arm_compute v19.05
diff --git a/src/runtime/CL/functions/CLReductionOperation.cpp b/src/runtime/CL/functions/CLReductionOperation.cpp
index 3d82e3f..9f99d2d 100644
--- a/src/runtime/CL/functions/CLReductionOperation.cpp
+++ b/src/runtime/CL/functions/CLReductionOperation.cpp
@@ -71,7 +71,7 @@
else
{
// Create temporary tensor infos
- auto sums_vector = arm_compute::support::cpp14::make_unique<TensorInfo[]>(num_of_stages - 1);
+ std::vector<TensorInfo> sums_vector(num_of_stages - 1);
// Create intermediate tensor info
TensorShape shape{ input->tensor_shape() };
@@ -110,17 +110,17 @@
}
// Validate ReductionOperation only on first kernel
- ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(input, sums_vector.get(), axis, first_kernel_op));
+ ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(input, &sums_vector[0], axis, first_kernel_op));
// Validate ReductionOperation on intermediate stages
for(unsigned int i = 1; i < num_of_stages - 1; ++i)
{
- ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(sums_vector.get() + i - 1, sums_vector.get() + i, axis, intermediate_kernel_op));
+ ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(&sums_vector[i - 1], &sums_vector[i], axis, intermediate_kernel_op));
}
// Validate ReductionOperation on the last stage
const unsigned int last_stage = num_of_stages - 1;
- ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(sums_vector.get() + last_stage - 1, output, axis, last_kernel_op, input->dimension(0)));
+ ARM_COMPUTE_RETURN_ON_ERROR(CLReductionOperationKernel::validate(&sums_vector[last_stage - 1], output, axis, last_kernel_op, input->dimension(0)));
}
return Status{};
@@ -133,7 +133,7 @@
_is_serial = is_data_type_quantized(input->info()->data_type()) || axis != 0;
// Configure reduction operation kernels
- _reduction_kernels_vector = arm_compute::support::cpp14::make_unique<CLReductionOperationKernel[]>(_num_of_stages);
+ _reduction_kernels_vector.resize(_num_of_stages);
// Create temporary tensors
if(_is_serial)
@@ -142,8 +142,8 @@
}
else
{
- _border_handlers_vector = arm_compute::support::cpp14::make_unique<CLFillBorderKernel[]>(_num_of_stages);
- _results_vector = arm_compute::support::cpp14::make_unique<CLTensor[]>(_num_of_stages - 1);
+ _border_handlers_vector.resize(_num_of_stages);
+ _results_vector.resize(_num_of_stages - 1);
TensorShape shape{ input->info()->tensor_shape() };
for(unsigned int i = 0; i < _num_of_stages - 1; i++)
{
@@ -152,7 +152,7 @@
}
// Apply ReductionOperation only on first kernel
- _memory_group.manage(_results_vector.get());
+ _memory_group.manage(&_results_vector[0]);
ReductionOperation first_kernel_op;
ReductionOperation intermediate_kernel_op;
@@ -183,30 +183,30 @@
ARM_COMPUTE_ERROR("Not supported");
}
- _reduction_kernels_vector[0].configure(input, _results_vector.get(), axis, first_kernel_op);
+ _reduction_kernels_vector[0].configure(input, &_results_vector[0], axis, first_kernel_op);
_border_handlers_vector[0].configure(input, _reduction_kernels_vector[0].border_size(), BorderMode::CONSTANT, pixelValue);
// Apply ReductionOperation on intermediate stages
for(unsigned int i = 1; i < _num_of_stages - 1; ++i)
{
- _memory_group.manage(_results_vector.get() + i);
- _reduction_kernels_vector[i].configure(_results_vector.get() + i - 1, _results_vector.get() + i, axis, intermediate_kernel_op);
- _border_handlers_vector[i].configure(_results_vector.get() + i - 1, _reduction_kernels_vector[i].border_size(), BorderMode::CONSTANT, pixelValue);
+ _memory_group.manage(&_results_vector[i]);
+ _reduction_kernels_vector[i].configure(&_results_vector[i - 1], &_results_vector[i], axis, intermediate_kernel_op);
+ _border_handlers_vector[i].configure(&_results_vector[i - 1], _reduction_kernels_vector[i].border_size(), BorderMode::CONSTANT, pixelValue);
_results_vector[i - 1].allocator()->allocate();
}
// Apply ReductionOperation on the last stage
const unsigned int last_stage = _num_of_stages - 1;
const unsigned int input_width = input->info()->dimension(0);
- _reduction_kernels_vector[last_stage].configure(_results_vector.get() + last_stage - 1, output, axis, last_kernel_op, input_width);
- _border_handlers_vector[last_stage].configure(_results_vector.get() + last_stage - 1, _reduction_kernels_vector[last_stage].border_size(), BorderMode::CONSTANT, pixelValue);
+ _reduction_kernels_vector[last_stage].configure(&_results_vector[last_stage - 1], output, axis, last_kernel_op, input_width);
+ _border_handlers_vector[last_stage].configure(&_results_vector[last_stage - 1], _reduction_kernels_vector[last_stage].border_size(), BorderMode::CONSTANT, pixelValue);
_results_vector[last_stage - 1].allocator()->allocate();
}
}
void CLReductionOperation::run()
{
- _memory_group.acquire();
+ MemoryGroupResourceScope scope_mg(_memory_group);
if(_is_serial)
{
@@ -220,6 +220,4 @@
CLScheduler::get().enqueue(_reduction_kernels_vector[i], false);
}
}
-
- _memory_group.release();
}