COMPMID-3316: NEDeconvolutionLayer failing for a big input

- Using NEDirectConvolution for big shapes since the memory
  required explodes for 9x9 kernel
- Adding test cases
- Fix enables only the NEON Deconvolution for NHWC

Change-Id: I8a541346428e5686818f8ecb7f69e2a9106cbceb
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3135
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>

1 files changed, 1 insertions, 1 deletions

diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index 7d2b7df43b..dfccec8b37 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -485,7 +485,7 @@ inline TensorShape compute_depthwise_convolution_shape(const ITensorInfo &input,
  * @return the calculated shape
  */
 inline TensorShape compute_deconvolution_upsampled_shape(const ITensorInfo &input, const ITensorInfo &weights, unsigned int sx, unsigned int sy,
-                                                         std::pair<unsigned int, unsigned int> &out_dims, unsigned int &padx, unsigned int &pady)
+                                                         std::pair<unsigned int, unsigned int> &out_dims, uint32_t &padx, uint32_t &pady)
 {
     const DataLayout data_layout = input.data_layout();
     const size_t     idx_w       = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);