diff --git a/onert-micro/onert-micro/src/train/kernels/FullyConnected.cpp b/onert-micro/onert-micro/src/train/kernels/FullyConnected.cpp
index a8248a7fc91..e3035f223bd 100644
--- a/onert-micro/onert-micro/src/train/kernels/FullyConnected.cpp
+++ b/onert-micro/onert-micro/src/train/kernels/FullyConnected.cpp
@@ -153,7 +153,8 @@ OMStatus onert_micro::train::train_kernel_CircleFullyConnected(const OMBackpropE
 
       // 2. Calculate weight gradient
       // Init weight grads with zeros
-      for (int i = 0; i < output_shape.dims(1) * input_shape.dims(1); i += sizeof(float))
+      const auto kDlossSizeInBytes = output_shape.dims(1) * input_shape.dims(1) * sizeof(float);
+      for (int i = 0; i < kDlossSizeInBytes; i += sizeof(float))
         *static_cast<float *>(static_cast<void *>(dloss_dweight_data + i)) = 0;
 
       pal::FullyConnectedWeightGrad(
diff --git a/onert-micro/onert-micro/src/train/kernels/MaxPool2D.cpp b/onert-micro/onert-micro/src/train/kernels/MaxPool2D.cpp
index 096d2d31e8a..8da11dfa3a6 100644
--- a/onert-micro/onert-micro/src/train/kernels/MaxPool2D.cpp
+++ b/onert-micro/onert-micro/src/train/kernels/MaxPool2D.cpp
@@ -119,7 +119,7 @@ OMStatus onert_micro::train::train_kernel_CircleMaxPool2D(const OMBackpropExecut
   params.filter_w = options->filter_width();
 
   // Set input grad to zero
-  for (size_t i = 0; i < input_shape.flatSize(); i += sizeof(float))
+  for (size_t i = 0; i < input_shape.flatSize() * sizeof(float); i += sizeof(float))
     *static_cast<float *>(static_cast<void *>(dloss_dinput_data + i)) = 0;
 
   // Calculate input grad