vbatts/llama.cpp
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ggml : build backends as libraries (#10256)

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* ggml : build backends as libraries

---------

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: R0CKSTAR <xiaodong.ye@mthreads.com>
This commit is contained in:
Diego Devesa 2024-11-14 18:04:35 +01:00 • committed by GitHub
parent 4a8ccb37ad
commit ae8de6d50a
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191 changed files with 17541 additions and 16879 deletions
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7
pocs/vdot/vdot.cpp
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@ -237,7 +237,6 @@ int main(int argc, char** argv) {
int n4 = useQ4_1 ? kVecSize / QK4_1 : kVecSize / QK4_0; n4 = 64*((n4 + 63)/64);
int n8 = kVecSize / QK8_0; n8 = 64*((n8 + 63)/64);
const auto * funcs = ggml_get_type_traits(useQ4_1 ? GGML_TYPE_Q4_1 : GGML_TYPE_Q4_0);
const auto * funcs_cpu = ggml_get_type_traits_cpu(useQ4_1 ? GGML_TYPE_Q4_1 : GGML_TYPE_Q4_0);
std::vector<block_q4_0> q40;
@ -263,9 +262,9 @@ int main(int argc, char** argv) {
// Note, we do not include this in the timing as in practical application
// we already have the quantized model weights.
if (useQ4_1) {
funcs->from_float(x1.data(), q41.data(), kVecSize);
funcs_cpu->from_float(x1.data(), q41.data(), kVecSize);
} else {
funcs->from_float(x1.data(), q40.data(), kVecSize);
funcs_cpu->from_float(x1.data(), q40.data(), kVecSize);
}
// Now measure time the dot product needs using the "scalar" version above
@ -284,7 +283,7 @@ int main(int argc, char** argv) {
dot_q4_q8(kVecSize, &result, q40.data(), q8.data());
}
else {
const auto * vdot = ggml_get_type_traits(funcs_cpu->vec_dot_type);
const auto * vdot = ggml_get_type_traits_cpu(funcs_cpu->vec_dot_type);
vdot->from_float(y1.data(), q8.data(), kVecSize);
if (useQ4_1) funcs_cpu->vec_dot(kVecSize, &result, 0, q41.data(), 0, q8.data(), 0, 1);
else funcs_cpu->vec_dot(kVecSize, &result, 0, q40.data(), 0, q8.data(), 0, 1);