COMPMID-2671 use Signed32 for default output data type of ArgMinMax

Signed32 is used as data types before and after reshaping of ArgMinMax.

Change-Id: I230af43a931d4e106de6c72f716ced1dab511084
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2262
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>

4 files changed, 7 insertions, 7 deletions

diff --git a/src/core/CL/kernels/CLReductionOperationKernel.cpp b/src/core/CL/kernels/CLReductionOperationKernel.cpp
index a085ab1683..cbf3923243 100644
--- a/src/core/CL/kernels/CLReductionOperationKernel.cpp
+++ b/src/core/CL/kernels/CLReductionOperationKernel.cpp
@@ -83,7 +83,7 @@ std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITe
     // Output tensor auto initialization if not yet initialized
     const bool        is_arg_min_max   = (op == ReductionOperation::ARG_IDX_MIN || op == ReductionOperation::ARG_IDX_MAX);
     const TensorShape output_shape     = arm_compute::misc::shape_calculator::compute_reduced_shape(input->tensor_shape(), axis, !is_arg_min_max);
-    const DataType    output_data_type = is_arg_min_max ? DataType::U32 : input->data_type();
+    const DataType    output_data_type = is_arg_min_max ? DataType::S32 : input->data_type();
     auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape).set_data_type(output_data_type).reset_padding().set_is_resizable(true));
 
     const unsigned int num_elems_processed_per_iteration = (is_data_type_quantized(input->data_type()) && (axis == 0)) ? 1 : 16;
diff --git a/src/core/NEON/kernels/NEReductionOperationKernel.cpp b/src/core/NEON/kernels/NEReductionOperationKernel.cpp
index 85abda598d..a2ce0de38b 100644
--- a/src/core/NEON/kernels/NEReductionOperationKernel.cpp
+++ b/src/core/NEON/kernels/NEReductionOperationKernel.cpp
@@ -1204,7 +1204,7 @@ std::tuple<Status, Window> validate_and_configure_window(ITensorInfo *input, ITe
 
     // Output auto initialization if not yet initialized
     const bool is_arg_min_max   = (op == ReductionOperation::ARG_IDX_MIN || op == ReductionOperation::ARG_IDX_MAX);
-    DataType   output_data_type = is_arg_min_max ? DataType::U32 : input->data_type();
+    DataType   output_data_type = is_arg_min_max ? DataType::S32 : input->data_type();
     auto_init_if_empty(*output, input->clone()->set_tensor_shape(output_shape).set_data_type(output_data_type).reset_padding().set_is_resizable(true));
 
     unsigned int num_elems_processed_per_iteration = 16 / data_size_from_type(input->data_type());
diff --git a/src/runtime/CL/functions/CLReductionOperation.cpp b/src/runtime/CL/functions/CLReductionOperation.cpp
index 447c15b1e8..3aa5a813b6 100644
--- a/src/runtime/CL/functions/CLReductionOperation.cpp
+++ b/src/runtime/CL/functions/CLReductionOperation.cpp
@@ -86,7 +86,7 @@ Status CLReductionOperation::validate(const ITensorInfo *input, const ITensorInf
     const auto input_data_type    = input->data_type();
     const auto input_num_channles = input->num_channels();
     const auto input_qinfo        = input->quantization_info();
-    const auto output_data_type   = is_arg_min_max ? DataType::U32 : output->data_type();
+    const auto output_data_type   = is_arg_min_max ? DataType::S32 : output->data_type();
 
     auto initialize_tensorinfo = [](TensorInfo & ti, TensorShape shape, DataType data_type, int num_channels, QuantizationInfo qinfo)
     {
@@ -208,7 +208,7 @@ ICLTensor *CLReductionOperation::configure_intermediate_result_vector(ICLTensor
 
     if(is_arg_min_max)
     {
-        _results_vector.back().info()->set_data_type(DataType::U32).set_is_resizable(true).reset_padding();
+        _results_vector.back().info()->set_data_type(DataType::S32).set_is_resizable(true).reset_padding();
     }
 
     return _is_reshape_required ? &_results_vector.back() : output;
@@ -229,7 +229,7 @@ void CLReductionOperation::configure(ICLTensor *input, ICLTensor *output, unsign
     if(_is_reshape_required)
     {
         const TensorShape output_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        output_data_type = is_arg_min_max ? DataType::S32 : input->info()->data_type();
         auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape).set_data_type(output_data_type).reset_padding().set_is_resizable(true));
     }
 
diff --git a/src/runtime/NEON/functions/NEReductionOperation.cpp b/src/runtime/NEON/functions/NEReductionOperation.cpp
index 09cd765d4b..397fe21cb9 100644
--- a/src/runtime/NEON/functions/NEReductionOperation.cpp
+++ b/src/runtime/NEON/functions/NEReductionOperation.cpp
@@ -80,7 +80,7 @@ Status NEReductionOperation::validate(const ITensorInfo *input, const ITensorInf
         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();
+        const auto output_data_type   = is_arg_min_max ? DataType::S32 : 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);
 
@@ -110,7 +110,7 @@ void NEReductionOperation::configure(ITensor *input, ITensor *output, unsigned i
     {
         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 output_data_type      = is_arg_min_max ? DataType::S32 : input->info()->data_type();
         const auto num_channels          = input->info()->num_channels();
         const auto qinfo                 = input->info()->quantization_info();