happyz
/
llama.cpp
mirror of https://github.com/ggerganov/llama.cpp.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Minor refactoring

This commit is contained in:
Ed Addario 2025-11-29 10:30:20 +00:00
parent 69a32b6f50
commit 5b557ca958
No known key found for this signature in database
GPG Key ID: E7875815A3230993
1 changed files with 6 additions and 6 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
src/llama-quant.cpp
View File

@ -635,7 +635,7 @@ static std::unordered_map<std::string, ggml_type> target_bpw_type(
int nthread int nthread
) { ) {
bpw_stop.store(false, std::memory_order_relaxed); bpw_stop.store(false, std::memory_order_relaxed);
// Signal handlers // SIGINT/SIGTERM signal handlers
struct signal_scope_guard { struct signal_scope_guard {
using handler_t = void (*)(int); using handler_t = void (*)(int);
handler_t prev_int = SIG_DFL; handler_t prev_int = SIG_DFL;
@ -1361,14 +1361,14 @@ static std::unordered_map<std::string, ggml_type> target_bpw_type(
for (size_t i = 0; i < compatible_candidates.size(); ++i) { for (size_t i = 0; i < compatible_candidates.size(); ++i) {
if (bpw_stop.load(std::memory_order_relaxed)) { return std::nullopt; } if (bpw_stop.load(std::memory_order_relaxed)) { return std::nullopt; }
const ggml_type tensor_types = compatible_candidates[i]; const ggml_type tensor_type = compatible_candidates[i];
const auto bpw = (float)tensor_bpw(tensor, tensor_types); const auto bpw = (float)tensor_bpw(tensor, tensor_type);
const size_t bytes = tensor_bytes(tensor, tensor_types); const size_t bytes = tensor_bytes(tensor, tensor_type);
double mse = 0.0; double mse = 0.0;
double proj = 0.0; double proj = 0.0;
const auto err = estimate_error(tensor, tensor_types, f32_sample, rows_sample, values, activations, const auto err = estimate_error(tensor, tensor_type, f32_sample, rows_sample, values, activations,
quantized_buffer, dequantized_buffer, tensor_lambda, slice_lambda, &mse, &proj); quantized_buffer, dequantized_buffer, tensor_lambda, slice_lambda, &mse, &proj);
eval_candidates[i] = candidate_types{ tensor_types, bpw, bytes, err, mse, proj }; eval_candidates[i] = candidate_types{ tensor_type, bpw, bytes, err, mse, proj };
} }
if (bpw_stop.load(std::memory_order_relaxed)) { return std::nullopt; } if (bpw_stop.load(std::memory_order_relaxed)) { return std::nullopt; }