commit afbc5ffb0b567ae93fa2765066bd136d72be88ff
author Michalis Spyrou <michalis.spyrou@arm.com> Wed Oct 03 14:18:19 2018 +0100
committer Anthony Barbier <anthony.barbier@arm.com> Fri Nov 02 16:55:45 2018 +0000
tree 328005d70d5526609a9d84173a317fd1f10b4ed2
parent 67d94d29c154a376d12e582421323c1d250da20c

COMPMID-1621 Deconvolution wrong output calculation

Change-Id: Ida71312bcf6dbd854f2ab1efc65f74910c79e152
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/151510
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>

tests/validation/CL/DeconvolutionLayer.cpp

diff --git a/tests/validation/CL/DeconvolutionLayer.cpp b/tests/validation/CL/DeconvolutionLayer.cpp
index 2aa7cfe..84a2b01 100644
--- a/tests/validation/CL/DeconvolutionLayer.cpp
+++ b/tests/validation/CL/DeconvolutionLayer.cpp
@@ -48,7 +48,7 @@
 constexpr AbsoluteTolerance<float>  tolerance_qasymm8(1.0);               /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */
 constexpr float                     tolerance_num = 0.07f;                /**< Tolerance number */
 
-const auto data4x4 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 3)
+const auto data4x4 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 5) * framework::dataset::make("StrideY", 1, 5) * framework::dataset::make("PadX", 0, 3)
                      * framework::dataset::make("PadY", 0, 3) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 });
 
 const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 2)
@@ -71,7 +71,7 @@
     const unsigned int num_kernels   = 1;
     const TensorShape  weights_shape(kernel_size_x, kernel_size_y, input_shape.z(), num_kernels);
     const TensorShape  bias_shape(num_kernels);
-    auto               out_dim      = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, 1, 1, 0, 0, 1, 1);
+    auto               out_dim      = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, 1, 1, 1, 1);
     TensorShape        output_shape = deconvolution_output_shape(out_dim, input_shape, weights_shape);
 
     // Create tensors