chore: format code

src/core/backend_fit.cpp

@@ -183,7 +183,7 @@ namespace sd::backend_fit {
         vm_statistics64_data_t stats{};
         mach_msg_type_number_t count = HOST_VM_INFO64_COUNT;
         const bool ok                = host_page_size(host, &page_size) == KERN_SUCCESS &&
-                        host_statistics64(host, HOST_VM_INFO64, (host_info64_t)&stats, &count) == KERN_SUCCESS;
+                                       host_statistics64(host, HOST_VM_INFO64, (host_info64_t)&stats, &count) == KERN_SUCCESS;
         mach_port_deallocate(mach_task_self(), host);
         if (ok) {
             return ((int64_t)stats.free_count + stats.inactive_count) * page_size;
@@ -262,10 +262,10 @@ namespace sd::backend_fit {
 
             const auto& runtime_devices = plan.runtimes[ci].devices;
             const bool fits_runtime     = !runtime_devices.empty() &&
-                                      std::all_of(runtime_devices.begin(), runtime_devices.end(), [&](size_t di) {
+                                          std::all_of(runtime_devices.begin(), runtime_devices.end(), [&](size_t di) {
                                           const int64_t headroom = headroom_for(ci, di);
                                           return headroom <= remaining[di] && comp.params_bytes <= remaining[di] - headroom;
-                                      });
+                                          });
             if (fits_runtime) {
                 decision.params_location = ParamsLocation::MAIN_GPU;
                 decision.params_device   = runtime_devices.front();

src/core/ggml_runner.cpp

@@ -896,7 +896,7 @@ std::optional<Tensor<float>> GGMLRunner::execute_graph(ggml_cgraph* graph, int n
         const bool last     = index + 1 == plan.segments.size();
         auto fail_segment   = [&](const char* phase) {
             LOG_ERROR("%s segment %zu/%zu (%s) failed during %s", get_desc().c_str(),
-                        index + 1, plan.segments.size(), segment.group_name.c_str(), phase);
+                      index + 1, plan.segments.size(), segment.group_name.c_str(), phase);
             return std::nullopt;
         };
         cut_cache_.prune(segment.live_cut_names);

src/core/segment_graph_bindings.cpp

@@ -112,7 +112,7 @@ namespace sd {
                 input_tensor->data                                          = cached_tensor->data == nullptr
                                                                                   ? nullptr
                                                                                   : static_cast<void*>(static_cast<char*>(cached_tensor->data) +
-                                                              input_tensor->view_offs);
+                                                                                                       input_tensor->view_offs);
                 input_tensor->extra                                         = cached_tensor->extra;
             } else {
                 input_tensor->buffer = cached_tensor->buffer;