commit ed5a492ba791d8c8b3334749d4ae946b8f11d13d
author Michele Di Giorgio <michele.digiorgio@arm.com> Thu Sep 13 16:22:01 2018 +0100
committer Anthony Barbier <anthony.barbier@arm.com> Fri Nov 02 16:55:45 2018 +0000
tree 89c8cd6f705dc88a21c61668164aad079800aff7
parent 7e9391bb14d219cda310bff355669b5964b1f576

COMPMID-1586: Add support for NHWC CLDeconvolutionLayer

COMPMID-1651: Fix QASYMM8 CLDeconvolutionLayer

This patch also extends the range of values used for testing Convolution and
Deconvolution to cover quantized [-1.0f, 1.0f].

Change-Id: I8b280669db67bb3ec25bf5d411c8f5954f5b0dab
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/149869
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Tested-by: bsgcomp <bsgcomp@arm.com>

tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h

diff --git a/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h b/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h
index 3bb935e..93e4e64 100644
--- a/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h
+++ b/tests/validation/fixtures/NormalizePlanarYUVLayerFixture.h
@@ -68,11 +68,10 @@
         }
         else if(is_data_type_quantized_asymmetric(_data_type))
         {
-            const QuantizationInfo          quant_info = src_tensor.quantization_info();
-            const int                       min_bound  = quant_info.quantize(-1.f, RoundingPolicy::TO_NEAREST_UP);
-            const int                       max_bound  = quant_info.quantize(1.f, RoundingPolicy::TO_NEAREST_UP);
-            std::uniform_int_distribution<> distribution(min_bound, max_bound);
-            std::uniform_int_distribution<> distribution_std(quant_info.quantize(0.1f, RoundingPolicy::TO_NEAREST_UP), max_bound);
+            const QuantizationInfo quant_info = src_tensor.quantization_info();
+            std::pair<int, int> bounds = get_quantized_bounds(quant_info, -1.f, 1.0f);
+            std::uniform_int_distribution<> distribution(bounds.first, bounds.second);
+            std::uniform_int_distribution<> distribution_std(quant_info.quantize(0.1f, RoundingPolicy::TO_NEAREST_UP), bounds.second);
             library->fill(src_tensor, distribution, 0);
             library->fill(mean_tensor, distribution, 1);
             library->fill(std_tensor, distribution_std, 2);