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authorGeorgios Pinitas <georgios.pinitas@arm.com>2019-05-16 14:23:00 +0100
committerMichalis Spyrou <michalis.spyrou@arm.com>2019-05-17 17:54:57 +0100
commitbd17a169153ee181100f3b31984968b66618ef3c (patch)
treeb288e1747d9194391f1c0c528bbebc8506cca7e4 /src/runtime/CL/functions/CLReduceMean.cpp
parent032cce9bd3d691c3f7e481f1c0015a5f2aa4b4f6 (diff)
downloadComputeLibrary-bd17a169153ee181100f3b31984968b66618ef3c.tar.gz
IVGCVSW-2794: Return correct status for ReduceMean operations.branches/arm_compute_19_05
Returns data type support status. Change-Id: If6f95896eec9a31ede9dc5801a0c949376991a91 Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com> Reviewed-on: https://review.mlplatform.org/c/1155 Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com> Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/runtime/CL/functions/CLReduceMean.cpp')
-rw-r--r--src/runtime/CL/functions/CLReduceMean.cpp3
1 files changed, 3 insertions, 0 deletions
diff --git a/src/runtime/CL/functions/CLReduceMean.cpp b/src/runtime/CL/functions/CLReduceMean.cpp
index 15091f9066..a3634cd46e 100644
--- a/src/runtime/CL/functions/CLReduceMean.cpp
+++ b/src/runtime/CL/functions/CLReduceMean.cpp
@@ -23,6 +23,7 @@
*/
#include "arm_compute/runtime/CL/functions/CLReduceMean.h"
+#include "arm_compute/core/CL/CLValidate.h"
#include "arm_compute/core/CL/ICLTensor.h"
#include "arm_compute/core/CL/kernels/CLReductionOperationKernel.h"
#include "arm_compute/core/Types.h"
@@ -99,6 +100,8 @@ void CLReduceMean::configure(ICLTensor *input, const Coordinates &reduction_axis
Status CLReduceMean::validate(const ITensorInfo *input, const Coordinates &reduction_axis, bool keep_dims, const ITensorInfo *output)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
+ ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
ARM_COMPUTE_RETURN_ERROR_ON(reduction_axis.num_dimensions() > input->num_dimensions());
TensorShape out_shape = input->tensor_shape();