_STR(a) + "," + VARS_TO_STR15(b, c, d, e, f, g, h, i, j, k, l, m, n, o, p)
|
||||
#define VARS_TO_STR17(a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q) VAR_TO_STR(a) + "," + VARS_TO_STR16(b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q)
|
||||
|
||||
#ifdef GGML_USE_SYCL
|
||||
static bool inline _isinf(float f) {
|
||||
return (*(uint32_t *)&f & 0x7fffffff) == 0x7f800000;
|
||||
}
|
||||
#else
|
||||
static bool inline _isinf(float f) { return std::isinf(f); }
|
||||
#endif
|
||||
|
||||
// accept FLT_MAX as infinity
|
||||
static bool isinf_or_max(float f) {
|
||||
return _isinf(f) || f == FLT_MAX || f == -FLT_MAX;
|
||||
return std::isinf(f) || f == FLT_MAX || f == -FLT_MAX;
|
||||
}
|
||||
|
||||
static bool ggml_is_view_op(enum ggml_op op) {
|
||||
@@ -4831,51 +4823,6 @@ struct test_mul_mat : public test_case {
|
||||
}
|
||||
};
|
||||
|
||||
#define P 1.0f
|
||||
#define N -1.0f
|
||||
|
||||
// constant Hadamard matrix via Paley I construction
|
||||
static constexpr float H12[12][12] = {
|
||||
{ P, P, P, P, P, P, P, P, P, P, P, P },
|
||||
{ P, N, P, N, P, P, P, N, N, N, P, N },
|
||||
{ P, N, N, P, N, P, P, P, N, N, N, P },
|
||||
{ P, P, N, N, P, N, P, P, P, N, N, N },
|
||||
{ P, N, P, N, N, P, N, P, P, P, N, N },
|
||||
{ P, N, N, P, N, N, P, N, P, P, P, N },
|
||||
{ P, N, N, N, P, N, N, P, N, P, P, P },
|
||||
{ P, P, N, N, N, P, N, N, P, N, P, P },
|
||||
{ P, P, P, N, N, N, P, N, N, P, N, P },
|
||||
{ P, P, P, P, N, N, N, P, N, N, P, N },
|
||||
{ P, N, P, P, P, N, N, N, P, N, N, P },
|
||||
{ P, P, N, P, P, P, N, N, N, P, N, N }
|
||||
};
|
||||
|
||||
static constexpr float H20[20][20] = {
|
||||
{ P, P, P, P, P, P, P, P, P, P, P, P, P, P, P, P, P, P, P, P },
|
||||
{ P, N, P, N, N, P, P, P, P, N, P, N, P, N, N, N, N, P, P, N },
|
||||
{ P, N, N, P, N, N, P, P, P, P, N, P, N, P, N, N, N, N, P, P },
|
||||
{ P, P, N, N, P, N, N, P, P, P, P, N, P, N, P, N, N, N, N, P },
|
||||
{ P, P, P, N, N, P, N, N, P, P, P, P, N, P, N, P, N, N, N, N },
|
||||
{ P, N, P, P, N, N, P, N, N, P, P, P, P, N, P, N, P, N, N, N },
|
||||
{ P, N, N, P, P, N, N, P, N, N, P, P, P, P, N, P, N, P, N, N },
|
||||
{ P, N, N, N, P, P, N, N, P, N, N, P, P, P, P, N, P, N, P, N },
|
||||
{ P, N, N, N, N, P, P, N, N, P, N, N, P, P, P, P, N, P, N, P },
|
||||
{ P, P, N, N, N, N, P, P, N, N, P, N, N, P, P, P, P, N, P, N },
|
||||
{ P, N, P, N, N, N, N, P, P, N, N, P, N, N, P, P, P, P, N, P },
|
||||
{ P, P, N, P, N, N, N, N, P, P, N, N, P, N, N, P, P, P, P, N },
|
||||
{ P, N, P, N, P, N, N, N, N, P, P, N, N, P, N, N, P, P, P, P },
|
||||
{ P, P, N, P, N, P, N, N, N, N, P, P, N, N, P, N, N, P, P, P },
|
||||
{ P, P, P, N, P, N, P, N, N, N, N, P, P, N, N, P, N, N, P, P },
|
||||
{ P, P, P, P, N, P, N, P, N, N, N, N, P, P, N, N, P, N, N, P },
|
||||
{ P, P, P, P, P, N, P, N, P, N, N, N, N, P, P, N, N, P, N, N },
|
||||
{ P, N, P, P, P, P, N, P, N, P, N, N, N, N, P, P, N, N, P, N },
|
||||
{ P, N, N, P, P, P, P, N, P, N, P, N, N, N, N, P, P, N, N, P },
|
||||
{ P, P, N, N, P, P, P, P, N, P, N, P, N, N, N, N, P, P, N, N }
|
||||
};
|
||||
|
||||
#undef P
|
||||
#undef N
|
||||
|
||||
// GGML_HINT_SRC0_IS_HADAMARD
|
||||
struct test_mul_mat_hadamard : public test_mul_mat {
|
||||
test_mul_mat_hadamard(ggml_type type_a = GGML_TYPE_F32, ggml_type type_b = GGML_TYPE_F32,
|
||||
@@ -4900,58 +4847,20 @@ struct test_mul_mat_hadamard : public test_mul_mat {
|
||||
void initialize_tensors(ggml_context * ctx) override {
|
||||
for (ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) {
|
||||
if (strcmp(t->name, "a") == 0) {
|
||||
const int64_t n_cols = t->ne[0];
|
||||
const int64_t n_rows = ggml_nrows(t);
|
||||
const int64_t n_cols = t->ne[0];
|
||||
const int64_t n_rows = ggml_nrows(t);
|
||||
std::vector<float> data(n_cols * n_rows);
|
||||
float scale = 1.0f / sqrtf((float) n_cols);
|
||||
|
||||
auto is_pow2 = [](const int64_t a) {
|
||||
return (a > 0) && ((a & (a - 1)) == 0);
|
||||
};
|
||||
#ifdef GGML_USE_SYCL
|
||||
const bool is_kronecker =
|
||||
((n_cols % 12 == 0) && is_pow2(n_cols / 12)) || ((n_cols % 20 == 0) && is_pow2(n_cols / 20));
|
||||
#else
|
||||
const bool is_kronecker = false;
