vk_pipeline pipeline_rope_norm_f32, pipeline_rope_norm_f16, pipeline_rope_norm_f32_f16;
vk_pipeline pipeline_rope_neox_f32, pipeline_rope_neox_f16, pipeline_rope_neox_f32_f16;
- vk_pipeline pipeline_rope_multi_f32, pipeline_rope_multi_f16;
+ vk_pipeline pipeline_rope_multi_f32, pipeline_rope_multi_f16, pipeline_rope_multi_f32_f16;
vk_pipeline pipeline_rope_vision_f32, pipeline_rope_vision_f16;
vk_pipeline pipeline_argsort_f32[num_argsort_pipelines];
vk_pipeline pipeline_argsort_large_f32[num_argsort_pipelines];
ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32_f16, "rope_norm_f32_f16", rope_norm_f32_f16_rte_len, rope_norm_f32_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32_f16, "rope_neox_f32_f16", rope_neox_f32_f16_rte_len, rope_neox_f32_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+ ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f32_f16, "rope_multi_f32_f16", rope_multi_f32_f16_rte_len, rope_multi_f32_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
} else {
ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_len, rope_norm_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_len, rope_neox_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32_f16, "rope_norm_f32_f16", rope_norm_f32_f16_len, rope_norm_f32_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32_f16, "rope_neox_f32_f16", rope_neox_f32_f16_len, rope_neox_f32_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+ ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f32_f16, "rope_multi_f32_f16", rope_multi_f32_f16_len, rope_multi_f32_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
}
for (uint32_t i = 0; i < num_argsort_pipelines; ++i) {
if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
return ctx->device->pipeline_rope_multi_f32;
}
+ if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F16) {
+ return ctx->device->pipeline_rope_multi_f32_f16;
+ }
if (src0->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F16) {
return ctx->device->pipeline_rope_multi_f16;
}
return false;
}
- // Only norm/neox shaders have the fusion code
+ // Only norm/neox/mrope shaders have the fusion code
const int mode = ((const int32_t *) rope->op_params)[2];
- if (mode != GGML_ROPE_TYPE_NORMAL && mode != GGML_ROPE_TYPE_NEOX) {
+ if (mode != GGML_ROPE_TYPE_NORMAL && mode != GGML_ROPE_TYPE_NEOX && mode != GGML_ROPE_TYPE_MROPE) {
return false;
}
uint idst = i1*ne0 + i0;
const uint ix = rope_a_coord(i0, i01, i02, p);
- // Fusion optimization: ROPE + VIEW + SET_ROWS..
- // The rope output is viewed as a 1D tensor and offset based on a row index in data_i.
+ // Fusion optimization: ROPE + VIEW + SET_ROWS.
+ // The rope output is viewed as a 1D tensor and offset based on a row index in rope_data_i.
if (p.set_rows_stride != 0) {
idst = i01*ne0 + i0;
idst += rope_data_i[i02].x * p.set_rows_stride;
uint idst = i1*ne0 + i0/2;
const uint ix = rope_a_coord(i0/2, i01, i02, p);
- // Fusion optimization: ROPE + VIEW + SET_ROWS..
+ // Fusion optimization: ROPE + VIEW + SET_ROWS.
// The rope output is viewed as a 1D tensor and offset based on a row index in rope_data_i.
if (p.set_rows_stride != 0) {
idst = i01*ne0 + i0/2;
const uint i01 = i1 % ne1;
const uint i02 = i1 / ne1;
- const uint idst = i1*ne0 + i0/2;
+ uint idst = i1*ne0 + i0/2;
const uint ix = rope_a_coord(i0/2, i01, i02, p);
+ // Fusion optimization: ROPE + VIEW + SET_ROWS.
+ // The rope output is viewed as a 1D tensor and offset based on a row index in rope_data_i.
+ if (p.set_rows_stride != 0) {
+ idst = i01*ne0 + i0/2;
+ idst += rope_data_i[i02].x * p.set_rows_stride;
+ }
+
if (i0 >= p.n_dims) {
rope_data_d[idst + i0/2 + 0] = ROPE_D_TYPE(rope_data_a[ix + i0/2 + 0]);
rope_data_d[idst + i0/2 + 1] = ROPE_D_TYPE(rope_data_a[ix + i0/2 + 1]);
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 {
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");
+
+ float fs = 1.4245f;
+ float ef = 0.7465f;
+ float af = 1.4245f;
+ ggml_tensor * freq = nullptr;
+
+ 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[0] * ne[1], ne[2], rope->nb[2], 0);
+ 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[0] * ne[1], ne[2] * ne[3], 1, 1);
+ 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);
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);
+ }
}
}
}
}
}
- 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));
+ }
}
}