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path: root/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp
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Diffstat (limited to 'src/runtime/NEON/functions/NEL2NormalizeLayer.cpp')
-rw-r--r--src/runtime/NEON/functions/NEL2NormalizeLayer.cpp17
1 files changed, 12 insertions, 5 deletions
diff --git a/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp b/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp
index c9ab5c98e2..88ffdbfd08 100644
--- a/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp
+++ b/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp
@@ -28,25 +28,31 @@
namespace arm_compute
{
+namespace
+{
+constexpr int max_input_tensor_dim = 3;
+} // namespace
+
NEL2NormalizeLayer::NEL2NormalizeLayer(std::shared_ptr<IMemoryManager> memory_manager)
: _memory_group(std::move(memory_manager)), _reduce_func(), _normalize_kernel(), _sumsq()
{
}
-void NEL2NormalizeLayer::configure(ITensor *input, ITensor *output, unsigned int axis, float epsilon)
+void NEL2NormalizeLayer::configure(ITensor *input, ITensor *output, int axis, float epsilon)
{
// Manage intermediate buffers
_memory_group.manage(&_sumsq);
// Configure Kernels
- _reduce_func.configure(input, &_sumsq, axis, ReductionOperation::SUM_SQUARE);
+ const uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim);
+ _reduce_func.configure(input, &_sumsq, actual_axis, ReductionOperation::SUM_SQUARE);
_normalize_kernel.configure(input, &_sumsq, output, axis, epsilon);
// Allocate intermediate tensors
_sumsq.allocator()->allocate();
}
-Status NEL2NormalizeLayer::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, float epsilon)
+Status NEL2NormalizeLayer::validate(const ITensorInfo *input, const ITensorInfo *output, int axis, float epsilon)
{
TensorShape shape(input->tensor_shape());
@@ -55,10 +61,11 @@ Status NEL2NormalizeLayer::validate(const ITensorInfo *input, const ITensorInfo
sum_sq.set_data_type(input->data_type());
sum_sq.set_tensor_shape(shape);
- ARM_COMPUTE_RETURN_ON_ERROR(NEReductionOperation::validate(input, &sum_sq, axis, ReductionOperation::SUM_SQUARE));
+ const uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim);
+ ARM_COMPUTE_RETURN_ON_ERROR(NEReductionOperation::validate(input, &sum_sq, actual_axis, ReductionOperation::SUM_SQUARE));
// Reduce shape on axis
- shape.set(axis, 1);
+ shape.set(actual_axis, 1);
sum_sq.set_tensor_shape(shape);
ARM_COMPUTE_RETURN_ON_ERROR(NEL2NormalizeLayerKernel::validate(input, &sum_sq, output, axis, epsilon));