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authorJohn <78893154+cmp-nct@users.noreply.github.com>2024-01-10 14:37:09 +0100
committerGitHub <noreply@github.com>2024-01-10 15:37:09 +0200
commitd34633d8db6c2e400355de4862cd699154ecc73f (patch)
tree9047425d7bb97e369437a2bd28fa0405e27a5533
parent4f56458d34cb13dcbf69aca650e9bf77d5497e6f (diff)
clip : support more quantization types (#4846)
Uses ggml functions instead of hardcoded names and adds support to quantize into the modern Q-K variants. This is just the bare minimum to get k-types working - a more refined choice of types would be needed to get best quality on low quantizations. I ran a few tests, it doesn't break anything I could notice and a Q6_K ViT works almost as well as Q8_0 but 3 times the inference speed.
-rw-r--r--examples/llava/clip.cpp62
1 files changed, 24 insertions, 38 deletions
diff --git a/examples/llava/clip.cpp b/examples/llava/clip.cpp
index cfb79e78..2ae8853d 100644
--- a/examples/llava/clip.cpp
+++ b/examples/llava/clip.cpp
@@ -126,24 +126,7 @@ static struct ggml_tensor * get_tensor(struct ggml_context * ctx, const std::str
}
static std::string get_ftype(int ftype) {
- switch (ftype) {
- case 0:
- return "f32";
- case 1:
- return "f16";
- case 2:
- return "q4_0";
- case 3:
- return "q4_1";
- case 6:
- return "q5_0";
- case 7:
- return "q5_1";
- case 8:
- return "q8_0";
- default:
- throw std::runtime_error(format("%s: Unrecognized file type: %d\n", __func__, ftype));
- }
+ return ggml_type_name(static_cast<ggml_type>(ftype));
}
//
@@ -533,6 +516,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
buffer_size += n_tensors * 128 /* CLIP PADDING */;
clip_ctx * new_clip = new clip_ctx;
+
#ifdef GGML_USE_CUBLAS
new_clip->backend = ggml_backend_cuda_init(0);
printf("%s: CLIP using CUDA backend\n", __func__);
@@ -543,6 +527,7 @@ struct clip_ctx * clip_model_load(const char * fname, const int verbosity = 1) {
printf("%s: CLIP using Metal backend\n", __func__);
#endif
+
if (!new_clip->backend) {
new_clip->backend = ggml_backend_cpu_init();
printf("%s: CLIP using CPU backend\n", __func__);
@@ -931,26 +916,8 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
ggml_type type = GGML_TYPE_Q4_1;
- switch (itype) {
- case 2:
- type = GGML_TYPE_Q4_0;
- break;
- case 3:
- type = GGML_TYPE_Q4_1;
- break;
- case 6:
- type = GGML_TYPE_Q5_0;
- break;
- case 7:
- type = GGML_TYPE_Q5_1;
- break;
- case 8:
- type = GGML_TYPE_Q8_0;
- break;
- default:
- fprintf(stderr, "%s: invalid quantization type %d\n", __func__, itype);
- return false;
- };
+ assert(itype < GGML_TYPE_COUNT);
+ type = static_cast<ggml_type>(itype);
auto * ctx_clip = clip_model_load(fname_inp, 2);
@@ -1010,6 +977,10 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
if (quantize) {
new_type = type;
+ if (new_type >= GGML_TYPE_Q2_K && name.find("embd") != std::string::npos) {
+ new_type = GGML_TYPE_Q8_0; // ggml_get_rows needs non K type
+ // fprintf(stderr, "%s: quantizing %s to %s\n", __func__, name.c_str(), ggml_type_name(new_type));
+ }
const size_t n_elms = ggml_nelements(cur);
float * f32_data;
@@ -1054,6 +1025,21 @@ bool clip_model_quantize(const char * fname_inp, const char * fname_out, const i
case GGML_TYPE_Q8_0: {
new_size = ggml_quantize_q8_0(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
} break;
+ case GGML_TYPE_Q2_K: {
+ new_size = ggml_quantize_q2_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
+ } break;
+ case GGML_TYPE_Q3_K: {
+ new_size = ggml_quantize_q3_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
+ } break;
+ case GGML_TYPE_Q4_K: {
+ new_size = ggml_quantize_q4_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
+ } break;
+ case GGML_TYPE_Q5_K: {
+ new_size = ggml_quantize_q5_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
+ } break;
+ case GGML_TYPE_Q6_K: {
+ new_size = ggml_quantize_q6_K(f32_data, new_data, n_elms, cur->ne[0], hist_cur.data());
+ } break;
default: {
fprintf(stderr, "%s: unsupported quantization type %d\n", __func__, new_type);
return false;