From e48ca32f19095ba0c47058dc7a703c1bb52977e0 Mon Sep 17 00:00:00 2001
From: Ed Addario <eaddario@hotmail.com>
Date: Sun, 5 Oct 2025 20:17:27 +0100
Subject: [PATCH] Add save_bpw_state()

---
 src/llama-quant.cpp | 50 +++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 50 insertions(+)

diff --git a/src/llama-quant.cpp b/src/llama-quant.cpp
index 50c8dbf423..3080b0ed71 100644
--- a/src/llama-quant.cpp
+++ b/src/llama-quant.cpp
@@ -734,6 +734,56 @@ static std::unordered_map<std::string, ggml_type> target_bpw_type(
         });
     };
 
+    // Saved state per tensor
+    struct saved_info {
+        std::vector<candidate_types> candidate;
+        int choice = -1;
+        float min_bpw = 0.0f;
+        float max_bpw = 0.0f;
+        size_t n_elements = 0;
+    };
+
+    auto save_bpw_state = [&](const std::vector<tensor_info> & all_vec) {
+        const std::string tmp = checkpoint_file + ".tmp";
+        std::ofstream ofs(tmp, std::ios::binary | std::ios::trunc);
+        if (!ofs) { return; } // best-effort
+        const float target_bpw = params->target_bpw;
+        const uint8_t bias_mode = params->no_bias ? 1 : 0;
+        ofs.write((const char *)&file_magic, sizeof(file_magic));
+        ofs.write((const char *)&target_bpw, sizeof(target_bpw));
+        ofs.write((const char *)&bias_mode, sizeof(bias_mode));
+        const uint64_t n = all_vec.size();
+        ofs.write((const char *)&n, sizeof(n));
+        for (const auto & ti : all_vec) {
+            const std::string name = ggml_get_name(ti.w->tensor);
+            const uint32_t len = (uint32_t)name.size();
+            ofs.write((const char *)&len, sizeof(len));
+            ofs.write(name.data(), len);
+
+            const uint64_t cn = ti.candidate.size();
+            ofs.write((const char *)&cn, sizeof(cn));
+            ofs.write((const char *)&ti.choice, sizeof(ti.choice));
+            ofs.write((const char *)&ti.min_bpw, sizeof(ti.min_bpw));
+            ofs.write((const char *)&ti.max_bpw, sizeof(ti.max_bpw));
+            const uint64_t ne = ti.n_elements;
+            ofs.write((const char *)&ne, sizeof(ne));
+
+            for (const auto & c : ti.candidate) {
+                const int32_t  t = c.type;
+                const uint64_t b = c.bytes;
+                ofs.write((const char *)&t, sizeof(t));
+                ofs.write((const char *)&c.bpw, sizeof(c.bpw));
+                ofs.write((const char *)&b, sizeof(b));
+                ofs.write((const char *)&c.error, sizeof(c.error));
+            }
+        }
+
+        ofs.close();
+        std::remove(checkpoint_file.c_str()); // TODO: handle errors
+        std::rename(tmp.c_str(), checkpoint_file.c_str());
+        LLAMA_LOG_INFO("%s: saved bpw progress for %lu tensors to %s\n", func, all_vec.size(), checkpoint_file.c_str());
+    };
+
     // Estimate error for a given type using a sampled subset of rows
     auto estimate_error = [&](const ggml_tensor * t,
         const ggml_type quant_type,