arm_compute v18.11
diff --git a/tests/validation/reference/DeconvolutionLayer.cpp b/tests/validation/reference/DeconvolutionLayer.cpp
index e73023e..5ca3b44 100644
--- a/tests/validation/reference/DeconvolutionLayer.cpp
+++ b/tests/validation/reference/DeconvolutionLayer.cpp
@@ -33,19 +33,31 @@
{
namespace reference
{
-template <typename T>
-SimpleTensor<T> deconvolution_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<T> &bias, const TensorShape &output_shape,
+template <typename T, typename TB>
+SimpleTensor<T> deconvolution_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &weights, const SimpleTensor<TB> &bias, const TensorShape &output_shape,
const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> &a)
{
// Create reference
- const int stride_x = info.stride().first;
- const int stride_y = info.stride().second;
+ const int stride_x = info.stride().first;
+ const int stride_y = info.stride().second;
+ const int weights_width = weights.shape().x();
+ const int weights_height = weights.shape().y();
+ const int weights_upper_dims = weights.shape().total_size() / (weights_width * weights_height);
+
+ // Find the upsampled dimensions
+ unsigned int out_x = (src.shape().x() - 1) * stride_x + a.first + 1;
+ unsigned int out_y = (src.shape().y() - 1) * stride_y + a.second + 1;
+
+ // Find the padding needed for the convolution with stride 1 in order to match output shape
+ unsigned int padx = output_shape.x() - (out_x - weights_width + 1);
+ unsigned int pady = output_shape.y() - (out_y - weights_height + 1);
+ out_x += padx;
+ out_y += pady;
+
TensorShape scaled_shape = src.shape();
- int out_x = src.shape().x() + (src.shape().x() - 1) * (stride_x - 1) + a.first + 2 * info.pad().first;
- int out_y = src.shape().y() + (src.shape().y() - 1) * (stride_y - 1) + a.second + 2 * info.pad().second;
scaled_shape.set(0, out_x);
scaled_shape.set(1, out_y);
- SimpleTensor<T> scaled{ scaled_shape, src.data_type(), 1 };
+ SimpleTensor<T> scaled{ scaled_shape, src.data_type(), 1, src.quantization_info() };
const int width_in = src.shape().x();
const int height_in = src.shape().y();
@@ -59,19 +71,38 @@
ARM_COMPUTE_ERROR_ON_MSG(ax > stride_x - 1, "ax must be smaller than stride_x");
ARM_COMPUTE_ERROR_ON_MSG(ay > stride_y - 1, "ay must be smaller than stride_y");
- for(int j = 0; j < scaled.num_elements(); ++j)
+ if(src.data_type() == DataType::QASYMM8)
{
- scaled[j] = T(0);
+ const uint8_t quantized_zero = src.quantization_info().offset;
+ std::fill_n(scaled.data(), scaled.num_elements(), quantized_zero);
+ }
+ else
+ {
+ std::fill_n(scaled.data(), scaled.num_elements(), T(0));
+ }
+
+ // Flip weights by 180 degrees
+ SimpleTensor<T> weights_flipped{ weights.shape(), weights.data_type(), 1, weights.quantization_info() };
+ for(int ud = 0; ud < weights_upper_dims; ++ud)
+ {
+ const int offset = ud * weights_width * weights_height;
+ for(int y = 0; y < weights_height; ++y)
+ {
+ for(int x = 0; x < weights_width; ++x)
+ {
+ weights_flipped[offset + (weights_height - 1 - y) * weights_width + (weights_width - 1 - x)] = weights[offset + y * weights_width + x];
+ }
+ }
}
for(int slice = 0; slice < num_2d_slices; ++slice)
{
const int offset_slice_in = slice * width_in * height_in;
const int offset_slice_out = slice * width_scaled * height_scaled;
- const int start_x = info.pad().first;
- const int start_y = ay + info.pad().second;
- const int end_y = height_scaled - info.pad().second;
- const int end_x = width_scaled - ax - info.pad().first;
+ const int start_x = padx / 2;
+ const int start_y = ay + pady / 2;
+ const int end_y = height_scaled - pady / 2;
+ const int end_x = width_scaled - ax - padx / 2;
for(int yi = start_y, in_y = 0; yi < end_y; yi += stride_y, in_y++)
{
@@ -85,9 +116,11 @@
}
const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL);
- return convolution_layer(scaled, weights, bias, output_shape, conv_info);
+ return convolution_layer(scaled, weights_flipped, bias, output_shape, conv_info);
}
+template SimpleTensor<uint8_t> deconvolution_layer(const SimpleTensor<uint8_t> &src, const SimpleTensor<uint8_t> &weights, const SimpleTensor<int32_t> &bias, const TensorShape &output_shape,
+ const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> &a);
template SimpleTensor<float> deconvolution_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &weights, const SimpleTensor<float> &bias, const TensorShape &output_shape,
const PadStrideInfo &info, const std::pair<unsigned int, unsigned int> &a);
template SimpleTensor<half> deconvolution_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &weights, const SimpleTensor<half> &bias, const TensorShape &output_shape,