Add OpenVINO MUL operator to GGML of Llama.cpp.

This commit is contained in:
zhanmyz 2024-12-02 10:18:54 +08:00 committed by Mustafa Cavus
parent faa4a7de76
commit adc2c70f44
1 changed files with 81 additions and 13 deletions

View File

@ -9,6 +9,7 @@
#include <openvino/op/op.hpp>
#include <openvino/op/add.hpp>
#include <openvino/op/subtract.hpp>
#include <openvino/opsets/opset1.hpp>
#define GGML_OPENVINO_MAX_STREAMS 8
@ -133,6 +134,42 @@ static void ggml_backend_openvino_add_forward(ggml_tensor * dst) {
// fflush(stdout);
}
static void ggml_backend_openvino_mul_forward(ggml_tensor * dst) {
struct ggml_tensor *src0 = dst->src[0];
struct ggml_tensor *src1 = dst->src[1];
ov::Core core;
// define shape
ov::Shape shape0 = {static_cast<size_t>(src0->ne[1]), static_cast<size_t>(src0->ne[0])}; // For Example: [7, 3072]
ov::Shape shape1 = {static_cast<size_t>(src1->ne[1]), static_cast<size_t>(src1->ne[0])}; // For Example: [1, 3072] -> broadcast to [7, 3072]
// create OpenVINO tensor (src0 and src1)
ov::Tensor tensor0(ov::element::f32, shape0, src0->data);
ov::Tensor tensor1(ov::element::f32, shape1, src1->data);
// define input parameters
auto input0 = std::make_shared<ov::op::v0::Parameter>(ov::element::f32, shape0);
auto input1 = std::make_shared<ov::op::v0::Parameter>(ov::element::f32, shape1);
// create a multiply operation using broadcasting
auto multiply = std::make_shared<ov::op::v1::Multiply>(input0, input1);
// create model
auto model = std::make_shared<ov::Model>(multiply, ov::ParameterVector{input0, input1});
ov::CompiledModel compiled_model = core.compile_model(model, "CPU");
ov::InferRequest infer_request = compiled_model.create_infer_request();
infer_request.set_tensor(input0, tensor0);
infer_request.set_tensor(input1, tensor1);
infer_request.infer();
// get output tensor and copy it back to dst->data
ov::Tensor output_tensor = infer_request.get_output_tensor();
std::memcpy(dst->data, output_tensor.data<float>(), src0->ne[0] * src0->ne[1] * sizeof(float));
}
static void ggml_backend_openvino_add(ggml_tensor * dst) {
// Placeholder for OpenVINO add operation
// GGML_ASSERT(ctx.device != 0);
@ -169,28 +206,49 @@ static void ggml_backend_openvino_add(ggml_tensor * dst) {
}
static void test_op_for_NONE() {
GGML_LOG_DEBUG("...test_op_for_NONE... \n");
static void ggml_backend_openvino_mul(ggml_tensor * dst) {
GGML_ASSERT(dst->data != nullptr);
const struct ggml_tensor * src0 = dst->src[0];
const struct ggml_tensor * src1 = dst->src[1];
GGML_ASSERT(src1->type == GGML_TYPE_F32 && "only f32 src1 supported for now");
switch (src0->type) {
case GGML_TYPE_F32:
{
ggml_backend_openvino_mul_forward(dst);
} break;
default:
{
GGML_ABORT("fatal error");
}
}
}
static enum ggml_status ggml_backend_openvino_graph_compute(ggml_backend_t backend, struct ggml_cgraph * cgraph) {
for (int i = 0; i < cgraph->n_nodes; i++) {
struct ggml_tensor * node = cgraph->nodes[i];
if (node->op == GGML_OP_NONE || ggml_is_empty(node)) {
return GGML_STATUS_SUCCESS;
}
switch (node->op) {
case GGML_OP_ADD:
// TODO
ggml_backend_openvino_add(node);
break;
case GGML_OP_MUL_MAT:
case GGML_OP_OUT_PROD:
break;
case GGML_OP_NONE:
test_op_for_NONE();
case GGML_OP_RESHAPE:
case GGML_OP_VIEW:
case GGML_OP_PERMUTE:
case GGML_OP_RESHAPE:
case GGML_OP_TRANSPOSE:
case GGML_OP_VIEW:
break;
case GGML_OP_ADD:
{
ggml_backend_openvino_add(node);
} break;
case GGML_OP_MUL:
{
ggml_backend_openvino_mul(node);
} break;
case GGML_OP_MUL_MAT:
break;
default:
GGML_ABORT("%s: unsupported op %s\n", __func__, ggml_op_desc(node));
@ -395,8 +453,18 @@ static bool ggml_backend_openvino_device_supports_op(ggml_backend_dev_t dev, con
// ggml_backend_openvino_device_context * dev_ctx = (ggml_backend_openvino_device_context *) dev->context;
switch (op->op) {
case GGML_OP_NONE:
case GGML_OP_PERMUTE:
case GGML_OP_RESHAPE:
case GGML_OP_TRANSPOSE:
case GGML_OP_VIEW:
return true;
case GGML_OP_ADD:
return true;
case GGML_OP_MUL:
return true;
case GGML_OP_MUL_MAT:
return false;
default:
return false;
}