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author | Pablo Tello <pablo.tello@arm.com> | 2019-02-05 16:16:19 +0000 |
---|---|---|
committer | Pablo Marquez <pablo.tello@arm.com> | 2019-02-08 11:15:30 +0000 |
commit | 54e98d98fbe082b265b2c4a384eabe0144866bcc (patch) | |
tree | f0367171d8dfcad282523efceb709ec523ef9edd /tests/validation/reference/WidthConcatenateLayer.cpp | |
parent | 03bb550b72ebd107a6cbd994008cdcc00597d822 (diff) | |
download | ComputeLibrary-54e98d98fbe082b265b2c4a384eabe0144866bcc.tar.gz |
COMPMID-1918: Different qinfos support in NEConcatLayer.
Added support in NEDepthConcatenateLayerKernel and NEWidthConcatenateLayer for
different quantization arguments both for the input and output.
If input's quantization infos are not homogeneous the input values are requantized using
the output's quantization info.
Change-Id: I2daa638361947eb3ec848d5425d0a5bbfea1936d
Reviewed-on: https://review.mlplatform.org/627
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Isabella Gottardi <isabella.gottardi@arm.com>
Diffstat (limited to 'tests/validation/reference/WidthConcatenateLayer.cpp')
-rw-r--r-- | tests/validation/reference/WidthConcatenateLayer.cpp | 31 |
1 files changed, 19 insertions, 12 deletions
diff --git a/tests/validation/reference/WidthConcatenateLayer.cpp b/tests/validation/reference/WidthConcatenateLayer.cpp index 6be171b64d..38543393ce 100644 --- a/tests/validation/reference/WidthConcatenateLayer.cpp +++ b/tests/validation/reference/WidthConcatenateLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 ARM Limited. + * Copyright (c) 2018-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -34,7 +34,7 @@ namespace validation namespace reference { template <typename T> -SimpleTensor<T> widthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs) +SimpleTensor<T> widthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst) { // Create reference std::vector<TensorShape> shapes; @@ -44,10 +44,6 @@ SimpleTensor<T> widthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs) shapes.emplace_back(src.shape()); } - DataType dst_type = srcs.empty() ? DataType::UNKNOWN : srcs[0].data_type(); - TensorShape dst_shape = calculate_width_concatenate_shape(shapes); - SimpleTensor<T> dst(dst_shape, dst_type); - // Compute reference int width_offset = 0; const int width_out = dst.shape().x(); @@ -74,21 +70,32 @@ SimpleTensor<T> widthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs) for(int r = 0; r < height; ++r) { const int offset = u * height * depth + d * height + r; - std::copy(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out); - src_ptr += width; + if(src.data_type() == DataType::QASYMM8 && src.quantization_info() != dst.quantization_info()) + { + std::transform(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out, [src, dst](T t) + { + const float dequantized_input = src.quantization_info().dequantize(t); + return dst.quantization_info().quantize(dequantized_input, RoundingPolicy::TO_NEAREST_UP); + }); + src_ptr += width; + } + else + { + std::copy(src_ptr, src_ptr + width, dst_ptr + width_offset + offset * width_out); + src_ptr += width; + } } } } - width_offset += width; } return dst; } -template SimpleTensor<float> widthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs); -template SimpleTensor<half> widthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs); -template SimpleTensor<uint8_t> widthconcatenate_layer(const std::vector<SimpleTensor<uint8_t>> &srcs); +template SimpleTensor<float> widthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs, SimpleTensor<float> &dst); +template SimpleTensor<half> widthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs, SimpleTensor<half> &dst); +template SimpleTensor<uint8_t> widthconcatenate_layer(const std::vector<SimpleTensor<uint8_t>> &srcs, SimpleTensor<uint8_t> &dst); } // namespace reference } // namespace validation } // namespace test |