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>

1 files changed, 19 insertions, 11 deletions

diff --git a/tests/validation/reference/DepthConcatenateLayer.cpp b/tests/validation/reference/DepthConcatenateLayer.cpp
index 90fbd915b1..6551f0c79e 100644
--- a/tests/validation/reference/DepthConcatenateLayer.cpp
+++ b/tests/validation/reference/DepthConcatenateLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -34,7 +34,7 @@ namespace validation
 namespace reference
 {
 template <typename T>
-SimpleTensor<T> depthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs)
+SimpleTensor<T> depthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs, SimpleTensor<T> &dst)
 {
     // Create reference
     std::vector<TensorShape> shapes;
@@ -44,10 +44,6 @@ SimpleTensor<T> depthconcatenate_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_depth_concatenate_shape(shapes);
-    SimpleTensor<T> dst(dst_shape, dst_type);
-
     // Compute reference
     int       depth_offset = 0;
     const int width_out    = dst.shape().x();
@@ -80,8 +76,20 @@ SimpleTensor<T> depthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs)
             {
                 for(int r = 0; r < height; ++r)
                 {
-                    std::copy(src_ptr, src_ptr + width, dst.data() + offset_to_first_element + d * out_stride_z + r * 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.data() + offset_to_first_element + d * out_stride_z + r * 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.data() + offset_to_first_element + d * out_stride_z + r * width_out);
+                        src_ptr += width;
+                    }
                 }
             }
         }
@@ -92,9 +100,9 @@ SimpleTensor<T> depthconcatenate_layer(const std::vector<SimpleTensor<T>> &srcs)
     return dst;
 }
 
-template SimpleTensor<uint8_t> depthconcatenate_layer(const std::vector<SimpleTensor<uint8_t>> &srcs);
-template SimpleTensor<float> depthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs);
-template SimpleTensor<half> depthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs);
+template SimpleTensor<uint8_t> depthconcatenate_layer(const std::vector<SimpleTensor<uint8_t>> &srcs, SimpleTensor<uint8_t> &dst);
+template SimpleTensor<float> depthconcatenate_layer(const std::vector<SimpleTensor<float>> &srcs, SimpleTensor<float> &dst);
+template SimpleTensor<half> depthconcatenate_layer(const std::vector<SimpleTensor<half>> &srcs, SimpleTensor<half> &dst);
 } // namespace reference
 } // namespace validation
 } // namespace test