COMPMID-647: Exclude padding pixels from averaging factor.

Adds support for excluding the padding pixels from the average scaling
factor calculation.

Change-Id: Ia13fbfeae235aff564db74191613921848231a01
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/93715
Reviewed-by: Robert Hughes <robert.hughes@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>

4 files changed, 41 insertions, 26 deletions

diff --git a/tests/validation/CL/PoolingLayer.cpp b/tests/validation/CL/PoolingLayer.cpp
index 809c80f28c..87b86fedf2 100644
--- a/tests/validation/CL/PoolingLayer.cpp
+++ b/tests/validation/CL/PoolingLayer.cpp
@@ -44,13 +44,14 @@ namespace validation
 namespace
 {
 /** Input data set for float data types */
-const auto PoolingLayerDatasetFP = combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { 2, 3, 4, 7, 9 })),
-                                           framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) }));
+const auto PoolingLayerDatasetFP = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { 2, 3, 4, 7, 9 })),
+                                                   framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
+                                           framework::dataset::make("ExcludePadding", { true, false }));
 
 /** Input data set for quantized data types */
-const auto PoolingLayerDatasetQS = combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { 2, 3 })),
-                                           framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) }));
-
+const auto PoolingLayerDatasetQS = combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { 2, 3 })),
+                                                   framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
+                                           framework::dataset::make("ExcludePadding", { true, false }));
 constexpr AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for float types */
 constexpr AbsoluteTolerance<float> tolerance_f16(0.01f);  /**< Tolerance value for comparing reference's output against implementation's output for float types */
 constexpr AbsoluteTolerance<float> tolerance_qs8(3);      /**< Tolerance value for comparing reference's output against implementation's output for quantized input */
diff --git a/tests/validation/CPP/PoolingLayer.cpp b/tests/validation/CPP/PoolingLayer.cpp
index 85a8343d87..4f755ce2c4 100644
--- a/tests/validation/CPP/PoolingLayer.cpp
+++ b/tests/validation/CPP/PoolingLayer.cpp
@@ -54,12 +54,13 @@ TensorShape calculate_output_shape(TensorShape shape, PoolingLayerInfo info)
 template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type>
 SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, PoolingLayerInfo info)
 {
-    const int   pool_size     = info.pool_size();
-    PoolingType type          = info.pool_type();
-    int         pool_stride_x = info.pad_stride_info().stride().first;
-    int         pool_stride_y = info.pad_stride_info().stride().second;
-    int         pad_x         = info.pad_stride_info().pad().first;
-    int         pad_y         = info.pad_stride_info().pad().second;
+    const int   pool_size       = info.pool_size();
+    PoolingType type            = info.pool_type();
+    int         pool_stride_x   = info.pad_stride_info().stride().first;
+    int         pool_stride_y   = info.pad_stride_info().stride().second;
+    int         pad_x           = info.pad_stride_info().pad().first;
+    int         pad_y           = info.pad_stride_info().pad().second;
+    bool        exclude_padding = info.exclude_padding();
 
     const auto w_src      = static_cast<int>(src.shape()[0]);
     const auto h_src      = static_cast<int>(src.shape()[1]);
@@ -122,6 +123,11 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, PoolingLayerInfo info)
                     hstart     = std::max(hstart, 0);
                     wend       = std::min(wend, w_src);
                     hend       = std::min(hend, h_src);
+                    // Exclude padding pixels from the average
+                    if(exclude_padding)
+                    {
+                        pool = (hend - hstart) * (wend - wstart);
+                    }
 
                     if(type == PoolingType::AVG)
                     {
@@ -157,12 +163,13 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, PoolingLayerInfo info)
 template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type>
 SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, PoolingLayerInfo info)
 {
-    const int   pool_size     = info.pool_size();
-    PoolingType type          = info.pool_type();
-    int         pool_stride_x = info.pad_stride_info().stride().first;
-    int         pool_stride_y = info.pad_stride_info().stride().second;
-    int         pad_x         = info.pad_stride_info().pad().first;
-    int         pad_y         = info.pad_stride_info().pad().second;
+    const int   pool_size       = info.pool_size();
+    PoolingType type            = info.pool_type();
+    int         pool_stride_x   = info.pad_stride_info().stride().first;
+    int         pool_stride_y   = info.pad_stride_info().stride().second;
+    int         pad_x           = info.pad_stride_info().pad().first;
+    int         pad_y           = info.pad_stride_info().pad().second;
+    bool        exclude_padding = info.exclude_padding();
 
