COMPMID-2707: add keep_dims parameter to Reduction Operation
The added parameter is used to decide whether or not to keep
the target dimension of reduction operation. ArgMinMax operations
will always remove the reduced dimension. Following things
are updated to support the parameter.
- [CL/NEON] functions and reference kernel
- [CL/NEON] ArgMinMax function to use ReductionOperation function
- [CL/NEON] validation test suite for Reduction and ArgMinMax operations
to validate the added parameter
- ReductionOperationFixture is modified NOT to pre-populate output
tensor and now relies on underlying kernel/function.
- Adjust CL validation test suite for Reduction operation to remove
excessive test cases with axis values beyond input tensor's
dimension.
Change-Id: I3e24d276ed469a4201f323001708f0c525f11c4f
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2167
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/src/runtime/NEON/functions/NEReductionOperation.cpp b/src/runtime/NEON/functions/NEReductionOperation.cpp
index dc6cf59..09cd765 100644
--- a/src/runtime/NEON/functions/NEReductionOperation.cpp
+++ b/src/runtime/NEON/functions/NEReductionOperation.cpp
@@ -24,6 +24,7 @@
#include "arm_compute/runtime/NEON/functions/NEReductionOperation.h"
#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/NEON/NEScheduler.h"
namespace arm_compute
@@ -52,25 +53,78 @@
}
} // namespace
-NEReductionOperation::NEReductionOperation()
- : _reduction_kernel(), _fill_border_kernel(), _window_split(0), _reduction_axis()
+NEReductionOperation::NEReductionOperation(std::shared_ptr<IMemoryManager> memory_manager)
+ : _memory_group(memory_manager), _reduction_kernel(), _fill_border_kernel(), _reshape_kernel(), _output_internal(), _window_split(0), _reduction_axis(), _is_reshape_required(false)
{
}
-Status NEReductionOperation::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op)
+Status NEReductionOperation::validate(const ITensorInfo *input, const ITensorInfo *output, unsigned int axis, ReductionOperation op, bool keep_dims)
{
- ARM_COMPUTE_RETURN_ON_ERROR(NEReductionOperationKernel::validate(input, output, axis, op));
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Reduction axis greater than max number of dimensions");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis > 3, "Unsupported reduction axis");
+
+ const auto is_reshape_required = !keep_dims;
+
+ auto *output_internal = output;
+
+ TensorInfo info_before_reshape;
+
+ if(is_reshape_required)
+ {
+ const TensorInfo expected_output_shape = output->clone()->set_tensor_shape(arm_compute::misc::shape_calculator::compute_reduced_shape(input->tensor_shape(), axis, keep_dims));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(&expected_output_shape, output);
+
+ auto shape_before_reshape = input->tensor_shape();
+ shape_before_reshape.set(axis, 1);
+
+ const auto input_num_channles = input->num_channels();
+ const auto input_qinfo = input->quantization_info();
+ const auto is_arg_min_max = (op == ReductionOperation::ARG_IDX_MAX) || (op == ReductionOperation::ARG_IDX_MIN);
+ const auto output_data_type = is_arg_min_max ? DataType::U32 : output->data_type();
+
+ info_before_reshape.set_data_type(output_data_type).set_tensor_shape(shape_before_reshape).set_num_channels(input_num_channles).set_quantization_info(input_qinfo);
+
+ output_internal = &info_before_reshape;
+ }
+
+ ARM_COMPUTE_RETURN_ON_ERROR(NEReductionOperationKernel::validate(input, output_internal, axis, op));
+
+ if(is_reshape_required)
+ {
+ ARM_COMPUTE_RETURN_ON_ERROR(NEReshapeLayerKernel::validate(output_internal, output));
+ }
return Status{};
}
-void NEReductionOperation::configure(ITensor *input, ITensor *output, unsigned int axis, ReductionOperation op)
+void NEReductionOperation::configure(ITensor *input, ITensor *output, unsigned int axis, ReductionOperation op, bool keep_dims)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
- ARM_COMPUTE_ERROR_THROW_ON(NEReductionOperation::validate(input->info(), output->info(), axis, op));
+
+ _is_reshape_required = !keep_dims;
+
+ auto *output_internal = output;
+ const auto is_arg_min_max = (op == ReductionOperation::ARG_IDX_MAX) || (op == ReductionOperation::ARG_IDX_MIN);
+
+ if(_is_reshape_required)
+ {
+ const auto output_internal_shape = arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis);
+ const auto output_external_shape = arm_compute::misc::shape_calculator::compute_reduced_shape(input->info()->tensor_shape(), axis, false);
+ const auto output_data_type = is_arg_min_max ? DataType::U32 : input->info()->data_type();
+ const auto num_channels = input->info()->num_channels();
+ const auto qinfo = input->info()->quantization_info();
+
+ _output_internal.allocator()->init(input->info()->clone()->set_data_type(output_data_type).set_tensor_shape(output_internal_shape).reset_padding().set_is_resizable(true).set_num_channels(
+ num_channels).set_quantization_info(qinfo));
+ _memory_group.manage(&_output_internal);
+ output_internal = &_output_internal;
+ auto_init_if_empty(*output->info(), input->info()->clone()->set_data_type(output_data_type).set_tensor_shape(output_external_shape).reset_padding().set_is_resizable(true));
+ }
+
+ ARM_COMPUTE_ERROR_THROW_ON(NEReductionOperation::validate(input->info(), output->info(), axis, op, keep_dims));
// Configure reduction kernel
- _reduction_kernel.configure(input, output, axis, op);
+ _reduction_kernel.configure(input, output_internal, axis, op);
_window_split = reduction_window_split_dimension(axis);
_reduction_axis = axis;
@@ -150,7 +204,13 @@
default:
ARM_COMPUTE_ERROR("Reduction Operation unsupported");
}
- _fill_border_kernel.configure(input, fill_border_size, BorderMode::CONSTANT, pixelValue);
+ _fill_border_kernel.configure(input, fill_border_size, (is_arg_min_max ? BorderMode::REPLICATE : BorderMode::CONSTANT), pixelValue);
+ }
+
+ if(_is_reshape_required)
+ {
+ _reshape_kernel.configure(output_internal, output);
+ _output_internal.allocator()->allocate();
}
}
@@ -161,5 +221,9 @@
NEScheduler::get().schedule(&_fill_border_kernel, Window::DimY);
}
NEScheduler::get().schedule(&_reduction_kernel, _window_split);
+ if(_is_reshape_required)
+ {
+ NEScheduler::get().schedule(&_reshape_kernel, Window::DimY);
+ }
}
} // namespace arm_compute