fix(rng): use fixed seed for deterministic LoRA init

Replace std::random_device with 42 + omp_get_thread_num() to ensure reproducible LoRA initialization across runs.

Author: chen2021673

infini_train/src/nn/init.cc

@@ -22,8 +22,20 @@
 
 namespace infini_train::nn::init {
 namespace {
-static std::random_device rd;
-static std::mt19937 gen(rd());
+constexpr int kRandomSeed = 42;
+
+// FIXME: RNG design is incomplete.
+//
+// Current implementation lacks:
+//   - unified Generator abstraction
+//   - global default generator and seed control
+//   - reproducible / clonable RNG state
+//
+// TODO:
+//   - introduce Generator interface and backend impl
+//   - add default generator management (per device)
+//   - refactor random ops to consume Generator
+static std::mt19937 gen(kRandomSeed);
 } // namespace
 
 std::shared_ptr<Tensor> Normal(const std::shared_ptr<Tensor> &tensor, float mean, float std,
@@ -34,7 +46,7 @@ std::shared_ptr<Tensor> Normal(const std::shared_ptr<Tensor> &tensor, float mean
 #ifdef USE_OMP
 #pragma omp parallel
     {
-        std::mt19937 local_gen(std::random_device{}() + omp_get_thread_num());
+        std::mt19937 local_gen(kRandomSeed + omp_get_thread_num());
         std::normal_distribution<float> local_dis(mean, std);
 #pragma omp for
         for (int i = 0; i < buffer.size(); ++i) {
@@ -126,7 +138,7 @@ std::shared_ptr<Tensor> Uniform(const std::shared_ptr<Tensor> &tensor, float a,
 #ifdef USE_OMP
 #pragma omp parallel
     {
-        std::mt19937 local_gen(std::random_device{}() + omp_get_thread_num());
+        std::mt19937 local_gen(kRandomSeed + omp_get_thread_num());
         std::uniform_real_distribution<float> local_dis(a, b);
 #pragma omp for
         for (int i = 0; i < buffer.size(); ++i) {