From 220df5f1fffab68e0a86f5fe9ca7c1eb272bde64 Mon Sep 17 00:00:00 2001 From: Ed Addario Date: Thu, 22 Jan 2026 23:19:26 +0000 Subject: [PATCH] Update output log --- src/llama-quant.cpp | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/src/llama-quant.cpp b/src/llama-quant.cpp index 600f2f215e..33da8cc60b 100644 --- a/src/llama-quant.cpp +++ b/src/llama-quant.cpp @@ -2140,24 +2140,26 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std:: // get more optimal quantization type based on the tensor shape, layer, etc. if (!params->pure && (ggml_is_quantized(default_type) || params->target_bpw != -1.0f || params->target_size != -1)) { + bool manual = false; + // get quantization type overrides targeting a bpw or file size budget if ((params->target_bpw != -1.0f || params->target_size != -1) && !bpw_overrides.empty()) { const auto override = bpw_overrides.find(name); if (override != bpw_overrides.end() && override->second != new_type) { - LLAMA_LOG_DEBUG("(bpw override %s) ", ggml_type_name(new_type)); + LLAMA_LOG_WARN("(target override: %s) ", ggml_type_name(new_type)); new_type = override->second; + manual = true; } } // if the user provided tensor types - use those - bool manual = false; if (params->tensor_types) { const std::vector & tensor_types = *static_cast *>(params->tensor_types); const std::string tensor_name(tensor->name); for (const auto & [tname, qtype] : tensor_types) { if (std::regex pattern(tname); std::regex_search(tensor_name, pattern)) { if (qtype != new_type) { - LLAMA_LOG_WARN("(manual override: %s -> %s) ", ggml_type_name(new_type), ggml_type_name(qtype)); + LLAMA_LOG_WARN("(manual override: %s) ", ggml_type_name(new_type)); new_type = qtype; // if two or more types are specified for the same tensor, the last match wins manual = true; break;