     const auto w_src      = static_cast<int>(src.shape()[0]);
     const auto h_src      = static_cast<int>(src.shape()[1]);
@@ -224,6 +231,11 @@ SimpleTensor<T> pooling_layer(const SimpleTensor<T> &src, PoolingLayerInfo info)
                     hstart     = std::max(hstart, 0);
                     wend       = std::min(wend, w_src);
                     hend       = std::min(hend, h_src);
+                    // Exclude padding pixels from the average
+                    if(exclude_padding)
+                    {
+                        pool = (hend - hstart) * (wend - wstart);
+                    }
 
                     using namespace fixed_point_arithmetic;
 
diff --git a/tests/validation/NEON/PoolingLayer.cpp b/tests/validation/NEON/PoolingLayer.cpp
index a721fb9d15..13384620bd 100644
--- a/tests/validation/NEON/PoolingLayer.cpp
+++ b/tests/validation/NEON/PoolingLayer.cpp
@@ -44,12 +44,14 @@ namespace validation
 namespace
 {
 /** Input data set for float data types */
-const auto PoolingLayerDatasetFP = combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { 2, 3, 7, 9 })),
-                                           framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) }));
+const auto PoolingLayerDatasetFP = combine(combine(combine(datasets::PoolingTypes(), framework::dataset::make("PoolingSize", { 2, 3, 7, 9 })),
+                                                   framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
+                                           framework::dataset::make("ExcludePadding", { true, false }));
 
 /** Input data set for quantized data types */
-const auto PoolingLayerDatasetQS = combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { 2, 3 })),
-                                           framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) }));
+const auto PoolingLayerDatasetQS = combine(combine(combine(framework::dataset::make("PoolingType", { PoolingType::MAX, PoolingType::AVG }), framework::dataset::make("PoolingSize", { 2, 3 })),
+                                                   framework::dataset::make("PadStride", { PadStrideInfo(1, 1, 0, 0), PadStrideInfo(2, 1, 0, 0), PadStrideInfo(1, 2, 1, 1), PadStrideInfo(2, 2, 1, 0) })),
+                                           framework::dataset::make("ExcludePadding", { false }));
 
 constexpr AbsoluteTolerance<float> tolerance_f32(0.001f); /**< Tolerance value for comparing reference's output against implementation's output for float types */
 #ifdef ARM_COMPUTE_AARCH64_V8_2
diff --git a/tests/validation/fixtures/PoolingLayerFixture.h b/tests/validation/fixtures/PoolingLayerFixture.h
index 775c4125fc..09b9e0ef1a 100644
--- a/tests/validation/fixtures/PoolingLayerFixture.h
+++ b/tests/validation/fixtures/PoolingLayerFixture.h
@@ -47,10 +47,10 @@ class PoolingLayerValidationFixedPointFixture : public framework::Fixture
 {
 public:
     template <typename...>
-    void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, DataType data_type, int fractional_bits)
+    void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type, int fractional_bits)
     {
         _fractional_bits = fractional_bits;
-        PoolingLayerInfo info(pool_type, pool_size, pad_stride_info);
+        PoolingLayerInfo info(pool_type, pool_size, pad_stride_info, exclude_padding);
 
         _target    = compute_target(shape, info, data_type, fractional_bits);
         _reference = compute_reference(shape, info, data_type, fractional_bits);
@@ -123,9 +123,9 @@ class PoolingLayerValidationFixture : public PoolingLayerValidationFixedPointFix
 {
 public:
     template <typename...>
-    void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, DataType data_type)
+    void setup(TensorShape shape, PoolingType pool_type, int pool_size, PadStrideInfo pad_stride_info, bool exclude_padding, DataType data_type)
     {
-        PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, pool_size, pad_stride_info, data_type, 0);
+        PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, pool_size, pad_stride_info, exclude_padding, data_type, 0);
     }
 };
 
@@ -136,7 +136,7 @@ public:
     template <typename...>
     void setup(TensorShape shape, PoolingType pool_type, DataType data_type)
     {
-        PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, shape.x(), PadStrideInfo(1, 1, 0, 0), data_type, 0);
+        PoolingLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape, pool_type, shape.x(), PadStrideInfo(1, 1, 0, 0), true, data_type, 0);
     }
 };
 } // namespace validation