Mixed data-layout testing on high priority operators

Change data layouts after the configure in validation tests for:
  - Scale
  - Pooling
  - FullyConnected
  - DepthwiseConvolution
  - DirectConvolution
  - FFTConvolution
  - WinogradConvolution
  - GEMMConvolution (Indirect GEMM included)
Extending fixtures

Fixes for new mixed data layout tests

Resolves: COMPMID-4162
Change-Id: I2f2eb2075f7e24ab3872249d88cadb57b82c5dde
Signed-off-by: Manuel Bottini <manuel.bottini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5326
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

1 files changed, 32 insertions, 8 deletions

diff --git a/tests/validation/fixtures/PoolingLayerFixture.h b/tests/validation/fixtures/PoolingLayerFixture.h
index af078d4ce3..ee81ff5538 100644
--- a/tests/validation/fixtures/PoolingLayerFixture.h
+++ b/tests/validation/fixtures/PoolingLayerFixture.h
@@ -47,14 +47,31 @@ class PoolingLayerValidationGenericFixture : public framework::Fixture
 public:
     template <typename...>
     void setup(TensorShape shape, PoolingLayerInfo pool_info, DataType data_type, DataLayout data_layout, bool indices = false,
-               QuantizationInfo input_qinfo = QuantizationInfo(), QuantizationInfo output_qinfo = QuantizationInfo())
+               QuantizationInfo input_qinfo = QuantizationInfo(), QuantizationInfo output_qinfo = QuantizationInfo(), bool mixed_layout = false)
     {
+        _mixed_layout = mixed_layout;
         _pool_info = pool_info;
         _target    = compute_target(shape, pool_info, data_type, data_layout, input_qinfo, output_qinfo, indices);
         _reference = compute_reference(shape, pool_info, data_type, data_layout, input_qinfo, output_qinfo, indices);
     }
 
 protected:
+
+    void mix_layout(FunctionType &layer, TensorType &src, TensorType &dst)
+    {
+        const DataLayout data_layout = src.info()->data_layout();
+        // Test Multi DataLayout graph cases, when the data layout changes after configure
+        src.info()->set_data_layout(data_layout == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW);
+        dst.info()->set_data_layout(data_layout == DataLayout::NCHW ? DataLayout::NHWC : DataLayout::NCHW);
+
+        // Compute Convolution function
+        layer.run();
+
+        // Reinstating original data layout for the test suite to properly check the values
+        src.info()->set_data_layout(data_layout);
+        dst.info()->set_data_layout(data_layout);
+    }
+
     template <typename U>
     void fill(U &&tensor)
     {
@@ -110,9 +127,15 @@ protected:
         // Fill tensors
         fill(AccessorType(src));
 
-        // Compute function
-        pool_layer.run();
-
+        if(_mixed_layout)
+        {
+            mix_layout(pool_layer, src, dst);
+        }
+        else
+        {
+            // Compute function
+            pool_layer.run();
+        }
         return dst;
     }
 
@@ -129,6 +152,7 @@ protected:
     TensorType             _target{};
     SimpleTensor<T>        _reference{};
     PoolingLayerInfo       _pool_info{};
+    bool                   _mixed_layout{false};
     TensorType             _target_indices{};
     SimpleTensor<uint32_t> _ref_indices{};
 };
@@ -144,7 +168,7 @@ public:
     }
 };
 
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false>
 class PoolingLayerValidationFixture : public PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
 {
 public:
@@ -152,7 +176,7 @@ public:
     void setup(TensorShape shape, PoolingType pool_type, Size2D pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type, DataLayout data_layout)
     {
         PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type, pool_size, data_layout, pad_stride_info, exclude_padding),
-                                                                                               data_type, data_layout);
+                                                                                               data_type, data_layout, false, mixed_layout);
     }
 };
 
@@ -168,7 +192,7 @@ public:
     }
 };
 
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
+template <typename TensorType, typename AccessorType, typename FunctionType, typename T, bool mixed_layout = false>
 class PoolingLayerValidationQuantizedFixture : public PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>
 {
 public:
@@ -177,7 +201,7 @@ public:
                QuantizationInfo input_qinfo = QuantizationInfo(), QuantizationInfo output_qinfo = QuantizationInfo())
     {
         PoolingLayerValidationGenericFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, PoolingLayerInfo(pool_type, pool_size, data_layout, pad_stride_info, exclude_padding),
-                                                                                               data_type, data_layout, false, input_qinfo, output_qinfo);
+                                                                                               data_type, data_layout, false, input_qinfo, output_qinfo, mixed_layout);
     }
 };