|
||||
#endif
|
||||
if (is_kronecker) {
|
||||
const int64_t B = (n_cols % 12 == 0 && is_pow2(n_cols / 12)) ? 12 : 20;
|
||||
for (int64_t r = 0; r < n_rows; r++) {
|
||||
float * row_data = data.data() + r * n_cols;
|
||||
const int64_t r_mod = r % n_cols;
|
||||
const int64_t r_b = r_mod / B;
|
||||
const int64_t r_m = r_mod % B;
|
||||
|
||||
for (int64_t i = 0; i < n_cols; i++) {
|
||||
const int64_t c_b = i / B;
|
||||
const int64_t c_m = i % B;
|
||||
|
||||
int pop = 0;
|
||||
int64_t val = r_b & c_b;
|
||||
while (val) {
|
||||
pop += (val & 1);
|
||||
val >>= 1;
|
||||
}
|
||||
const float sign_m = (pop % 2 == 0) ? 1.0f : -1.0f;
|
||||
const float sign_b = (B == 12) ? H12[c_m][r_m] : H20[c_m][r_m];
|
||||
|
||||
row_data[i] = scale * sign_b * sign_m;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
else if (is_pow2(n_cols)) {
|
||||
for (int64_t r = 0; r < n_rows; r++) {
|
||||
float * row_data = data.data() + r * n_cols;
|
||||
for (int64_t i = 0; i < n_cols; i++) {
|
||||
int pop_cnt = 0;
|
||||
int64_t val = r & i;
|
||||
while (val) {
|
||||
pop_cnt += (val & 1);
|
||||
val >>= 1;
|
||||
}
|
||||
row_data[i] = (pop_cnt % 2 == 0) ? scale : -scale;
|
||||
float scale = 1.0f / sqrtf((float)n_cols);
|
||||
for (int64_t r = 0; r < n_rows; r++) {
|
||||
float * row_data = data.data() + r * n_cols;
|
||||
for (int64_t i = 0; i < n_cols; i++) {
|
||||
int pop = 0;
|
||||
int64_t val = r & i;
|
||||
while (val) {
|
||||
pop += (val & 1);
|
||||
val >>= 1;
|
||||
}
|
||||
row_data[i] = (pop % 2 == 0) ? scale : -scale;
|
||||
}
|
||||
}
|
||||
ggml_backend_tensor_set(t, data.data(), 0, data.size() * sizeof(float));
|
||||
@@ -9716,16 +9625,7 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 256, 512, 256)); // many rows
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 32, 1, 32)); // too small (N<64)
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 1024, 1, 1024)); // too big (N>512)
|
||||
#ifdef GGML_USE_SYCL
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 384, 1, 384)); // m=12 (N=384)
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 384, 32, 384)); // m=12 (batch)
|
||||
test_cases.emplace_back(
|
||||
new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 384, 4, 384, { 2, 3 })); // m=12 (multi-dim)
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 768, 1, 768)); // m=12 (N=768)
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 640, 1, 640)); // m=20 (N=640)
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 640, 32, 640)); // m=20 (batch)
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 1280, 1, 1280)); // m=20 (N=1280)
|
||||
#endif
|
||||
|
||||
#if 0
|
||||
// > 4GB A matrix. Too slow to be enabled by default.
|
||||
test_cases.emplace_back(new test_mul_mat(GGML_TYPE_F16, GGML_TYPE_F16, 900000, 3, 2592, {1, 1}, {1, 1}));
|
||||
@@ -11011,16 +10911,7 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_perf() {
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 128, 2048, 128));
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 256, 2048, 256));
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 512, 2048, 512));
|
||||
#ifdef GGML_USE_SYCL
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 384, 1, 384)); // m=12 (N=384)
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 384, 32, 384)); // m=12 (batch)
|
||||
test_cases.emplace_back(
|
||||
new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 384, 4, 384, { 2, 3 })); // m=12 (multi-dim)
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 768, 1, 768)); // m=12 (N=768)
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 640, 1, 640)); // m=20 (N=640)
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 640, 32, 640)); // m=20 (batch)
|
||||
test_cases.emplace_back(new test_mul_mat_hadamard(GGML_TYPE_F32, GGML_TYPE_F32, 1280, 1, 1280)); // m=20 (N=1280)
|
||||
#endif
|
||||
|
||||
test_cases.emplace_back(new test_solve_tri(GGML_TYPE_F32, { 64, 64, 4, 4 }, { 32, 64, 4, 4 }));
|
||||
test_cases.emplace_back(new test_solve_tri(GGML_TYPE_F32, { 128, 128, 4, 2 }, { 32, 128, 4, 2 }));
|
||||
// qwen3next with CHUNK_SIZE 64
|
||||
|
||||
Reference in New Issue
Block a user