ggml : mul_mat_id use the same tensor for all the experts (#6387)

* ggml : update mul_mat_id to use the same tensor for all the experts

* update cuda

* minor

* update metal

* update test-backend-ops

* fix cuda

* Update ggml-metal.m

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* update convert.py

* update convert-hf-to-gguf.py

* update convert.py for mixtral hf models

* Update convert-hf-to-gguf.py

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* cuda : support non-pow-2 number of experts

* allow quantize to work for split and merged experts models in the same way

* cleanup + disable mmap automatically with split tensors models

* update imatrix

* test-backend-ops : test qwen argsort

* update grok model loading

* llama : add merged experts tensors to the grok tensor map

* minor

* gguf : bump version

* fix quantizing of merged experts

* convert-hf-to-gguf.py : update grok (untested)

* make linter happy

* cuda/argsort : use shared memory instead of pool memory

* convert : fix grok tensor names

* metal : add support for non-pow-2 argsort

* llama : more loader cleanup, better error checking

* cuda : fix warning

* llama : still use mmap for loading old models, but copy the data to a host buffer

* add review note

* llama : remove ffn tensor counting + add sanity check

ggml-ci

* convert : fix handling of n_experts == None

ggml-ci

* imatrix : fix ncall counters

* llama : produce error if imatrix size does not match

* quantize : terminate on errors + trace logs

ggml-ci

* metal : pad shared memory to 16 bytes

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

1 files changed, 10 insertions, 6 deletions

diff --git a/examples/quantize/quantize.cpp b/examples/quantize/quantize.cpp
index 80c493f1..64cb6db1 100644
--- a/examples/quantize/quantize.cpp
+++ b/examples/quantize/quantize.cpp
@@ -116,13 +116,13 @@ static void load_imatrix(const std::string & imatrix_file, std::unordered_map<st
     std::ifstream in(imatrix_file.c_str(), std::ios::binary);
     if (!in) {
         printf("%s: failed to open %s\n",__func__, imatrix_file.c_str());
-        return;
+        exit(1);
     }
     int n_entries;
     in.read((char *)&n_entries, sizeof(n_entries));
     if (in.fail() || n_entries < 1) {
         printf("%s: no data in file %s\n", __func__, imatrix_file.c_str());
-        return;
+        exit(1);
     }
     for (int i = 0; i < n_entries; ++i) {
         int len; in.read((char *)&len, sizeof(len));
@@ -130,11 +130,11 @@ static void load_imatrix(const std::string & imatrix_file, std::unordered_map<st
         in.read((char *)name_as_vec.data(), len);
         if (in.fail()) {
             printf("%s: failed reading name for entry %d from %s\n", __func__, i+1, imatrix_file.c_str());
-            return;
+            exit(1);
         }
         name_as_vec[len] = 0;
         std::string name{name_as_vec.data()};
-        auto & e = imatrix_data[std::move(name)];
+        auto & e = imatrix_data[name];
         int ncall;
         in.read((char *)&ncall, sizeof(ncall));
         int nval;
@@ -142,18 +142,22 @@ static void load_imatrix(const std::string & imatrix_file, std::unordered_map<st
         if (in.fail() || nval < 1) {
             printf("%s: failed reading number of values for entry %d\n", __func__, i);
             imatrix_data = {};
-            return;
+            exit(1);
         }
         e.resize(nval);
         in.read((char *)e.data(), nval*sizeof(float));
         if (in.fail()) {
             printf("%s: failed reading data for entry %d\n", __func__, i);
             imatrix_data = {};
-            return;
+            exit(1);
         }
         if (ncall > 0) {
             for (auto& v : e) v /= ncall;
         }
+
+        if (getenv("LLAMA_TRACE")) {
+            printf("%s: loaded data (size = %6d, ncall = %6d) for '%s'\n", __func__, int(e.size()), ncall, name.c_str());
+        }
     }
     printf("%s: loaded %d importance matrix entries from %s\n", __func__, int(imatrix_data.size()), imatrix_file.c_str());
 }