COMPMID-417: Fix potential memory leak in CLReduction Kernel.
Change-Id: I1c285b2fdac5ebf154731e8e34e0549a7f92525f
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/87939
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Moritz Pflanzer <moritz.pflanzer@arm.com>
diff --git a/src/runtime/CL/functions/CLReductionOperation.cpp b/src/runtime/CL/functions/CLReductionOperation.cpp
index 6643c9b..d02afb4 100644
--- a/src/runtime/CL/functions/CLReductionOperation.cpp
+++ b/src/runtime/CL/functions/CLReductionOperation.cpp
@@ -49,6 +49,9 @@
// depending on the size of the input. Last stage should have only 1 WG.
_num_of_stages = num_of_wg / 128 + 2;
+ // Create temporary tensors
+ _sums_vector = arm_compute::support::cpp14::make_unique<CLTensor[]>(_num_of_stages - 1);
+
// Configure reduction operation kernels
_reduction_kernels_vector = arm_compute::support::cpp14::make_unique<CLReductionOperationKernel[]>(_num_of_stages);
_border_handlers_vector = arm_compute::support::cpp14::make_unique<CLFillBorderKernel[]>(_num_of_stages);
@@ -57,22 +60,28 @@
for(unsigned int i = 0; i < _num_of_stages - 1; i++)
{
shape.set(0, ceil(shape.x() / 128.f));
- auto *tensor = new CLTensor;
- tensor->allocator()->init(TensorInfo(shape, input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position()));
- _memory_group.manage(tensor);
- _sums_vector.push_back(tensor);
+ _sums_vector[i].allocator()->init(TensorInfo(shape, input->info()->num_channels(), input->info()->data_type(), input->info()->fixed_point_position()));
}
// Apply ReductionOperation only on first kernel
- _reduction_kernels_vector[0].configure(input, _sums_vector.at(0), axis, op);
+ _memory_group.manage(_sums_vector.get());
+ _reduction_kernels_vector[0].configure(input, _sums_vector.get(), axis, op);
_border_handlers_vector[0].configure(input, _reduction_kernels_vector[0].border_size(), BorderMode::CONSTANT, PixelValue(0));
- for(unsigned int i = 1; i < _num_of_stages; i++)
+
+ // Apply ReductionOperation on intermediate stages
+ for(unsigned int i = 1; i < _num_of_stages - 1; ++i)
{
- // Last sum vector is the output vector
- _reduction_kernels_vector[i].configure(_sums_vector.at(i - 1), i == _num_of_stages - 1 ? output : _sums_vector.at(i), axis, ReductionOperation::SUM);
- _border_handlers_vector[i].configure(_sums_vector.at(i - 1), _reduction_kernels_vector[i].border_size(), BorderMode::CONSTANT, PixelValue(0));
- _sums_vector.at(i - 1)->allocator()->allocate();
+ _memory_group.manage(_sums_vector.get() + i);
+ _reduction_kernels_vector[i].configure(_sums_vector.get() + i - 1, _sums_vector.get() + i, axis, ReductionOperation::SUM);
+ _border_handlers_vector[i].configure(_sums_vector.get() + i - 1, _reduction_kernels_vector[i].border_size(), BorderMode::CONSTANT, PixelValue(0));
+ _sums_vector[i - 1].allocator()->allocate();
}
+
+ // Apply ReductionOperation on the last stage
+ const unsigned int last_stage = _num_of_stages - 1;
+ _reduction_kernels_vector[last_stage].configure(_sums_vector.get() + last_stage - 1, output, axis, ReductionOperation::SUM);
+ _border_handlers_vector[last_stage].configure(_sums_vector.get() + last_stage - 1, _reduction_kernels_vector[last_stage].border_size(), BorderMode::CONSTANT, PixelValue(0));
+ _sums_vector[last_stage - 1].allocator()->allocate();
}
void CLReductionOperation::run()