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https://github.com/ggml-org/llama.cpp.git
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5397c36194
* Update to OV 2026.2.1, Make OV release packages self-contained * Update to OV 2026.2.1, Make OV release packages self-contained * OpenVINO Backend: Remove compute_op_type hardcoded sets (#222) * OpenVINO Backend: Remove compute_op_type hardcoded sets * revert get_op_type removal * OpenVINO backend: enable softmax with sink input * OpenVINO backend: opt mul_mat_id convert process for large size * OpenVINO backend: Modify add_id to support 2D/4D * OpenVINO Backend: Add glu_swiglu_oai * PR review: fix paths * PR review: fix path consistency --------- Co-authored-by: Mostafa <mostafas.main.email@gmail.com> Co-authored-by: Xuejun <Xuejun.Zhai@intel.com>
77 lines
2.9 KiB
C++
77 lines
2.9 KiB
C++
#include "../node_context.h"
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#include "../op_table.h"
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#include "../utils.h"
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#include <memory>
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#include <openvino/core/node.hpp>
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#include <openvino/core/node_output.hpp>
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#include <openvino/op/add.hpp>
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#include <openvino/op/constant.hpp>
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#include <openvino/op/convert.hpp>
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#include <openvino/op/gather.hpp>
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#include <openvino/op/reshape.hpp>
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#include <openvino/op/shape_of.hpp>
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namespace ov {
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namespace frontend {
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namespace ggml {
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namespace op {
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static ov::Output<ov::Node> reshape_add_id_input_to_2d(const ov::Output<ov::Node> & input,
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const ov::PartialShape & input_shape,
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const std::vector<int> & dims) {
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const auto actual_shape = input.get_partial_shape();
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if (actual_shape.rank().is_static() && actual_shape.rank().get_length() == 2) {
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return input;
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}
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if (input_shape.rank().is_static() && input_shape.rank().get_length() == 2) {
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return input;
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}
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auto shape = std::make_shared<ov::op::v3::ShapeOf>(input, ov::element::i64);
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return std::make_shared<ov::op::v1::Reshape>(input, get_dimensions(shape, dims), false);
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}
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OutputVector translate_add_id(const NodeContext & context) {
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num_inputs_check(context, 3, 3);
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auto input = process_view_input_new(context, 0);
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auto bias = process_view_input_new(context, 1);
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auto ids = process_view_input_new(context, 2);
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// OpenVINO uses reversed GGML dimensions:
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// input: [1, n_token, n_used, n_embd]
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// bias: [1, 1, n_expert, n_embd]
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// ids: [1, 1, n_token, n_used]
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// Model bias constants may already be stored as [n_expert, n_embd].
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bias = reshape_add_id_input_to_2d(bias, context.get_input_shape(1), {2, 3});
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ids = reshape_add_id_input_to_2d(ids, context.get_input_shape(2), {2, 3});
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if (ids.get_element_type() != ov::element::i32 && ids.get_element_type() != ov::element::i64) {
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ids = std::make_shared<ov::op::v0::Convert>(ids, ov::element::i32);
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}
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auto gather_axis = ov::op::v0::Constant::create(ov::element::i32, ov::Shape{}, {0});
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ov::Output<ov::Node> selected_bias = std::make_shared<ov::op::v8::Gather>(bias, ids, gather_axis);
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selected_bias = std::make_shared<ov::op::v1::Reshape>(
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selected_bias, std::make_shared<ov::op::v3::ShapeOf>(input, ov::element::i64), false);
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if (selected_bias.get_element_type() != input.get_element_type()) {
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selected_bias = std::make_shared<ov::op::v0::Convert>(selected_bias, input.get_element_type());
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}
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ov::Output<ov::Node> res = std::make_shared<ov::op::v1::Add>(input, selected_bias);
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const auto output_type = context.get_output_type();
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if (res.get_element_type() != output_type) {
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res = std::make_shared<ov::op::v0::Convert>(res, output_type);
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}
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return rename_outputs_with_suffix({res}, context.get_name());
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}
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} // namespace op
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} // namespace ggml
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} // namespace frontend
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} // namespace ov
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