COMPMID-2855: CLReduceMean throws error for invalid configs

Change-Id: Icc198a6db7dc79230972e12f226fa6fa1d9de6cb
Signed-off-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2452
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 36 insertions, 0 deletions

diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index 66a42d9667..a7298d6cbf 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -39,6 +39,42 @@ namespace misc
 {
 namespace shape_calculator
 {
+/** Calculate the output tensor shape for the reduce mean operation
+ *
+ * @param[in] input          Input tensor shape
+ * @param[in] reduction_axis Reduction axis
+ * @param[in] keep_dims      Flag to indicate if dimensions are kept
+ *
+ * @return the calculated shape
+ */
+inline TensorShape calculate_reduce_mean_shape(ITensor *input, const Coordinates &reduction_axis, bool keep_dims)
+{
+    const int   reduction_ops = reduction_axis.num_dimensions();
+    Coordinates axis_local    = reduction_axis;
+    const int   input_dims    = input->info()->num_dimensions();
+    convert_negative_axis(axis_local, input_dims);
+    TensorShape out_shape = input->info()->tensor_shape();
+    // Configure reshape layer if we want to drop the dimensions
+    if(!keep_dims)
+    {
+        // We have to sort the reduction axis vectors in order for remove_dimension
+        // to work properly
+        std::sort(axis_local.begin(), axis_local.begin() + reduction_ops);
+        for(int i = 0; i < reduction_ops; ++i)
+        {
+            out_shape.remove_dimension(axis_local[i] - i);
+        }
+        return out_shape;
+    }
+    else
+    {
+        for(int i = 0; i < reduction_ops; ++i)
+        {
+            out_shape.set(axis_local[i], 1);
+        }
+        return out_shape;
+    }
+}
 /** Calculate the output tensor shape of a vector input given the convolution dimensions
  *
  * @param[in] input       Input tensor shape