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vulkan: Extend rope fusions to allow mrope (#18264)

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Extend the test-backend-ops tests as well.
This commit is contained in:
Jeff Bolz
2025-12-22 11:03:13 -06:00
committed by GitHub
parent 6ce863c803
commit e3b35ddf1c
4 changed files with 82 additions and 25 deletions
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tests/test-backend-ops.cpp
+61 -18
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@@ -2329,11 +2329,13 @@ struct test_set_rows : public test_case {
struct test_rope_set_rows : public test_case {
const ggml_type type;
const ggml_type type_idx;
const std::array<int64_t, 4> ne;
const std::array<int64_t, 4> ne_a;
int mode;
const int n_ctx{512};
const int n_dims{128};
std::string vars() override {
return VARS_TO_STR4(type, type_idx, ne, mode);
return VARS_TO_STR4(type, type_idx, ne_a, mode);
}
std::string op_desc(ggml_tensor * t) override {
@@ -2345,24 +2347,51 @@ struct test_rope_set_rows : public test_case {
test_rope_set_rows(ggml_type type,
ggml_type type_idx,
std::array<int64_t, 4> ne,
std::array<int64_t, 4> ne_a,
int mode)
: type(type), type_idx(type_idx), ne(ne), mode(mode) {}
: type(type), type_idx(type_idx), ne_a(ne_a), mode(mode) {}
ggml_tensor * build_graph(ggml_context * ctx) override {
ggml_tensor * src = ggml_new_tensor_4d(ctx, GGML_TYPE_F32, ne[0], ne[1], ne[2], 1);
ggml_set_name(src, "src");
ggml_tensor * a = ggml_new_tensor_4d(ctx, GGML_TYPE_F32, ne_a[0], ne_a[1], ne_a[2], 1);
ggml_set_name(a, "a");
ggml_tensor * pos = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, ne[2]);
const bool is_mrope = mode & GGML_ROPE_TYPE_MROPE;
const bool is_vision = mode == GGML_ROPE_TYPE_VISION;
ggml_tensor * rope = ggml_rope(ctx, src, pos, ne[0], mode);
ggml_tensor * pos;
if (is_mrope || is_vision) {
pos = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, ne_a[2] * 4);
} else {
pos = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, ne_a[2]);
}
ggml_set_name(pos, "pos");
ggml_tensor * view = ggml_view_2d(ctx, rope, ne[0] * ne[1], ne[2], rope->nb[2], 0);
float fs = 1.4245f;
float ef = 0.7465f;
float af = 1.4245f;
ggml_tensor * freq = nullptr;
ggml_tensor * dst = ggml_new_tensor_4d(ctx, type, ne[0] * ne[1], ne[2] * ne[3], 1, 1);
ggml_tensor * rope = nullptr;
if (is_mrope) {
if (is_vision) {
GGML_ASSERT(n_dims/4 > 0);
int rope_sections[4] = {n_dims/4, n_dims/4, 0, 0}; // Vision-RoPE only use first two dimension for image (x, y) coordinate
rope = ggml_rope_multi(ctx, a, pos, freq, n_dims/2, rope_sections, mode, 0, 10000.0f, fs, ef, af, 1.0f, 1.0f);
} else {
GGML_ASSERT(n_dims/3 > 0);
int rope_sections[4] = {n_dims/3, n_dims/3, n_dims/3, 0};
rope = ggml_rope_multi(ctx, a, pos, freq, n_dims, rope_sections, mode, 0, 10000.0f, fs, ef, af, 1.0f, 1.0f);
}
} else {
rope = ggml_rope(ctx, a, pos, ne_a[0], mode);
}
ggml_tensor * view = ggml_view_2d(ctx, rope, ne_a[0] * ne_a[1], ne_a[2], rope->nb[2], 0);
ggml_tensor * dst = ggml_new_tensor_4d(ctx, type, ne_a[0] * ne_a[1], ne_a[2] * ne_a[3], 1, 1);
ggml_set_name(dst, "dst");
ggml_tensor * row_idxs = ggml_new_tensor_3d(ctx, type_idx, ne[2], 1, 1);
ggml_tensor * row_idxs = ggml_new_tensor_3d(ctx, type_idx, ne_a[2], 1, 1);
ggml_set_name(row_idxs, "row_idxs");
ggml_tensor * out = ggml_set_rows(ctx, dst, view, row_idxs);
@@ -2373,14 +2402,26 @@ struct test_rope_set_rows : public test_case {
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 (t->type == GGML_TYPE_I64 || t->type == GGML_TYPE_I32) {
if (strcmp(t->name, "row_idxs") == 0) {
if (ggml_is_view_op(t->op)) {
continue;
}
init_set_rows_row_ids(t, ne[2]);
init_set_rows_row_ids(t, ne_a[2]);
} else if (t->type == GGML_TYPE_I32) {
// pos
const int num_pos_ids = (mode & GGML_ROPE_TYPE_MROPE) ? ne_a[2] * 4 : ne_a[2];
std::vector<int> data(num_pos_ids);
for (int i = 0; i < num_pos_ids; i++) {
data[i] = rand() % n_ctx;
}
ggml_backend_tensor_set(t, data.data(), 0, num_pos_ids * sizeof(int));
} else {
init_tensor_uniform(t);
if (t->ne[0] == n_dims/2) {
// frequency factors in the range [0.9f, 1.1f]
init_tensor_uniform(t, 0.9f, 1.1f);
} else {
init_tensor_uniform(t);
}
}
}
}
@@ -6854,10 +6895,12 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
}
}
for (int mode : { GGML_ROPE_TYPE_NORMAL, GGML_ROPE_TYPE_NEOX }) {
for (int mode : { GGML_ROPE_TYPE_NORMAL, GGML_ROPE_TYPE_NEOX, GGML_ROPE_TYPE_MROPE, GGML_ROPE_TYPE_VISION }) {
for (ggml_type type : {GGML_TYPE_F16, GGML_TYPE_F32}) {
test_cases.emplace_back(new test_rope_set_rows(type, GGML_TYPE_I64, { 128, 32, 1, 100 }, mode));
test_cases.emplace_back(new test_rope_set_rows(type, GGML_TYPE_I64, { 128, 32, 512, 1 }, mode));
for (int ne2 : {1, 8, 512}) {
test_cases.emplace_back(new test_rope_set_rows(type, GGML_TYPE_I64, { 128, 32, ne2, 1 }, mode));
test_cases.emplace_back(new test_rope_set_rows(type, GGML_TYPE_I64, { 128, 32, ne2, 3 }, mode));
}
}
}