COMPMID-814: NEScale NHWC support

Change-Id: Ibf5c624a5c5482faa42eb02bc8abe9ae0d65b0d1
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/130608
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 12 insertions, 3 deletions

diff --git a/tests/benchmark/fixtures/ScaleFixture.h b/tests/benchmark/fixtures/ScaleFixture.h
index cd51f5778f..b2fbd9c3b6 100644
--- a/tests/benchmark/fixtures/ScaleFixture.h
+++ b/tests/benchmark/fixtures/ScaleFixture.h
@@ -41,11 +41,17 @@ class ScaleFixture : public framework::Fixture
 {
 public:
     template <typename...>
-    void setup(TensorShape shape, DataType data_type, InterpolationPolicy policy, BorderMode border_mode, SamplingPolicy sampling_policy)
+    void setup(TensorShape shape, DataType data_type, DataLayout data_layout, InterpolationPolicy policy, BorderMode border_mode, SamplingPolicy sampling_policy)
     {
         constexpr float max_width  = 8192.0f;
         constexpr float max_height = 6384.0f;
 
+        // Change shape in case of NHWC.
+        if(data_layout == DataLayout::NHWC)
+        {
+            permute(shape, PermutationVector(2U, 0U, 1U));
+        }
+
         std::mt19937                          generator(library->seed());
         std::uniform_real_distribution<float> distribution_float(0.25f, 3.0f);
         float                                 scale_x = distribution_float(generator);
@@ -57,9 +63,12 @@ public:
         std::uniform_int_distribution<uint8_t> distribution_u8(0, 255);
         uint8_t                                constant_border_value = static_cast<uint8_t>(distribution_u8(generator));
 
+        const int idx_width  = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
+        const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT);
+
         TensorShape shape_scaled(shape);
-        shape_scaled.set(0, shape[0] * scale_x);
-        shape_scaled.set(1, shape[1] * scale_y);
+        shape_scaled.set(idx_width, shape[idx_width] * scale_x);
+        shape_scaled.set(idx_height, shape[idx_height] * scale_y);
 
         // Create tensors
         src = create_tensor<TensorType>(shape, data_type);