happyz
/
llama.cpp
mirror of https://github.com/ggerganov/llama.cpp.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Add support for RMS_NORM OP

This commit is contained in:
zhanmyz 2024-12-19 15:43:39 +08:00 committed by Mustafa Cavus
parent 2353c73f53
commit 0f7d07de7d
1 changed files with 24 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

31
ggml/src/ggml-openvino.cpp
View File

@ -334,9 +334,8 @@ void ggml_backend_openvino_rms_norm_f32(ggml_tensor *dst) {
const int64_t ne0 = src0->ne[0];
const int64_t ne1 = src0->ne[1];
const int64_t ne2 = src0->ne[2];
const int64_t ne3 = src0->ne[3];
const size_t input_size = ne0 * ne1 * ne2 * ne3;
const size_t input_size = ne0 * ne1 * ne2;
const float *src_data = static_cast<const float *>(src0->data);
float *dst_data = static_cast<float *>(dst->data);
@ -344,8 +343,7 @@ void ggml_backend_openvino_rms_norm_f32(ggml_tensor *dst) {
ov::Core core;
ov::Shape input_shape = {static_cast<size_t>(ne3), static_cast<size_t>(ne2),
static_cast<size_t>(ne1), static_cast<size_t>(ne0)};
ov::Shape input_shape = {static_cast<size_t>(ne2), static_cast<size_t>(ne1), static_cast<size_t>(ne0)};
ov::Tensor input_tensor(ov::element::f32, input_shape, const_cast<float *>(src_data));
auto input_param = std::make_shared<ov::op::v0::Parameter>(
@ -357,7 +355,7 @@ void ggml_backend_openvino_rms_norm_f32(ggml_tensor *dst) {
auto square = std::make_shared<ov::op::v1::Multiply>(input_param, input_param);
auto reduce_sum = std::make_shared<ov::op::v1::ReduceSum>(
square,
ov::op::v0::Constant::create(ov::element::i64, ov::Shape{1}, {3}),
ov::op::v0::Constant::create(ov::element::i64, ov::Shape{1}, {2}),
true
);
@ -383,9 +381,16 @@ void ggml_backend_openvino_rms_norm_f32(ggml_tensor *dst) {
auto normalized_input = std::make_shared<ov::op::v1::Multiply>(input_param, scale);
ov::ParameterVector parameters = {input_param};
auto function = std::make_shared<ov::Model>(ov::NodeVector{normalized_input}, parameters);
auto model = std::make_shared<ov::Model>(ov::NodeVector{normalized_input}, parameters);
auto compiled_model = core.compile_model(function, "CPU");
// static bool model_saved = false;
// if (!model_saved) {
// std::cout << "\n rms model saved" << std::endl;
// ov::save_model(model, "/<Your-Host-Path>/rms_norm_model.xml");
// model_saved = true;
// }
auto compiled_model = core.compile_model(model, "CPU");
auto infer_request = compiled_model.create_infer_request();
@ -416,6 +421,18 @@ void ggml_backend_openvino_rms_norm(ggml_tensor * dst) {
static enum ggml_status ggml_backend_openvino_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
openvino_frontend_compute(backend, cgraph);
// for (int i = 0; i < cgraph->n_nodes; i++) {
// struct ggml_tensor * node = cgraph->nodes[i];
// switch (node->op) {
// case GGML_OP_RMS_NORM:
// ggml_backend_openvino_rms_norm(node);
// break;
// default:
// GGML_ABORT("%s: unsupported op %s\n", __func__, ggml_op_desc(node));
// }
// }
return GGML_STATUS_SUCCESS;
GGML_UNUSED(backend);