[Mixed Precision] Fix gradient clipping logic

update mixed precision - gradient clipping logic - when gradient clipping, gradient should unscale before calc l2norm **Self evaluation:** 1. Build test: [X]Passed [ ]Failed [ ]Skipped 2. Run test: [X]Passed [ ]Failed [ ]Skipped Signed-off-by: Donghak PARK <[email protected]>
nnstreamer · Dec 2, 2024 · 0ee82e0 · 0ee82e0
1 parent 4b6776b
commit 0ee82e0
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Showing 2 changed files with 9 additions and 4 deletions.
diff --git a/nntrainer/graph/network_graph.cpp b/nntrainer/graph/network_graph.cpp
@@ -474,11 +474,15 @@ bool NetworkGraph::backwarding(
     Tensor global_norm_t(
       TensorDim({1u, 1u, 1u, (unsigned int)lazy_weights.size()}));
     float *global_norm_data = global_norm_t.getData();
+
     for (unsigned int idx = 0; idx < lazy_weights.size(); idx++) {
       auto const &w = lazy_weights[idx];
-      if (w->getGradientRef().getDataType() != TensorDim::DataType::FP32) {
-        Tensor grad_32 = w->getGradientRef().clone(TensorDim::DataType::FP32);
-        global_norm_data[idx] = grad_32.l2norm();
+
+      if (isMixedPrecision()) {
+        Tensor scaled_grad =
+          w->getGradientRef().clone(TensorDim::DataType::FP32);
+        scaled_grad.divide_i(loss_scale);
+        global_norm_data[idx] = scaled_grad.l2norm();
       } else {
         global_norm_data[idx] = w->getGradientNorm();
       }
@@ -1567,6 +1571,7 @@ void NetworkGraph::requestOptimizerVariable(
 }
 
 void NetworkGraph::resetLossScale(float scale) {
+  loss_scale = scale;
   for (auto iter = cbegin(); iter != cend(); iter++) {
     auto &ln = *iter;
     ln->getRunContext().setLossScale(scale);

diff --git a/nntrainer/graph/network_graph.h b/nntrainer/graph/network_graph.h
@@ -508,7 +508,7 @@ class NetworkGraph {
     lazy_weights; /**< weights with delayed grad update, e.g., gradient
                      clipping, loss scaling */
   bool is_clip_grad;
-
+  float loss_scale;
   unsigned int nan_count;
 
   /**